[{"data":1,"prerenderedAt":1671},["ShallowReactive",2],{"es-ai-connect/prompt-library":3,"es-global-content":252,"es-page-global-content":1625,"prompt-library-role-entries-es":1626,"prompt-library-topic-entries-es":1646},{"name":4,"created_at":5,"published_at":6,"updated_at":7,"id":8,"uuid":9,"content":10,"slug":237,"full_slug":238,"sort_by_date":17,"position":239,"tag_list":240,"is_startpage":14,"parent_id":241,"meta_data":17,"group_id":242,"first_published_at":6,"release_id":17,"lang":243,"path":17,"alternates":244,"default_full_slug":245,"translated_slugs":246},"AI Connect: Prompt Library","2026-08-31T12:31:03.040Z","2026-09-02T08:05:42.850Z","2026-09-02T08:05:42.884Z",214998479079385,"db2ea245-a4b8-4373-9708-e132cc7d5a03",{"seo":11,"_uid":26,"footer":27,"component":28,"components":29,"hideNavbar":14,"footerTheme":233,"lightNavbar":14,"hideIntercom":14,"unfixedNavbar":14,"abTestRollouts":234,"navbarCustomCtas":235,"confettiAnimation":14,"disabledLanguages":236,"disableNavbarLogoLink":14,"onPageViewSegmentEvent":18,"disableAnnoucementBanner":14,"disableNavbarScrollAnimation":14},[12],{"_uid":13,"noIndex":14,"component":15,"metaImage":16,"metaFields":21},"b7c368a1-af92-40f0-87bf-a8e281cee7b5",false,"seo",{"id":17,"alt":17,"name":18,"focus":17,"title":17,"source":17,"filename":18,"copyright":17,"fieldtype":19,"meta_data":20},null,"","asset",{},{"_uid":22,"title":23,"plugin":24,"description":25},"2c0729cc-5633-4fef-90e7-6012730cf6ee","Spendesk AI Connect: Finance Prompt Library","meta-fields","Ready-to-use AI prompts for finance teams. Run spend analysis, budget reviews and variance commentary on your data — with Spendesk AI Connect.","5e925323-a97e-40b9-a5e0-99845c14598f","normal","page",[30,69],{"cta":31,"_uid":32,"title":33,"eyebrow":45,"subtitle":49,"component":38,"textAlign":18,"eyebrowPill":14,"checkmarkList":14,"flexibleSection":58,"sectionSettings":59,"displaySeparator":14,"breakLineOnMobile":14,"subtitleLeftBorder":14,"customTitleFontSize":18},[],"d8469f2c-da93-4d4f-9d62-11d6cfc28196",{"type":34,"attrs":35,"content":36},"doc",{"backgroundColor":17},[37],{"type":38,"attrs":39,"content":41},"heading",{"level":40,"textAlign":17},1,[42],{"text":43,"type":44},"Finance-grade answers at your fingertips","text",{"type":34,"content":46},[47],{"type":48},"paragraph",{"type":34,"attrs":50,"content":51},{"backgroundColor":17},[52],{"type":48,"attrs":53,"content":55},{"textAlign":17,"key":54},"p-0",[56],{"text":57,"type":44},"Pre-tested prompts for finance teams. Manually upload your data for static responses, or connect it using our MCP for live, AI-ready data.",[],[60],{"_uid":61,"hide":14,"theme":62,"anchorId":18,"component":63,"spacingTop":18,"colorSettings":64,"hideOnDevices":65,"spacingBottom":66,"decorativeBlob":18,"decorativeLine":18,"floatingImages":67,"variableOverrides":68,"overlapPreviousSection":14},"e69094a8-8d1b-4746-86c6-bae944e0be1a","white-theme","sectionSettings",[],[],"no-padding-bottom",[],[],{"cta":70,"_uid":90,"prompts":91,"component":224,"sectionSettings":225,"searchPlaceholder":232},[71],{"tag":18,"_uid":72,"hide":14,"icon":73,"link":75,"type":18,"label":87,"style":88,"component":89,"mobileLabel":18,"onClickEvent":18,"openInANewTab":14,"horizontalFill":14},"80d55c6d-3f96-4dfd-8cd7-b0874b793b44",{"id":17,"alt":17,"name":18,"focus":17,"title":17,"source":17,"filename":18,"copyright":17,"fieldtype":19,"meta_data":74},{},{"id":76,"url":18,"linktype":77,"fieldtype":78,"cached_url":79,"prep":80,"story":81},"92c675ca-b9a9-4a17-9ac3-8b5dd3221fc4","story","multilink","/es/schedule-a-demo/",true,{"name":82,"id":83,"uuid":76,"slug":84,"url":85,"full_slug":86,"_stopResolving":80},"Schedule a demo",126838129,"schedule-a-demo","schedule-a-demo/","es/schedule-a-demo/","Book a demo","primary","cta","f2412a47-ac42-472f-86c7-c294f80f3f9a",[92,99,104,108,113,117,122,128,132,136,141,145,149,154,158,162,166,170,174,179,183,187,191,195,199,204,208,212,216,220],{"_uid":93,"role":94,"title":95,"topic":96,"prompt":97,"component":98},"d5ef11af-a0c7-4a4c-9508-474c680b4467","cfo","Monthly spend overview","spend-analysis","# Monthly spend overview\n\n## Purpose\n\nAnalyse company spend for the selected period and compare it with the previous period and available budget data.\n\nCreate a concise, CFO-ready overview of total spend, key movements, recurring costs, unusual transactions and areas requiring attention.\n\nUse the uploaded files or pasted data provided by the user. Do not invent explanations. If information is missing, unclear or inconsistent, state the limitation before presenting the analysis.\n\n## Inputs\n\nUse the available data for:\n\n- Current-period spend\n- Previous-period spend, if available\n- Budget data, if available\n- Department, category, supplier and entity breakdowns, where available\n- Transaction, approval or payment status, where relevant\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the fields needed to analyse spend, compare periods and produce the requested breakdowns.\n\nConfirm:\n\n- The period covered\n- Whether the data is transactional or aggregated\n- Whether it represents actual, pending, approved, committed or budgeted spend\n- The currency or currencies used\n- Whether the reporting period is complete\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, amounts, suppliers, departments, categories, entities and statuses.\n\nIf a field is missing or its meaning is unclear, flag it and explain how this affects the analysis.\n\n### Step 1.3, Check data quality\n\nCheck for:\n\n- Missing or invalid values\n- Duplicate transactions\n- Inconsistent names or categories\n- Mixed currencies\n- Negative transactions, refunds or reversals\n- Incomplete periods\n- Unclear transaction statuses\n\nDo not silently exclude problematic records. State how important data quality issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total spend\n- Number of transactions\n- Average transaction value\n- Spend by department, category, supplier and entity\n- Change compared with the previous period\n- Variance against budget\n- Recurring and one-off spend\n- Unusual or potentially duplicate transactions\n\nShow both absolute and percentage changes where meaningful. Do not calculate a percentage when the comparison value is zero or unavailable.\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify the largest increases and decreases in spend.\n\nFor each significant movement, show:\n\n- The affected area\n- The current and comparison amounts\n- The absolute and percentage change\n- The transactions, suppliers or categories contributing to the movement\n- Whether the movement appears recurring, one-off or unclear\n\nOnly describe a reason as confirmed when it is supported by the data. Otherwise, label it as a possible explanation or question for review.\n\n### Step 2.3, Identify areas for review\n\nIdentify:\n\n- Material increases or decreases\n- Spending above budget\n- New suppliers or spending areas\n- Significant recurring costs\n- Unusual or potentially duplicate transactions\n- Spend with missing categories, departments or suppliers\n- Pending, unapproved or unpaid spend\n- Areas affected by data quality limitations\n\nFor each priority area, provide the relevant evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nStart with a concise summary covering:\n\n- Total spend\n- Change compared with the previous period\n- Budget position, if available\n- The two or three most important movements\n- The main recurring or unusual spend\n- The most important actions or questions for review\n\n### Main analysis\n\nPresent the analysis in the following order:\n\n1. Overall spend position\n2. Comparison with the previous period\n3. Budget comparison, if available\n4. Spend by department\n5. Spend by category\n6. Spend by supplier\n7. Spend by entity\n8. Recurring and unusual spend\n9. Main areas for review\n\nUse concise tables where they improve readability. Clearly state the currency and the period covered.\n\n### Exceptions and data quality issues\n\nList the most important limitations separately.\n\nInclude:\n\n- Missing or ambiguous information\n- Incomplete periods\n- Duplicate or potentially duplicated transactions\n- Mixed currencies\n- Missing budget or comparison data\n- Negative transactions, refunds or reversals\n- Any assumptions made\n\nExplain how each issue may affect the conclusions.\n\n### Questions for review\n\nEnd with practical questions for the CFO or finance team, such as:\n\n- What explains the largest changes in spend?\n- Are the main movements one-off or recurring?\n- Which departments or categories require a budget review?\n- Are any suppliers responsible for a material increase?\n- Are any unusual transactions expected and properly classified?\n- Which recurring costs should be reviewed or renegotiated?\n\n## Output rules\n\n- Write for a CFO or finance leadership audience.\n- Lead with the most material findings.\n- Use clear, concise business language.\n- Separate facts, assumptions, interpretations and recommendations.\n- Never invent explanations.\n- Flag missing, ambiguous or unreliable data.\n- Distinguish actual, pending, approved, committed and budgeted spend.\n- Use the available level of detail without implying unsupported precision.\n- Make the output useful even when some data is unavailable.","promptCard",{"_uid":100,"role":94,"title":101,"topic":102,"prompt":103,"component":98},"e89c517d-1aaf-4606-a829-a7eaa01a4c32","Budget versus actuals executive review","budgets-variance","# Budget versus actuals executive review\n\n## Purpose\n\nCompare actual company spend with budget for the selected period and identify the main favourable and unfavourable variances.\n\nCreate a concise, CFO-ready review showing where spend is on track, where it is above or below budget, what is driving the differences and which areas require attention.\n\nUse the uploaded files or pasted data provided by the user. Do not invent explanations. If information is missing, unclear or inconsistent, state the limitation before presenting the analysis.\n\n## Inputs\n\nUse the available data for:\n\n- Actual spend for the selected period\n- Budget for the same period\n- Previous-period or year-to-date data, if available\n- Department, category, supplier and entity breakdowns, where available\n- Committed, pending or approved spend, if available\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the fields needed to compare actual spend with budget.\n\nConfirm:\n\n- The period covered by the actuals\n- The period covered by the budget\n- Whether the data is transactional or aggregated\n- Whether the amounts represent actual, pending, approved, committed or forecast spend\n- The currency or currencies used\n- Whether the periods are complete and comparable\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, actual amounts, budget amounts, suppliers, departments, categories, entities and statuses.\n\nIf actuals and budget data use different structures or levels of detail, explain how they were compared.\n\nIf a field is missing or its meaning is unclear, flag it and explain how this affects the analysis.\n\n### Step 1.3, Check data quality\n\nCheck for:\n\n- Missing or invalid values\n- Duplicate transactions or budget lines\n- Actuals without a corresponding budget\n- Budget lines without corresponding actuals\n- Inconsistent names or categories\n- Mixed currencies\n- Partial periods\n- Negative transactions, refunds or reversals\n- Unclear treatment of committed or pending spend\n- Zero or unavailable budget values\n\nDo not silently exclude problematic records. State how important data quality issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total actual spend\n- Total budget\n- Absolute variance\n- Variance percentage\n- Budget utilisation\n- Actual spend by department, category, supplier and entity\n- Budget by department, category, supplier and entity, where available\n- Committed or pending spend, if available\n- Year-to-date actuals and budget, if available\n\nFor spend data, treat spending above budget as an unfavourable variance and spending below budget as a favourable variance, unless the context indicates otherwise.\n\nDo not calculate a percentage when the budget is zero or unavailable. Keep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify the largest favourable and unfavourable variances by:\n\n- Department\n- Spend category\n- Supplier\n- Entity\n- Month or reporting period\n\nFor each significant variance, show:\n\n- The affected area\n- Actual spend\n- Budget\n- Absolute variance\n- Variance percentage, where meaningful\n- The transactions, suppliers or categories contributing to the difference\n- Whether the variance appears temporary, recurring or unclear\n\nOnly describe a reason as confirmed when it is supported by the data. Otherwise, label it as a possible explanation or question for review.\n\n### Step 2.3, Identify areas for review\n\nIdentify:\n\n- Areas materially above budget\n- Areas materially below budget\n- Spending without an identifiable budget\n- Budget lines with little or no actual spend\n- Recurring overspend\n- Significant committed or pending spend not included in actuals\n- New or unusual spending areas\n- Variances caused by changes in transaction volume, value or supplier mix\n- Areas affected by data quality limitations\n\nFor each priority area, provide the relevant evidence, potential financial implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nStart with a concise summary covering:\n\n- Total actual spend compared with total budget\n- Overall favourable or unfavourable variance\n- Budget utilisation\n- The two or three most important variances\n- Whether the main variances appear temporary, recurring or unclear\n- The most important actions or questions for review\n\n### Main analysis\n\nPresent the analysis in the following order:\n\n1. Overall budget versus actuals\n2. Variance by department\n3. Variance by category\n4. Variance by supplier\n5. Variance by entity\n6. Monthly or year-to-date trend, if available\n7. Committed, pending or approved spend, if available\n8. Main variance drivers\n9. Areas requiring management attention\n\nUse concise tables where they improve readability.\n\nFor the overall analysis, include:\n\n| Area | Actual spend | Budget | Variance | Variance % | Status |\n|---|---:|---:|---:|---:|---|\n\nUse consistent rounding and clearly state the currency and period covered.\n\n### Exceptions and data quality issues\n\nList the most important limitations separately.\n\nInclude:\n\n- Missing or ambiguous information\n- Non-comparable periods\n- Incomplete actuals or budget data\n- Actuals without a budget\n- Budget without actuals\n- Duplicate or potentially duplicated records\n- Mixed currencies\n- Zero or unavailable budget values\n- Negative transactions, refunds or reversals\n- Any assumptions made\n\nExplain how each issue may affect the conclusions.\n\n### Questions for review\n\nEnd with practical questions for the CFO or finance team, such as:\n\n- Which of the largest unfavourable variances are expected?\n- Are the main variances caused by timing, volume, pricing or classification?\n- Which budget lines should be reforecast?\n- Is any committed or pending spend missing from the current actuals?\n- Are there recurring overspend patterns that require corrective action?\n- Are any areas below budget because spending has been delayed?\n- Which data quality issues should be resolved before the next reporting cycle?\n\n## Output rules\n\n- Write for a CFO or finance leadership audience.\n- Lead with the most material variances.\n- Use clear, concise business language.\n- Separate facts, assumptions, interpretations and recommendations.\n- Never invent explanations for variances.\n- Flag missing, ambiguous or unreliable data.\n- Show both absolute and percentage variances where meaningful.\n- Do not calculate percentages when the budget is zero or unavailable.\n- Distinguish actual, pending, approved, committed and forecast spend.\n- Do not treat underspend as automatically positive.\n- Keep currencies separate unless a reliable conversion method is provided.\n- Use the available level of detail without implying unsupported precision.\n- Make the output useful even when some data is unavailable.\n",{"_uid":105,"role":94,"title":106,"topic":102,"prompt":107,"component":98},"4e6a9216-ae5e-4f6d-b577-d7a7a2032536","Variance commentary for leadership","# Variance commentary for leadership\n\n## Purpose\n\nExplain the most significant budget or spend variances in a clear, leadership-ready format.\n\nGo beyond calculating the difference between actual and budgeted spend. Identify what changed, how much it changed, what appears to be driving the movement, whether it is temporary or recurring, and what the leadership team may need to know or decide.\n\nUse the uploaded files or pasted data provided by the user. Do not invent explanations. If information is missing, unclear or inconsistent, state the limitation before presenting the commentary.\n\n## Inputs\n\nUse the available data for:\n\n- Actual spend and budget\n- Previous-period or year-to-date comparisons, if available\n- Variance calculations, if already provided\n- Department, category, supplier and entity breakdowns\n- Transaction volume and average transaction value, if available\n- Business context or explanations provided by the user\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to explain the main variances.\n\nConfirm:\n\n- The period covered\n- Whether actuals and budget are comparable\n- The currency or currencies used\n- The dimensions available for analysis\n- Whether the data is transactional or aggregated\n- Whether the period is complete\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for actual spend, budget, variance, dates, departments, categories, suppliers, entities and transaction details.\n\nIf a variance is already calculated, validate the calculation where possible.\n\nIf a field is missing or its meaning is unclear, flag it and explain how this affects the commentary.\n\n### Step 1.3, Check data quality\n\nCheck for:\n\n- Missing or inconsistent values\n- Duplicate records\n- Non-comparable periods\n- Mixed currencies\n- Variances without supporting transaction detail\n- Negative transactions, refunds or reversals\n- Incomplete periods\n- Unclear or unsupported explanations\n\nDo not silently exclude problematic records. State how important data quality issues affect the conclusions.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nFor each material variance, calculate or validate:\n\n- Actual spend\n- Budget\n- Absolute variance\n- Variance percentage\n- Previous-period spend, if available\n- Change compared with the previous period\n- Transaction volume, if available\n- Average transaction value, if available\n\nPrioritise variances based on both financial materiality and relative change.\n\nDo not calculate a percentage when the budget or comparison value is zero or unavailable.\n\n### Step 2.2, Identify the main movements\n\nIdentify the largest favourable and unfavourable variances by:\n\n- Department\n- Spend category\n- Supplier\n- Entity\n- Month or reporting period\n\nFor each significant variance, assess whether the movement appears to be caused by:\n\n- Timing\n- Transaction volume\n- Average transaction value\n- Pricing\n- Supplier or category mix\n- A one-off purchase\n- A recurring pattern\n- A budget classification issue\n- Missing or incomplete data\n\nOnly describe a cause as confirmed when it is supported by the data or by context provided by the user.\n\nClassify each explanation as:\n\n- Confirmed driver\n- Likely driver\n- Possible explanation\n- Unknown or requiring validation\n\n### Step 2.3, Identify areas for review\n\nIdentify:\n\n- Variances that require leadership attention\n- Recurring unfavourable variances\n- One-off variances that materially affect the period\n- Variances that may require reforecasting\n- Variances with potential operational or financial impact\n- Variances that cannot be explained reliably\n- Areas where corrective action may be required\n\nFor each priority variance, provide:\n\n- The affected area\n- The financial impact\n- The evidence\n- The explanation and its confidence level\n- Whether it is likely to continue\n- The recommended follow-up action\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nStart with a concise summary covering:\n\n- The most material variances\n- The overall financial impact\n- The main confirmed or likely drivers\n- Whether the variances appear temporary or recurring\n- The main risks or decisions for leadership\n\n### Main analysis\n\nPresent the analysis in the following order:\n\n1. Overall variance picture\n2. Largest unfavourable variances\n3. Largest favourable variances\n4. Main variance drivers\n5. One-off versus recurring movements\n6. Variances requiring reforecasting or corrective action\n7. Variances requiring further investigation\n\nFor each material variance, include:\n\n| Area | Actual spend | Budget | Variance | Variance % | Commentary | Confidence |\n|---|---:|---:|---:|---:|---|---|\n\nWrite the commentary in a format that can be reused in a leadership meeting, finance report or executive update.\n\n### Exceptions and data quality issues\n\nList the most important limitations separately.\n\nInclude:\n\n- Missing or ambiguous information\n- Unsupported explanations\n- Non-comparable periods\n- Incomplete data\n- Mixed currencies\n- Duplicate or potentially duplicated records\n- Variances without sufficient transaction detail\n- Any assumptions made\n\nExplain how each issue may affect the commentary.\n\n### Questions for review\n\nEnd with practical questions for the CFO or leadership team, such as:\n\n- Which variances are expected and which require action?\n- Are the main movements one-off or recurring?\n- Should any budget or forecast be revised?\n- Are the reported explanations supported by transaction data?\n- Which spending decisions should be reviewed?\n- What additional information is needed before confirming the cause?\n- Which variances should be monitored in the next reporting period?\n\n## Output rules\n\n- Write for a CFO or finance leadership audience.\n- Make the commentary clear enough to reuse in an executive meeting or report.\n- Focus on the most material variances.\n- Separate facts, explanations, assumptions and recommendations.\n- Never invent the cause of a variance.\n- Clearly label the confidence level of each explanation.\n- Distinguish one-off, recurring, timing-related and unresolved variances.\n- Use both absolute and percentage variances where meaningful.\n- Do not calculate percentages when the comparison value is zero or unavailable.\n- Flag missing, ambiguous or unreliable data.\n- Use clear, concise business language.\n- End with practical actions or questions for review.",{"_uid":109,"role":94,"title":110,"topic":111,"prompt":112,"component":98},"c4c2288e-dbf6-47e6-8143-91a6fd5c64f8","Supplier concentration risk","suppliers-procurement","# Supplier concentration risk\n\n## Purpose\n\nAnalyse how much company spend is concentrated among a small number of suppliers, categories, departments or entities.\n\nCreate a concise, CFO-ready review showing supplier dependency, material concentrations, potential risks and areas where mitigation or further review may be required.\n\nUse the uploaded files or pasted data provided by the user. Do not assume that supplier concentration automatically represents risk. Explain the evidence supporting each finding.\n\n## Inputs\n\nUse the available data for:\n\n- Current and previous-period spend\n- Supplier and category information\n- Department and entity breakdowns\n- Budget data, if available\n- Contract, renewal or payment information, if available\n- Supplier status or business context provided by the user\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to analyse supplier concentration.\n\nConfirm:\n\n- The period covered\n- Whether the data is transactional or aggregated\n- The currency or currencies used\n- Whether supplier names are consistently recorded\n- Whether the reporting period is complete\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, amounts, suppliers, categories, departments, entities and statuses.\n\nIf supplier names appear under different names, group them only when the data supports that they refer to the same supplier. If the relationship is unclear, flag it rather than combining the records.\n\nIf a field is missing or its meaning is unclear, explain how this affects the analysis.\n\n### Step 1.3, Check data quality\n\nCheck for:\n\n- Missing or inconsistent supplier names\n- Duplicate transactions\n- Mixed currencies\n- Missing categories, departments or entities\n- Partial periods\n- Refunds or reversals\n- Suppliers that may have been split across different names\n- Spend without an identifiable supplier\n\nDo not silently exclude problematic records. State how important data quality issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total spend\n- Spend by supplier\n- Percentage of total spend by supplier\n- Top suppliers by spend\n- Number of suppliers\n- Spend concentration among the top 5 and top 10 suppliers\n- Supplier concentration by category, department and entity\n- Change compared with the previous period\n- Budget variance for concentrated suppliers, if available\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify:\n\n- Suppliers representing a material share of total spend\n- Categories or departments dependent on a small number of suppliers\n- Suppliers with rapidly increasing spend\n- Concentration that has increased or decreased over time\n- Similar services or categories spread across multiple suppliers\n- Supplier concentration linked to recurring or critical spend\n\nFor each significant concentration, show:\n\n- The supplier or group of suppliers\n- The relevant spend amount\n- The percentage of total spend\n- The affected category, department or entity\n- The change over time\n- Whether the concentration appears expected, strategic or potentially risky\n\nOnly describe a business or operational risk as confirmed when it is supported by the data or context provided by the user.\n\n### Step 2.3, Identify areas for review\n\nIdentify:\n\n- High dependency on one supplier\n- Categories with limited supplier alternatives\n- Critical or recurring spend concentrated in one supplier\n- Suppliers with material increases in spend\n- Potential duplicate supplier records\n- Concentrated spend without an identifiable budget or owner\n- Areas where data quality prevents a reliable assessment\n\nFor each priority area, provide the evidence, potential implication and recommended mitigation or follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nStart with a concise summary covering:\n\n- Overall supplier concentration\n- The top suppliers by spend\n- The most concentrated categories, departments or entities\n- The main potential risks\n- The most important mitigation actions or questions for review\n\n### Main analysis\n\nPresent the analysis in the following order:\n\n1. Overall supplier concentration\n2. Top suppliers by spend\n3. Concentration by category, department and entity\n4. Changes compared with the previous period\n5. Recurring or critical supplier spend\n6. Potential supplier dependency risks\n7. Recommended mitigation actions\n\nUse concise tables where they improve readability.\n\nFor the main analysis, include:\n\n| Supplier or area | Spend | Share of total spend | Change | Concentration level | Review status |\n|---|---:|---:|---:|---|---|\n\nClearly state the currency and period covered.\n\n### Exceptions and data quality issues\n\nList the most important limitations separately.\n\nInclude:\n\n- Missing or ambiguous supplier information\n- Inconsistent supplier names\n- Mixed currencies\n- Partial periods\n- Duplicate or potentially duplicated records\n- Spend without an identifiable supplier\n- Any assumptions made\n\nExplain how each issue may affect the conclusions.\n\n### Questions for review\n\nEnd with practical questions for the CFO or finance team, such as:\n\n- Which supplier dependencies are intentional and which require mitigation?\n- Are there viable alternative suppliers for the most concentrated categories?\n- Are any critical or recurring services dependent on one supplier?\n- Has supplier concentration increased recently?\n- Should any supplier relationship be renegotiated or reviewed?\n- Which data quality issues should be resolved before making a supplier risk decision?\n\n## Output rules\n\n- Write for a CFO or finance leadership audience.\n- Focus on material supplier dependencies and changes.\n- Separate facts, assumptions, interpretations and recommendations.\n- Do not treat concentration as risk without explaining the relevant evidence.\n- Never invent supplier alternatives, contract terms or business-criticality information.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- Use clear, concise business language.\n- End with practical mitigation actions or questions for review.",{"_uid":114,"role":94,"title":115,"topic":96,"prompt":116,"component":98},"36fabddc-b375-4784-a0e9-4b68fd700677","Recurring spend review","# Recurring spend review\n\n## Purpose\n\nIdentify and analyse recurring company spend across suppliers, categories, departments and entities.\n\nCreate a CFO-ready overview of recurring costs, changes over time, material increases, potential duplicates, upcoming review areas and opportunities to improve visibility or control.\n\nUse the uploaded files or pasted data provided by the user. Do not assume that repeated transactions are automatically recurring. Explain the evidence supporting each recurring spend finding.\n\n## Inputs\n\nUse the available data for:\n\n- Current and previous-period spend\n- Transaction or invoice history\n- Supplier and category information\n- Department and entity breakdowns\n- Budget data, if available\n- Contract, renewal or payment frequency information, if available\n- Approval or payment status, where relevant\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to detect and analyse recurring spend.\n\nConfirm:\n\n- The period covered\n- Whether the period is long enough to identify recurring patterns\n- Whether the data is transactional, invoice-based or aggregated\n- The currency or currencies used\n- Whether the data includes refunds, reversals, pending or cancelled transactions\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, amounts, suppliers, categories, departments, entities, descriptions and statuses.\n\nIf a field is missing or its meaning is unclear, flag it and explain how this affects the analysis.\n\n### Step 1.3, Check data quality\n\nCheck for:\n\n- Missing or invalid dates\n- Missing amounts\n- Inconsistent supplier names\n- Duplicate transactions\n- Inconsistent categories\n- Mixed currencies\n- Partial periods\n- Refunds or reversals\n- Transactions that may represent the same recurring cost under different names\n\nDo not silently exclude problematic records. State how important data quality issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total recurring spend\n- Recurring spend as a percentage of total spend\n- Number of recurring suppliers or cost areas\n- Recurring spend by supplier\n- Recurring spend by category\n- Recurring spend by department and entity\n- Average recurring payment amount\n- Monthly or periodic recurring cost\n- Change compared with the previous period\n- Recurring spend above or below budget, if budget data is available\n\nDistinguish between confirmed recurring spend, likely recurring spend and spend that cannot be classified reliably.\n\n### Step 2.2, Identify the main movements\n\nIdentify:\n\n- Recurring costs that increased or decreased\n- New recurring suppliers or categories\n- Recurring costs that appear to have stopped\n- Suppliers with multiple similar recurring charges\n- Costs with changing payment amounts\n- Costs with unusual payment frequency\n- Recurring spend concentrated in one department, category or entity\n- Recurring spend that may be one-off or incorrectly classified\n\nFor each significant movement, show:\n\n- The affected supplier or area\n- The recurring amount\n- The payment pattern\n- The change over time\n- Whether the movement appears expected, unusual or unclear\n\nOnly describe a reason as confirmed when it is supported by the data or context provided by the user.\n\n### Step 2.3, Identify areas for review\n\nIdentify:\n\n- High-value recurring costs\n- Recurring costs with significant increases\n- Recurring spend without an identifiable budget\n- Potential duplicate or overlapping costs\n- Suppliers with several similar charges\n- Recurring costs with unclear ownership or classification\n- Costs that may require renewal, renegotiation or cancellation review\n- Areas affected by incomplete or unreliable data\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nStart with a concise summary covering:\n\n- Total recurring spend\n- The share of total spend represented by recurring costs\n- The largest recurring suppliers or categories\n- The most significant increases or changes\n- Potential duplicate, overlapping or unusual costs\n- The main actions or questions for review\n\n### Main analysis\n\nPresent the analysis in the following order:\n\n1. Overall recurring spend\n2. Recurring spend by supplier\n3. Recurring spend by category\n4. Recurring spend by department and entity\n5. Largest increases and decreases\n6. New, stopped or changing recurring costs\n7. Potential duplicates or overlapping spend\n8. Areas requiring review\n\nUse concise tables where they improve readability.\n\nFor the main analysis, include:\n\n| Supplier or area | Recurring spend | Frequency | Change | Budget status | Review status |\n|---|---:|---|---:|---|---|\n\nClearly state the currency and period covered.\n\n### Exceptions and data quality issues\n\nList the most important limitations separately.\n\nInclude:\n\n- Insufficient history to confirm recurring patterns\n- Missing or ambiguous information\n- Inconsistent supplier names\n- Duplicate or potentially duplicated transactions\n- Mixed currencies\n- Partial periods\n- Unclear payment frequency\n- Any assumptions made\n\nExplain how each issue may affect the conclusions.\n\n### Questions for review\n\nEnd with practical questions for the CFO or finance team, such as:\n\n- Which recurring costs should be reviewed or renegotiated?\n- Are any recurring suppliers charging for overlapping services?\n- Which recurring costs increased without a corresponding budget change?\n- Are any costs still being paid even though they appear inactive?\n- Which recurring costs should be included in the next forecast?\n- Are there recurring costs without a clear owner or category?\n- What additional information is needed to confirm the recurring pattern?\n\n## Output rules\n\n- Write for a CFO or finance leadership audience.\n- Focus on material recurring costs and changes.\n- Separate confirmed recurring spend from likely or unclear patterns.\n- Never assume that repeated transactions represent a recurring commitment without evidence.\n- Do not invent contract, renewal or cancellation information.\n- Flag missing, ambiguous or unreliable data.\n- Distinguish recurring, one-off, pending and committed spend.\n- Use clear, concise business language.\n- Highlight practical opportunities for review, control or renegotiation.\n- End with specific actions or questions for review.",{"_uid":118,"role":94,"title":119,"topic":120,"prompt":121,"component":98},"0d6bf672-85a0-4d26-89da-018f5a4ef75d","Executive spend and finance summary","reporting-reconciliation","# Executive spend and finance summary\n\n## Purpose\n\nCreate a concise executive summary of the company’s spend and finance position using the available spend, budget, variance, supplier and recurring-cost data.\n\nSynthesize the most important findings for the CFO without repeating every detail from the underlying analyses. Focus on the overall financial picture, key movements, risks, decisions and actions.\n\nUse the uploaded files or pasted data provided by the user. If previous analyses are provided, consolidate them and identify any inconsistencies between them.\n\n## Inputs\n\nUse the available data for:\n\n- Current and previous-period spend\n- Budget and actuals\n- Variance analysis\n- Supplier and procurement data\n- Recurring spend\n- Department, category and entity breakdowns\n- Pending, approved or committed spend, if available\n- Previous reports or analysis provided by the user\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to produce an executive spend and finance summary.\n\nConfirm:\n\n- The reporting period\n- The scope of the data\n- Whether the figures are actual, budgeted, pending, committed or forecast\n- The currency or currencies used\n- Whether the sources are comparable\n- Whether the period is complete\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, amounts, budget, variance, suppliers, departments, categories, entities and statuses.\n\nIf previous analysis outputs are provided, identify the main metrics and conclusions contained in them.\n\nIf a field or source is missing or its meaning is unclear, flag it and explain how this affects the summary.\n\n### Step 1.3, Check data quality\n\nCheck for:\n\n- Conflicting figures between sources\n- Missing or ambiguous information\n- Duplicate records\n- Non-comparable periods\n- Mixed currencies\n- Incomplete data\n- Unsupported explanations\n- Different definitions of actual, budget, committed or forecast spend\n\nDo not silently resolve conflicting information. Explain which source was prioritised and why.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate or validate, where the data supports it:\n\n- Total actual spend\n- Total budget\n- Overall variance\n- Change compared with the previous period\n- Budget utilisation\n- Recurring spend\n- Committed or pending spend\n- Spend concentration by supplier, category, department and entity\n- Number of material exceptions\n\nDo not calculate percentages when the comparison value is zero or unavailable.\n\n### Step 2.2, Identify the main movements\n\nIdentify the most important findings across:\n\n- Overall spend\n- Budget and variance\n- Departments and categories\n- Suppliers\n- Recurring costs\n- Entities\n- Pending, approved or committed spend\n- Data quality or reporting limitations\n\nPrioritise findings based on:\n\n- Financial materiality\n- Potential business impact\n- Recurrence\n- Urgency\n- Need for leadership action\n\nAvoid duplicating detailed analysis that is already available in the source data. Summarise the conclusion and link it to the supporting evidence provided.\n\n### Step 2.3, Identify areas for review\n\nIdentify:\n\n- Material unfavourable variances\n- Significant recurring or increasing costs\n- Supplier concentration or dependency\n- Spend without a clear budget or owner\n- Risks caused by pending or committed spend\n- Areas requiring reforecasting or corrective action\n- Important unanswered questions\n- Decisions required from leadership\n\nFor each priority area, provide:\n\n- The key finding\n- The financial impact\n- The evidence\n- The potential implication\n- The recommended action or decision\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nStart with a concise CFO-ready summary covering:\n\n- The overall spend position\n- Budget and variance position\n- The most important movements\n- The main recurring or supplier-related risks\n- The most important data limitations\n- The decisions or actions required from leadership\n\n### Main analysis\n\nPresent the analysis in the following order:\n\n1. Overall financial picture\n2. Spend and budget position\n3. Main variance drivers\n4. Supplier and recurring spend findings\n5. Key risks and exceptions\n6. Recommended actions and decisions\n\nUse concise tables where they improve readability.\n\nFor each priority finding, include:\n\n| Area | Key finding | Financial impact | Risk or implication | Recommended action |\n|---|---|---:|---|---|\n\nClearly state the currency and period covered.\n\n### Exceptions and data quality issues\n\nList the most important limitations separately.\n\nInclude:\n\n- Conflicting information between sources\n- Missing or ambiguous data\n- Incomplete periods\n- Mixed currencies\n- Unsupported explanations\n- Duplicate or potentially duplicated records\n- Any assumptions made\n\nExplain how each issue may affect the conclusions.\n\n### Questions for review\n\nEnd with practical questions for the CFO or leadership team, such as:\n\n- What are the most important financial movements this period?\n- Which variances require immediate action?\n- Which recurring costs or suppliers should be reviewed?\n- Should any budget or forecast be revised?\n- What risks may arise from pending or committed spend?\n- Which decisions require leadership approval?\n- What additional information is needed before finalising the view?\n\n## Output rules\n\n- Write for a CFO or finance leadership audience.\n- Be concise and prioritise the most material findings.\n- Synthesise the available analysis instead of repeating every detail.\n- Separate facts, assumptions, interpretations and recommendations.\n- Never invent explanations or financial figures.\n- Flag conflicts, missing data and unreliable conclusions.\n- Distinguish actual, budgeted, pending, committed and forecast spend.\n- Make the recommended actions specific and practical.\n- Use clear, concise business language.\n- End with the decisions, actions and questions that require leadership attention.",{"_uid":123,"role":124,"title":125,"topic":126,"prompt":127,"component":98},"d84ac930-3ea6-40c2-a2ea-2bbb2f5a5185","controllers","Invoice reconciliation","invoices-ap","# Invoice reconciliation\n\n## Purpose\n\nCompare invoice data with available payment, purchase order or accounting data to identify matched, unmatched and inconsistent records.\n\nCreate a concise, Controller-ready reconciliation showing the main differences, open items, financial impact and actions required before reporting or close.\n\nUse the uploaded files or pasted data provided by the user. Do not invent explanations. If information is missing, unclear or inconsistent, state the limitation before presenting the analysis.\n\n## Inputs\n\nUse the available data for:\n\n- Invoice records\n- Payment or transaction records\n- Purchase order data, if available\n- Accounting or ledger export, if available\n- Supplier, entity and category information\n- Invoice, approval and payment status\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the fields needed to compare invoices with payments, purchase orders or accounting records.\n\nConfirm the periods covered, the currencies used, the available matching references and whether the sources are complete.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for invoice references, dates, amounts, suppliers, purchase orders, payments, entities, currencies and statuses.\n\nIf the sources use different structures or references, explain how they were matched. If a field is missing or unclear, flag the limitation.\n\n### Step 1.3, Check data quality\n\nCheck for missing references, duplicates, amount differences, inconsistent supplier names, mixed currencies, inconsistent periods, invoices without payments and payments without invoices.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total invoices and invoice value\n- Matched and unmatched invoice value\n- Invoices without payments\n- Payments without invoices\n- Amount mismatches\n- Records requiring review\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify the main reconciliation differences by supplier, entity, category, status and period.\n\nFor each significant difference, show the affected record or area, relevant amounts, mismatch type, supported explanation and financial or reporting impact.\n\nOnly describe a reason as confirmed when supported by the data. Otherwise, label it as a possible explanation or question for review.\n\n### Step 2.3, Identify areas for review\n\nIdentify material unmatched invoices, payments without supporting invoices, amount mismatches, suppliers with repeated issues and items that may affect month-end reporting.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the overall reconciliation status, matched and unmatched value, significant mismatches, main areas requiring attention and actions before reporting or close.\n\n### Main analysis\n\nPresent:\n\n1. Overall reconciliation status\n2. Matched and unmatched records\n3. Amount mismatches\n4. Invoices without payments\n5. Payments without invoices\n6. Main supplier, entity or category differences\n7. Open items requiring action\n\nUse concise tables where useful:\n\n| Area or record | Invoice value | Matched value | Difference | Status | Recommended action |\n|---|---:|---:|---:|---|---|\n\n### Exceptions and data quality issues\n\nList missing information, unmatched records, duplicates, mixed currencies, incomplete periods and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about urgent unmatched invoices, unsupported payments, amount mismatches, close impact, repeated supplier issues and information needed to complete the reconciliation.\n\n## Output rules\n\n- Write for a Controller or finance operations audience.\n- Focus on material differences and open items.\n- Never invent a match or explanation.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- End with practical actions required to complete the reconciliation.",{"_uid":129,"role":124,"title":130,"topic":126,"prompt":131,"component":98},"eba06623-5d38-4f7a-acfa-cb207ed4b66d","Duplicate invoice detection","# Duplicate invoice detection\n\n## Purpose\n\nIdentify duplicate or potentially duplicate invoices and assess their possible financial and operational impact.\n\nCreate a concise, Controller-ready review that distinguishes confirmed duplicates from records requiring manual validation.\n\nUse the uploaded files or pasted data provided by the user. Do not assume that similar records are duplicates. Explain the evidence supporting each finding.\n\n## Inputs\n\nUse the available data for:\n\n- Invoice records\n- Supplier information\n- Invoice references, dates and amounts\n- Currency information\n- Purchase order or payment references, if available\n- Invoice and payment status\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to detect duplicate or potentially duplicate invoices.\n\nConfirm the period covered, the currency or currencies used, the identifiers available for comparison and whether the data is complete.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for invoice references, suppliers, dates, amounts, currencies, purchase orders, descriptions and statuses.\n\nIf supplier names or invoice references use different formats, normalise them where appropriate and explain the method used.\n\n### Step 1.3, Check data quality\n\nCheck for missing invoice references, inconsistent supplier names, duplicate transaction IDs, different currencies, credit notes, refunds, reversals and legitimate recurring invoices that may resemble duplicates.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total invoices reviewed\n- Confirmed duplicate groups\n- Potential duplicate groups\n- Value of confirmed and potential duplicates\n- Suppliers affected\n- Duplicates already paid or approved\n- Duplicates still pending review\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify potential duplicates using combinations of supplier, invoice reference, amount, date, description, purchase order and payment reference.\n\nFor each potential duplicate group, show the records involved, supplier, dates, amounts, matching evidence and payment or approval status.\n\nClassify records as confirmed, potential or requiring review. Do not classify similar records as confirmed duplicates without sufficient evidence.\n\n### Step 2.3, Identify areas for review\n\nIdentify confirmed duplicates, potential duplicates, paid or approved duplicates, suppliers with repeated patterns and issues caused by formatting or data entry.\n\nFor each priority group, provide the evidence, potential financial impact and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the number and value of confirmed and potential duplicates, whether any were paid or approved, the suppliers most affected and the most important actions.\n\n### Main analysis\n\nPresent:\n\n1. Overall duplicate detection results\n2. Confirmed duplicates\n3. Potential duplicates requiring review\n4. Paid or approved duplicate invoices\n5. Suppliers with repeated patterns\n6. Data or process issues\n7. Recommended actions\n\nUse concise tables where useful:\n\n| Duplicate group | Supplier | Invoice value | Matching evidence | Status | Recommended action |\n|---|---|---:|---|---|---|\n\n### Exceptions and data quality issues\n\nList missing references, inconsistent supplier names, incomplete records, mixed currencies, legitimate recurring invoices resembling duplicates and assumptions.\n\n### Questions for review\n\nEnd with questions about priority reviews, paid or approved duplicates, repeated supplier patterns, false positives and controls needed to prevent future duplicates.\n\n## Output rules\n\n- Distinguish confirmed duplicates from potential duplicates.\n- Never label similar records as duplicates without sufficient evidence.\n- Flag missing, ambiguous or unreliable data.\n- Separate financial impact from records requiring investigation.\n- Use clear, concise business language.\n- End with practical actions to investigate, correct or prevent duplicate invoices.",{"_uid":133,"role":124,"title":134,"topic":120,"prompt":135,"component":98},"d08ad9a8-985f-4aa7-afdf-e3c4d9438c64","Month-end close readiness","# Month-end close readiness\n\n## Purpose\n\nAssess whether the available spend, invoice, approval, payment and accounting data is ready for month-end close.\n\nCreate a concise, Controller-ready review showing completed areas, open items, potential blockers, missing information and actions required before close.\n\nUse the uploaded files or pasted data provided by the user. Do not assume that an item is complete without evidence.\n\n## Inputs\n\nUse the available data for:\n\n- Invoices and credit notes\n- Spend transactions\n- Payments and approvals\n- Purchase orders, if available\n- Accounting or ledger exports, if available\n- Reconciliation results, if available\n- Close checklist or deadlines, if provided\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to assess month-end close readiness.\n\nConfirm the close period, whether it is complete, which sources represent actual, pending, approved, committed or posted data, the currencies used and whether all relevant entities are covered.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, amounts, invoices, transactions, approvals, payments, purchase orders, accounting references and statuses.\n\nIf a field or source is missing or unclear, flag it and explain how this affects the readiness assessment.\n\n### Step 1.3, Check data quality\n\nCheck for missing invoices or transactions, unmatched payments or accounting entries, unapproved or pending items, missing accounting references, duplicates, incomplete periods, mixed currencies and unclear statuses.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total spend and invoice value\n- Posted or completed value\n- Pending or unapproved value\n- Unpaid value\n- Unreconciled value\n- Number of open items\n- Items missing required information\n- Items that may affect close\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify the main open items by status, department, supplier, entity, category, financial value and age, if dates support the calculation.\n\nPrioritise items that are material, overdue, repeated or likely to delay close.\n\nFor each significant item or group, show the value, current status, missing action or information and potential impact on close.\n\n### Step 2.3, Identify areas for review\n\nIdentify material unposted or unreconciled spend, invoices awaiting approval, payments without supporting records, missing invoices or accounting references, open purchase orders, repeated close issues and items requiring manual investigation.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise overall readiness, completed, open and blocked areas, the value of material open items, potential blockers and actions required before close.\n\n### Main analysis\n\nPresent:\n\n1. Overall readiness status\n2. Completed and posted items\n3. Pending approvals and payments\n4. Unreconciled or missing items\n5. Open purchase orders or commitments\n6. Material blockers and risks\n7. Recommended actions and owners, if available\n\nUse concise tables where useful:\n\n| Area or item | Value | Current status | Close impact | Required action |\n|---|---:|---|---|---|\n\n### Exceptions and data quality issues\n\nList missing information, incomplete coverage, unmatched or unreconciled records, duplicates, mixed currencies and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about open items that must be resolved, material pending approvals or invoices, unreconciled records, open purchase orders, recurring close issues and action ownership.\n\n## Output rules\n\n- Clearly distinguish ready, open, blocked and unresolved items.\n- Prioritise material and time-sensitive issues.\n- Never assume an item is complete without evidence.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- Separate facts, assumptions, risks and recommended actions.\n- End with the actions required before month-end close.",{"_uid":137,"role":124,"title":138,"topic":139,"prompt":140,"component":98},"41d520d0-9f5d-4cd9-a2ac-a704014318e9","Expense data quality review","expense-management","# Expense data quality review\n\n## Purpose\n\nAssess the completeness, consistency and reliability of expense data for reporting, reconciliation and financial review.\n\nCreate a concise, Controller-ready review showing the main data quality issues, their potential impact and the actions required to improve the reliability of the analysis.\n\nUse the uploaded files or pasted data provided by the user. Do not invent missing information or assign a quality status without evidence.\n\n## Inputs\n\nUse the available data for:\n\n- Expense transactions\n- Categories and departments\n- Suppliers, employees or cardholders, if available\n- Entities and currencies\n- Approval, payment and transaction status\n- Previous-period data, if available\n- Data quality rules or reporting requirements, if provided\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to assess expense data quality and reporting readiness.\n\nConfirm the period covered, number and type of records, dimensions available, currencies used and whether the data is complete.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, amounts, suppliers, employees, departments, categories, entities and statuses.\n\nIf fields use different structures or names, explain how they were interpreted. If a field is missing or unclear, flag the limitation.\n\n### Step 1.3, Check data quality\n\nCheck for missing values, invalid dates or amounts, duplicates, inconsistent supplier or employee names, missing departments, categories or entities, mixed currencies, unclear statuses, negative transactions and inconsistent classifications.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total records and total spend\n- Completeness by key field\n- Records with missing information\n- Duplicates or potential duplicates\n- Records with inconsistent classifications\n- Spend affected by each major issue\n- Changes compared with the previous period, if available\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify the most significant data quality issues by financial value, number of records, department, category, supplier, entity and employee or cardholder, where relevant.\n\nFor each issue, show the affected area, number and value of records, issue type, potential reporting impact and whether it appears isolated or recurring.\n\n### Step 2.3, Identify areas for review\n\nIdentify material spend affected by unreliable data, departments or categories with repeated issues, inconsistent supplier or employee information, duplicates, records that cannot be reconciled and issues requiring process or data correction.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the overall data quality position, the most significant issues by financial impact, the areas most affected, the impact on reporting or reconciliation and the most important corrective actions.\n\n### Main analysis\n\nPresent:\n\n1. Overall data quality position\n2. Missing and incomplete information\n3. Duplicate or potentially duplicated records\n4. Classification and consistency issues\n5. Issues by department, category, supplier and entity\n6. Impact on reporting or reconciliation\n7. Recommended corrective actions\n\nUse concise tables where useful:\n\n| Issue or area | Number of records | Affected spend | Potential impact | Recommended action |\n|---|---:|---:|---|---|\n\n### Exceptions and data quality issues\n\nList missing or ambiguous information, incomplete periods, mixed currencies, duplicates, unclear classification rules and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about the issues with greatest financial impact, recurring process problems, records needing correction, classifications affecting accounting analysis, mandatory fields and checks for the next reporting cycle.\n\n## Output rules\n\n- Prioritise issues based on financial impact and reporting risk.\n- Separate facts, assumptions, limitations and recommendations.\n- Never invent missing values or classifications.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- Distinguish isolated issues from recurring patterns.\n- Use clear, concise business language.\n- End with practical corrective actions.",{"_uid":142,"role":124,"title":143,"topic":120,"prompt":144,"component":98},"8c2f9b1c-3c22-4fe7-bc8d-146182e9dc93","Accounting export validation","# Accounting export validation\n\n## Purpose\n\nValidate an accounting export against the available source spend, invoice or transaction data.\n\nCreate a concise, Controller-ready review showing whether the export is complete and consistent, which totals or records do not match and what needs to be corrected before reporting or close.\n\nUse the uploaded files or pasted data provided by the user. Do not assume that different totals indicate an error without checking scope, timing, currency and data definitions.\n\n## Inputs\n\nUse the available data for:\n\n- Accounting export\n- Source spend or invoice data\n- Transaction or payment data\n- Accounting period\n- Account, category, department and entity information\n- Currency and amount information\n- Export or posting status, if available\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to validate the accounting export against its source data.\n\nConfirm the period covered by each source, the accounting scope, the level of detail, the currencies used and whether the sources are complete and comparable.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, amounts, transaction references, accounts, categories, departments, entities, suppliers and statuses.\n\nIf the sources use different structures or levels of detail, explain how they were compared. If a field is missing or unclear, flag the limitation.\n\n### Step 1.3, Check data quality\n\nCheck for missing accounting references, duplicate records, missing or invalid account assignments, different periods, mixed currencies, unmatched transactions and missing dimensions.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate or validate, where the data supports it:\n\n- Total source value\n- Total accounting export value\n- Absolute difference\n- Difference percentage, where meaningful\n- Matched and unmatched records\n- Records with account or dimension differences\n- Records outside the expected period\n\nDo not calculate a percentage when the comparison value is zero or unavailable.\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify the largest differences by account or category, department, entity, supplier, reporting period and transaction status.\n\nFor each significant difference, show the affected area, source value, export value, difference, supported explanation and potential reporting impact.\n\nOnly describe a reason as confirmed when supported by the data. Otherwise, label it as a possible explanation or question for review.\n\n### Step 2.3, Identify areas for review\n\nIdentify material total differences, unmatched records, missing accounting references, incorrect account assignments, transactions posted in the wrong period, missing dimensions and duplicate export lines.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the overall validation status, whether source and export totals match, the most significant differences, the main affected accounts or dimensions and the corrections required.\n\n### Main analysis\n\nPresent:\n\n1. Overall source versus export comparison\n2. Matched and unmatched records\n3. Total and account-level differences\n4. Period, currency or dimension issues\n5. Main supplier, department or entity differences\n6. Corrections required before reporting or close\n\nUse concise tables where useful:\n\n| Area | Source value | Export value | Difference | Status | Recommended action |\n|---|---:|---:|---:|---|---|\n\n### Exceptions and data quality issues\n\nList missing or ambiguous information, non-comparable periods, unmatched records, duplicates, mixed currencies, missing dimensions and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about differences requiring correction, comparable populations, missing references or dimensions, wrong-period postings, timing versus data corrections and checks for the next export.\n\n## Output rules\n\n- Focus on material differences and reporting impact.\n- Separate facts, assumptions, exceptions and recommendations.\n- Never assume a mismatch is an error without checking scope and timing.\n- Flag missing, ambiguous or unreliable data.\n- Do not calculate percentages when the comparison value is zero or unavailable.\n- Keep currencies separate unless a reliable conversion method is provided.\n- Use clear, concise business language.\n- End with practical corrections and validation actions.",{"_uid":146,"role":124,"title":147,"topic":139,"prompt":148,"component":98},"801eaea1-a279-4c9c-8421-67b3183d25a6","Approval exception report","# Approval exception report\n\n## Purpose\n\nIdentify transactions or invoices with approval exceptions, delays, missing approvals or approval patterns that require review.\n\nCreate a concise, Controller-ready report showing the financial value, type and potential impact of approval exceptions, without assuming that every exception represents a policy violation.\n\nUse the uploaded files or pasted data provided by the user. Do not invent policy requirements or explanations. If approval rules are not provided, clearly state the limitation.\n\n## Inputs\n\nUse the available data for:\n\n- Expense or invoice transactions\n- Approval records and timestamps\n- Amounts and currencies\n- Suppliers, employees or cardholders, if available\n- Departments and entities\n- Transaction, invoice and payment status\n- Approval thresholds or policy rules, if available\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to analyse approval exceptions and delays.\n\nConfirm the period covered, the currencies used, the approval statuses and timestamps available, whether approval rules are provided and whether the period is complete.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, amounts, suppliers, employees, departments, entities, approvers, approval steps and statuses.\n\nIf approval rules are provided, map them to the available transaction or invoice information. If a field is missing or unclear, flag the limitation.\n\n### Step 1.3, Check data quality\n\nCheck for missing approval statuses, dates or approver information, duplicates, inconsistent names, mixed currencies, incomplete periods, unclear statuses and missing policy thresholds.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total transactions or invoices reviewed\n- Total value reviewed\n- Pending, rejected and cancelled value\n- Value with missing approval information\n- Average approval time, if timestamps are available\n- Value exceeding known approval thresholds\n- Exceptions by department, approver, supplier or entity\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify the main approval exceptions by type, financial value, department, entity, supplier, approver or approval step and age or delay.\n\nFor each significant exception, show the affected area, value, status, evidence and potential financial or control impact.\n\nOnly describe an exception as a policy breach when the applicable rule is provided and supported by the data. Otherwise, label it as requiring review.\n\n### Step 2.3, Identify areas for review\n\nIdentify material transactions with missing approval information, long-pending approvals, repeated exceptions, transactions above known thresholds, approval delays affecting payment or close and rejected or cancelled transactions remaining in reporting data.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the overall approval exception position, the value and number of material exceptions, the main exception types, the areas most affected and the most important actions required.\n\n### Main analysis\n\nPresent:\n\n1. Overall approval exception position\n2. Pending, rejected and cancelled items\n3. Missing approval information\n4. Approval delays\n5. Threshold or policy exceptions, if rules are available\n6. Exceptions by department, supplier, entity or approver\n7. Recommended actions\n\nUse concise tables where useful:\n\n| Area or exception | Number of items | Value | Status | Potential impact | Recommended action |\n|---|---:|---:|---|---|---|\n\n### Exceptions and data quality issues\n\nList missing or ambiguous approval information, missing policy rules, incomplete periods, duplicates, mixed currencies, conflicting statuses and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about urgent exceptions, material pending transactions, repeated patterns, delays affecting close, policy clarification and process changes to prevent recurrence.\n\n## Output rules\n\n- Focus on material exceptions, delays and control risks.\n- Separate facts, assumptions, policy-based findings and recommendations.\n- Never invent approval rules or label an exception as a breach without evidence.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- Distinguish pending, rejected, cancelled and approved transactions.\n- Use clear, concise business language.\n- End with practical actions to resolve or prevent approval exceptions.",{"_uid":150,"role":151,"title":152,"topic":126,"prompt":153,"component":98},"5658710c-b39b-4036-8503-7e825d2ff250","ap-manager","Overdue invoice prioritisation","# Overdue invoice prioritisation\n\n## Purpose\n\nIdentify overdue invoices and prioritise the actions required to resolve them.\n\nCreate a concise, AP Manager-ready review showing the most urgent invoices, the financial value involved, the reasons for delay where supported and the next action required.\n\nUse the uploaded files or pasted data provided by the user. Do not assume that an overdue invoice should be paid immediately or that a delay has a specific cause without evidence.\n\n## Inputs\n\nUse the available data for:\n\n- Invoice records\n- Invoice and due dates\n- Amounts and currencies\n- Supplier information\n- Approval and payment status\n- Department and entity information\n- Dispute or exception information, if available\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to identify and prioritise overdue invoices.\n\nConfirm the period covered, the date used to determine overdue status, the currencies used, the available statuses and whether the data is complete.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for invoice dates, due dates, amounts, suppliers, entities, departments, approval status, payment status and disputes.\n\nIf a field is missing or unclear, flag the limitation and explain how it affects prioritisation.\n\n### Step 1.3, Check data quality\n\nCheck for missing or invalid dates, missing amounts, duplicate invoices, inconsistent supplier names, mixed currencies, unclear statuses, credit notes and incomplete periods.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Number and value of overdue invoices\n- Number and value of invoices by days overdue\n- Number and value of invoices awaiting approval\n- Number and value of overdue invoices already approved\n- Average days overdue\n- Overdue value by supplier, department and entity\n- Change compared with the previous period, if available\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify the largest and oldest overdue invoices, suppliers with repeated overdue invoices, increases in overdue value and overdue invoices affected by approval, dispute or payment issues.\n\nFor each priority invoice or group, show the invoice value, days overdue, supplier, current status, evidence and recommended next action.\n\nOnly describe a cause as confirmed when supported by the data. Otherwise, label it as a possible explanation or question for review.\n\n### Step 2.3, Identify areas for review\n\nIdentify high-value overdue invoices, invoices with long delays, overdue invoices blocked by approval or missing information, repeated supplier issues and items that may affect supplier relationships or reporting.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise total overdue value, the oldest and largest invoices, the main blockers, suppliers or areas affected and the actions required.\n\n### Main analysis\n\nPresent:\n\n1. Overall overdue invoice position\n2. Priority invoices by value and age\n3. Overdue invoices awaiting approval\n4. Overdue invoices already approved\n5. Supplier, department and entity patterns\n6. Main blockers and recommended actions\n\nUse concise tables where useful:\n\n| Invoice or supplier | Amount | Days overdue | Current status | Priority | Recommended action |\n|---|---:|---:|---|---|---|\n\nClearly state the currency and period covered.\n\n### Exceptions and data quality issues\n\nList missing or ambiguous information, invalid dates, duplicates, mixed currencies, unclear statuses, credit notes and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about urgent invoices, approval blockers, disputes, repeated supplier delays, ownership of next actions and information needed to resolve the queue.\n\n## Output rules\n\n- Write for an AP Manager or finance operations audience.\n- Prioritise by financial value, age and available status information.\n- Never invent the reason for a delay.\n- Do not recommend payment without considering approval, dispute and status information.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- End with a practical action queue.",{"_uid":155,"role":151,"title":156,"topic":126,"prompt":157,"component":98},"949bf81e-13a6-4fc5-9e03-22b2fd830c0c","Invoice ageing analysis","# Invoice ageing analysis\n\n## Purpose\n\nAnalyse the age and status of outstanding invoices to show the overall AP ageing position and the main changes over time.\n\nCreate a concise, AP Manager-ready review of current, overdue and ageing invoices by supplier, department and entity.\n\nUse the uploaded files or pasted data provided by the user. Do not assume that an old invoice is overdue unless the relevant due date or ageing method supports that conclusion.\n\n## Inputs\n\nUse the available data for:\n\n- Invoice records\n- Invoice and due dates\n- Amounts and currencies\n- Supplier information\n- Approval and payment status\n- Department and entity information\n- Previous-period ageing data, if available\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to calculate invoice ageing.\n\nConfirm the period covered, the date used for ageing, the currencies used, the statuses available and whether the data includes only outstanding invoices or all invoices.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for invoice dates, due dates, amounts, suppliers, departments, entities, approval status and payment status.\n\nIf the ageing method is not clear, state the method used and explain the limitation.\n\n### Step 1.3, Check data quality\n\nCheck for missing or invalid dates, missing amounts, duplicate invoices, inconsistent supplier names, mixed currencies, paid invoices included in outstanding balances and incomplete periods.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total outstanding invoice value\n- Number of outstanding invoices\n- Value and count by ageing bucket\n- Current and overdue value\n- Overdue value as a percentage of outstanding value\n- Average days outstanding or overdue\n- Ageing by supplier, department and entity\n- Change compared with the previous period, if available\n\nUse clear ageing buckets appropriate to the available data, such as current, 1 to 30 days, 31 to 60 days, 61 to 90 days and over 90 days.\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify changes in the ageing profile, suppliers with the oldest or largest balances, increases in overdue value and invoices moving between ageing buckets.\n\nFor each significant movement, show the affected area, amount, ageing bucket, change over time and available status information.\n\nOnly describe a reason as confirmed when supported by the data. Otherwise, label it as a possible explanation or question for review.\n\n### Step 2.3, Identify areas for review\n\nIdentify high-value or severely aged invoices, suppliers with repeated ageing issues, departments or entities with increasing overdue balances, invoices awaiting approval and balances affected by disputes or missing information.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the total outstanding balance, current and overdue value, the oldest ageing buckets, the main suppliers or areas affected and the actions required.\n\n### Main analysis\n\nPresent:\n\n1. Overall invoice ageing position\n2. Ageing bucket distribution\n3. Largest and oldest outstanding invoices\n4. Ageing by supplier\n5. Ageing by department and entity\n6. Changes compared with the previous period\n7. Recommended actions\n\nUse concise tables where useful:\n\n| Ageing bucket or area | Number of invoices | Outstanding value | Share of total | Change | Review status |\n|---|---:|---:|---:|---:|---|\n\nClearly state the currency, ageing method and period covered.\n\n### Exceptions and data quality issues\n\nList missing or ambiguous dates, duplicate invoices, paid records included in outstanding balances, mixed currencies, incomplete periods and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about the oldest balances, suppliers with repeated ageing issues, approval or dispute blockers, changes in overdue value and actions needed to improve the ageing position.\n\n## Output rules\n\n- Write for an AP Manager or finance operations audience.\n- Clearly distinguish current, overdue and severely aged invoices.\n- State the ageing method used.\n- Never infer payment risk from age alone.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- End with practical actions for the highest-priority ageing buckets.",{"_uid":159,"role":151,"title":160,"topic":126,"prompt":161,"component":98},"fab0cc6a-900b-4797-a11e-ecea033e189f","Missing invoice information","# Missing invoice information\n\n## Purpose\n\nIdentify invoices with missing, incomplete or inconsistent information that may block approval, payment, reconciliation or accounting.\n\nCreate a concise, AP Manager-ready review showing which invoices require correction, the financial value involved and the next action needed.\n\nUse the uploaded files or pasted data provided by the user. Do not assume that a field is required unless the data, process or rules provided by the user support that conclusion.\n\n## Inputs\n\nUse the available data for:\n\n- Invoice records\n- Supplier information\n- Invoice dates and amounts\n- Currency information\n- Purchase order or contract references, if available\n- Department and entity information\n- Approval, payment and accounting status\n- Required-field rules, if provided\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to assess invoice completeness.\n\nConfirm the period covered, the available invoice fields, the currencies used, the statuses available and any required-field rules provided by the user.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for invoice references, dates, amounts, suppliers, currencies, purchase orders, departments, entities and statuses.\n\nIf a field is missing or its meaning is unclear, flag the limitation rather than assuming that the information is absent.\n\n### Step 1.3, Check data quality\n\nCheck for missing or invalid values, inconsistent supplier names, duplicate invoices, mixed currencies, unclear statuses, incomplete periods and fields that are present but appear unreliable.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Number and value of invoices reviewed\n- Number and value of invoices with missing information\n- Missing information by field or issue type\n- Missing information by supplier, department and entity\n- Invoices blocked from approval, payment or accounting\n- Change compared with the previous period, if available\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify the most significant missing-information issues by financial value, number of invoices, supplier, department, entity and invoice status.\n\nFor each priority issue, show the affected invoice or group, missing information, value, current status, potential impact and recommended next action.\n\nOnly describe an item as blocked when the data or process context supports that conclusion.\n\n### Step 2.3, Identify areas for review\n\nIdentify high-value invoices with missing information, invoices close to or past due, suppliers with repeated incomplete submissions, missing references affecting accounting and issues that may delay payment or close.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the number and value of incomplete invoices, the main missing information, the areas most affected, the potential impact and the most important actions required.\n\n### Main analysis\n\nPresent:\n\n1. Overall invoice completeness position\n2. Missing information by issue type\n3. Highest-value incomplete invoices\n4. Supplier, department and entity patterns\n5. Invoices blocked or at risk of delay\n6. Recommended actions and owners, if available\n\nUse concise tables where useful:\n\n| Invoice or area | Amount | Missing information | Current status | Potential impact | Recommended action |\n|---|---:|---|---|---|---|\n\nClearly state the currency and period covered.\n\n### Exceptions and data quality issues\n\nList missing or ambiguous information, invalid values, duplicates, mixed currencies, unclear required fields and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about the most urgent incomplete invoices, supplier patterns, information needed for approval or payment, required-field rules and process changes to reduce incomplete submissions.\n\n## Output rules\n\n- Write for an AP Manager or finance operations audience.\n- Prioritise issues by financial value, due date and process impact.\n- Do not invent missing information or required fields.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- Distinguish missing information from confirmed process blockers.\n- End with a practical correction and follow-up queue.",{"_uid":163,"role":151,"title":164,"topic":126,"prompt":165,"component":98},"093b90ef-b974-4abf-b909-e4fbef807406","Approval bottleneck analysis","# Approval bottleneck analysis\n\n## Purpose\n\nIdentify delays and bottlenecks in the invoice or expense approval process.\n\nCreate a concise, AP Manager-ready review showing where approvals are accumulating, how long items have been waiting, the financial value affected and which actions may improve the flow.\n\nUse the uploaded files or pasted data provided by the user. Do not infer poor performance or policy failure without sufficient evidence.\n\n## Inputs\n\nUse the available data for:\n\n- Invoice or expense records\n- Submission and approval dates\n- Approval statuses and steps\n- Amounts and currencies\n- Suppliers, departments and entities\n- Approver information, if available\n- Approval rules or thresholds, if available\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to analyse approval time and bottlenecks.\n\nConfirm the period covered, the approval stages available, the date used to measure waiting time, the currencies used and whether the data is complete.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for submission dates, approval dates, amounts, suppliers, departments, entities, approvers, approval steps and statuses.\n\nIf a field is missing or unclear, flag the limitation and explain how it affects the analysis.\n\n### Step 1.3, Check data quality\n\nCheck for missing dates, missing approval statuses, duplicate records, inconsistent names, mixed currencies, incomplete periods, reopened requests and unclear status changes.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Number and value of invoices or expenses in approval\n- Average approval time\n- Longest approval times\n- Number and value pending by approval step\n- Number and value pending by department, entity or approver\n- Number and value overdue against available approval targets\n- Change compared with the previous period, if available\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify the approval steps, departments, entities or approvers with the largest queues or longest waiting times.\n\nFor each significant bottleneck, show the number and value of affected items, average or maximum waiting time, current status and evidence supporting the finding.\n\nOnly describe a cause as confirmed when supported by the data. Otherwise, label it as a possible explanation or question for review.\n\n### Step 2.3, Identify areas for review\n\nIdentify material pending approvals, repeated delays, approval steps with accumulating work, items close to or past due, and delays affecting payment or month-end close.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the total pending value, main bottlenecks, longest or most material delays, potential impact on payment or close and actions required.\n\n### Main analysis\n\nPresent:\n\n1. Overall approval flow position\n2. Pending items by approval step\n3. Waiting time and ageing\n4. Bottlenecks by department, entity or approver\n5. Items affecting payment or close\n6. Recommended actions\n\nUse concise tables where useful:\n\n| Approval step or area | Number of items | Value | Average wait | Oldest item | Recommended action |\n|---|---:|---:|---:|---:|---|\n\nClearly state the currency and period covered.\n\n### Exceptions and data quality issues\n\nList missing dates, unclear statuses, duplicates, mixed currencies, incomplete periods, reopened approvals and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about the largest queues, ownership of pending approvals, delays affecting payment or close, approval rules requiring clarification and process changes to reduce bottlenecks.\n\n## Output rules\n\n- Write for an AP Manager or finance operations audience.\n- Prioritise bottlenecks by financial value, waiting time and close or payment impact.\n- Never infer individual performance without sufficient evidence.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- Distinguish pending, rejected, cancelled and completed approvals.\n- End with practical actions to reduce the approval queue.",{"_uid":167,"role":151,"title":168,"topic":126,"prompt":169,"component":98},"9699fe6e-6b72-4671-a672-c17df66dad6b","Payment prioritisation","# Payment prioritisation\n\n## Purpose\n\nPrioritise approved invoices for payment based on due dates, ageing, financial value, status and available business rules.\n\nCreate a concise, AP Manager-ready payment queue showing which invoices require attention first, why they are prioritised and what blockers remain.\n\nUse the uploaded files or pasted data provided by the user. Do not make assumptions about cash availability, supplier criticality or payment policy unless the relevant information is provided.\n\n## Inputs\n\nUse the available data for:\n\n- Approved invoice records\n- Invoice and due dates\n- Amounts and currencies\n- Supplier information\n- Payment status\n- Dispute or exception information\n- Department and entity information\n- Payment terms, discounts or priority rules, if available\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to prioritise payments.\n\nConfirm the period covered, whether invoices are approved for payment, the date used for priority, the currencies used and any payment rules or constraints provided.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for invoice dates, due dates, amounts, suppliers, approval status, payment status, disputes, entities and payment terms.\n\nIf a field is missing or unclear, flag the limitation and explain how it affects prioritisation.\n\n### Step 1.3, Check data quality\n\nCheck for missing or invalid dates, missing amounts, duplicate invoices, inconsistent supplier names, mixed currencies, unpaid invoices marked as paid, disputed items and incomplete periods.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total approved invoices awaiting payment\n- Value due and overdue\n- Number and value by priority group\n- Number and value blocked by dispute, approval or missing information\n- Average days until due or days overdue\n- Available early-payment discounts\n- Payment queue by supplier, department and entity\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nPrioritise invoices using available evidence such as overdue status, due date, financial value, approval status, dispute status, payment terms, early-payment discount and available business rules.\n\nFor each priority group, show the supplier or area, amount, due or overdue position, current status, prioritisation rationale and next action.\n\nDo not present a priority as mandatory unless the data or rules support that conclusion.\n\n### Step 2.3, Identify areas for review\n\nIdentify overdue approved invoices, invoices approaching their due date, high-value invoices, invoices at risk of losing a discount, disputed or blocked invoices and suppliers with repeated payment delays.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the approved payment queue, due and overdue value, the highest-priority items, main blockers and actions required.\n\n### Main analysis\n\nPresent:\n\n1. Overall payment queue\n2. Overdue and due-soon invoices\n3. High-value payment priorities\n4. Blocked or disputed invoices\n5. Available discounts or payment terms\n6. Supplier, department and entity patterns\n7. Recommended actions\n\nUse concise tables where useful:\n\n| Invoice or supplier | Amount | Due status | Current status | Priority rationale | Recommended action |\n|---|---:|---|---|---|---|\n\nClearly state the currency and period covered.\n\n### Exceptions and data quality issues\n\nList missing or ambiguous information, invalid dates, duplicates, mixed currencies, disputed items, unclear payment rules and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about urgent payments, invoices blocked by disputes or missing information, discounts at risk, supplier patterns, applicable payment rules and ownership of next actions.\n\n## Output rules\n\n- Write for an AP Manager or finance operations audience.\n- Prioritise using available evidence, not unsupported assumptions.\n- Do not assume cash availability or supplier criticality.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- Distinguish approved, pending, disputed, blocked and paid invoices.\n- End with a practical payment queue and next actions.",{"_uid":171,"role":151,"title":172,"topic":126,"prompt":173,"component":98},"190f9e0c-05e3-4df1-a593-7a1eecef59cb","Supplier payment risk review","# Supplier payment risk review\n\n## Purpose\n\nIdentify supplier payment issues and patterns that may create operational, relationship or reporting risk.\n\nCreate a concise, AP Manager-ready review showing overdue or failed payments, repeated supplier issues, outstanding value and areas requiring investigation or follow-up.\n\nUse the uploaded files or pasted data provided by the user. Do not assume that an overdue or failed payment represents a critical supplier risk without supporting evidence.\n\n## Inputs\n\nUse the available data for:\n\n- Invoice and payment history\n- Due dates and payment dates\n- Amounts and currencies\n- Supplier information\n- Payment status and failure information\n- Disputes, credits or exceptions\n- Department and entity information\n- Supplier context provided by the user, if available\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to assess supplier payment risk.\n\nConfirm the period covered, the payment statuses available, the currencies used, the payment and due dates available and whether the data is complete.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, amounts, suppliers, invoices, payment statuses, payment failures, disputes, departments and entities.\n\nIf supplier names appear under different names, group them only when the data supports that they refer to the same supplier.\n\nIf a field is missing or unclear, flag the limitation and explain how it affects the assessment.\n\n### Step 1.3, Check data quality\n\nCheck for missing payment dates, inconsistent supplier names, duplicate invoices, mixed currencies, unclear payment statuses, refunds or reversals, incomplete periods and payments that cannot be matched to invoices.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total supplier payment value reviewed\n- Overdue and unpaid value\n- Failed or returned payment value\n- Disputed value\n- Number of affected suppliers\n- Repeated payment issues by supplier\n- Average and maximum payment delay\n- Change compared with the previous period, if available\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify suppliers with overdue, failed, returned or repeatedly delayed payments.\n\nFor each significant supplier or group, show:\n\n- Outstanding or affected value\n- Number of invoices or payments involved\n- Age or delay\n- Current status\n- Evidence of repeated or isolated issues\n- Potential operational or reporting implication\n\nOnly describe a supplier relationship or operational risk as confirmed when supported by the data or context provided by the user.\n\n### Step 2.3, Identify areas for review\n\nIdentify high-value overdue payments, repeated payment failures, suppliers with increasing outstanding balances, disputed invoices, unmatched payments and issues that may affect supplier relationships or month-end reporting.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the overall supplier payment position, the most significant overdue or failed payments, the suppliers most affected, potential risks and the actions required.\n\n### Main analysis\n\nPresent:\n\n1. Overall supplier payment position\n2. Overdue and unpaid payments\n3. Failed or returned payments\n4. Disputed or unmatched items\n5. Suppliers with repeated issues\n6. Department and entity patterns\n7. Recommended actions\n\nUse concise tables where useful:\n\n| Supplier or area | Affected value | Issue type | Age or delay | Risk assessment | Recommended action |\n|---|---:|---|---:|---|---|\n\nClearly state the currency and period covered.\n\n### Exceptions and data quality issues\n\nList missing or ambiguous information, inconsistent supplier names, duplicates, mixed currencies, unmatched payments, incomplete periods and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about urgent supplier payments, repeated failures, disputed invoices, outstanding balances, potential relationship impact, ownership of actions and information needed to confirm the risk assessment.\n\n## Output rules\n\n- Write for an AP Manager or finance operations audience.\n- Focus on material payment issues and repeated patterns.\n- Separate facts, assumptions, potential risks and recommendations.\n- Never invent supplier criticality, contract terms or relationship impact.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- Distinguish overdue, failed, returned, disputed and unmatched payments.\n- End with practical follow-up actions.",{"_uid":175,"role":176,"title":177,"topic":96,"prompt":178,"component":98},"a80b9dab-60ac-40f1-bf95-f4ef36de0299","finance-analyst-fpa","Spend trend analysis","# Spend trend analysis\n\n## Purpose\n\nAnalyse how company spend changes over time and identify the main trends, movements and areas requiring attention.\n\nCreate a concise, Finance Analyst-ready review showing changes in spend by period, department, category, supplier and entity where available.\n\nUse the uploaded files or pasted data provided by the user. Do not invent explanations. If information is missing, unclear or inconsistent, state the limitation before presenting the analysis.\n\n## Inputs\n\nUse the available data for:\n\n- Spend transactions or aggregated spend\n- Current and previous reporting periods\n- Department, category, supplier and entity information\n- Budget or forecast data, if available\n- Transaction status and business context, if available\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to analyse spend over time.\n\nConfirm the periods covered, whether the data is transactional or aggregated, the currencies used and whether the periods are comparable and complete.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, amounts, departments, categories, suppliers, entities and statuses.\n\nIf a field is missing or unclear, flag the limitation and explain how it affects the analysis.\n\n### Step 1.3, Check data quality\n\nCheck for missing dates or amounts, duplicates, inconsistent names or categories, mixed currencies, incomplete periods, refunds and reversals.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total spend by period\n- Number of transactions\n- Average transaction value\n- Absolute and percentage change\n- Spend by department, category, supplier and entity\n- Recurring and one-off spend\n- Budget or forecast variance, if available\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify the largest increases and decreases, emerging trends, seasonality, unusual peaks or drops and areas with sustained change.\n\nFor each significant movement, show the affected area, period values, change, contributing transactions or suppliers and whether the pattern appears recurring or one-off.\n\nOnly describe a reason as confirmed when supported by the data. Otherwise, label it as a possible explanation or question for review.\n\n### Step 2.3, Identify areas for review\n\nIdentify material trends, repeated increases, declining spend that may require explanation, unusual movements and areas affected by incomplete data.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the overall trend, the largest movements, the main drivers supported by the data and the most important actions or questions.\n\n### Main analysis\n\nPresent:\n\n1. Overall spend trend\n2. Trend by department and category\n3. Trend by supplier and entity\n4. Recurring and one-off movements\n5. Largest increases and decreases\n6. Budget or forecast comparison, if available\n7. Areas requiring review\n\nUse concise tables or charts only where they improve readability.\n\n### Exceptions and data quality issues\n\nList missing or ambiguous information, incomplete periods, duplicates, mixed currencies, refunds or reversals and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about the largest changes, recurring patterns, seasonality, unexpected decreases or increases and data required for further analysis.\n\n## Output rules\n\n- Write for a Finance Analyst or FP&A audience.\n- Focus on material trends and actionable movements.\n- Separate facts, assumptions, interpretations and recommendations.\n- Never invent explanations for trends.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- End with practical follow-up actions.",{"_uid":180,"role":176,"title":181,"topic":102,"prompt":182,"component":98},"39c3a90e-d3a6-4fae-a6c6-13f8c9e32664","Department budget variance","# Department budget variance\n\n## Purpose\n\nCompare actual spend with budget by department and identify the main variances, drivers and areas requiring follow-up.\n\nCreate a concise, Finance Analyst-ready analysis that helps Finance and department owners understand where spending is above or below plan.\n\nUse the uploaded files or pasted data provided by the user. Do not invent explanations. If information is missing, unclear or inconsistent, state the limitation before presenting the analysis.\n\n## Inputs\n\nUse the available data for:\n\n- Department-level actual spend\n- Department-level budget\n- Previous-period or year-to-date data, if available\n- Spend category, supplier and entity breakdowns\n- Committed or pending spend, if available\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to compare department actuals with budget.\n\nConfirm the periods covered, the department structure, whether actuals and budget are comparable, the currencies used and whether the data is complete.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, actual amounts, budget amounts, departments, categories, suppliers, entities and statuses.\n\nIf actuals and budget use different structures, explain how they were compared. Flag missing or unclear fields.\n\n### Step 1.3, Check data quality\n\nCheck for missing departments, duplicate records, departments without a budget, budget lines without actuals, mixed currencies, partial periods, zero budgets and inconsistent names.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Actual spend by department\n- Budget by department\n- Absolute and percentage variance\n- Budget utilisation\n- Department share of total spend\n- Committed or pending spend\n- Change compared with the previous period or forecast, if available\n\nFor expense data, treat spending above budget as unfavourable unless the context indicates otherwise. Do not calculate percentages when budget is zero or unavailable.\n\n### Step 2.2, Identify the main movements\n\nIdentify departments with the largest favourable and unfavourable variances.\n\nBreak down significant variances by category, supplier, entity, transaction volume and average transaction value where available.\n\nOnly describe a driver as confirmed when supported by the data. Otherwise, label it as a possible explanation or question for review.\n\n### Step 2.3, Identify areas for review\n\nIdentify material overspend, material underspend that may reflect delayed spending or incomplete data, recurring variance, unbudgeted spend and departments affected by data quality issues.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise overall department spend versus budget, the largest variances, the main supported drivers and the actions required from Finance or department owners.\n\n### Main analysis\n\nPresent:\n\n1. Overall department budget position\n2. Largest unfavourable variances\n3. Largest favourable variances\n4. Variance by category and supplier\n5. Committed or pending spend, if available\n6. Recurring or unexplained variances\n7. Recommended actions\n\nUse a concise table:\n\n| Department | Actual spend | Budget | Variance | Variance % | Status | Recommended action |\n|---|---:|---:|---:|---:|---|---|\n\n### Exceptions and data quality issues\n\nList missing budgets, non-comparable periods, zero budgets, unmatched departments, duplicates, mixed currencies and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about expected variances, reforecasting, delayed spending, unbudgeted purchases, recurring overspend and information needed from department owners.\n\n## Output rules\n\n- Write for a Finance Analyst or FP&A audience.\n- Prioritise variances by financial impact and recurrence.\n- Separate facts, assumptions, interpretations and recommendations.\n- Never invent the reason for a departmental variance.\n- Do not treat underspend as automatically positive.\n- Flag missing, ambiguous or unreliable data.\n- End with practical follow-up actions.",{"_uid":184,"role":176,"title":185,"topic":96,"prompt":186,"component":98},"d7c2a06e-1770-4315-ba59-da7edcdc0e64","Cost driver analysis","# Cost driver analysis\n\n## Purpose\n\nIdentify the factors driving changes in company spend and explain how volume, price, mix, timing or other available dimensions contribute to the movement.\n\nCreate a concise, Finance Analyst-ready analysis that separates evidence from assumptions and highlights the drivers that require attention.\n\nUse the uploaded files or pasted data provided by the user. Do not invent causes when the data does not support them.\n\n## Inputs\n\nUse the available data for:\n\n- Current and previous-period spend\n- Budget or forecast data, if available\n- Transaction volume and amounts\n- Supplier, category, department and entity information\n- Business drivers provided by the user, if available\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to analyse changes in spend and their potential drivers.\n\nConfirm the periods covered, the currencies used, the dimensions available, whether the data is transactional and whether the periods are comparable.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, amounts, transaction counts, suppliers, categories, departments, entities and statuses.\n\nIf a potential driver is not directly measured, state that limitation rather than estimating it without evidence.\n\n### Step 1.3, Check data quality\n\nCheck for missing values, duplicates, inconsistent classifications, mixed currencies, incomplete periods, refunds and reversals.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total spend change\n- Change in transaction volume\n- Change in average transaction value\n- Spend by supplier, category, department and entity\n- Budget or forecast variance, if available\n- Contribution of the largest areas to the overall change\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nAssess whether significant movements appear related to:\n\n- Volume\n- Price or average transaction value\n- Supplier or category mix\n- Timing\n- One-off transactions\n- Recurring spend\n- Classification or data quality issues\n\nFor each driver, show the supporting evidence, affected area, financial impact and confidence level.\n\nClassify explanations as confirmed driver, likely driver, possible explanation or unknown.\n\n### Step 2.3, Identify areas for review\n\nIdentify material cost drivers, changes concentrated in a small number of suppliers or categories, recurring increases, one-off items and movements that cannot be explained reliably.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the overall spend change, the most important cost drivers, confidence in the explanations and the main actions required.\n\n### Main analysis\n\nPresent:\n\n1. Overall spend movement\n2. Volume and average value changes\n3. Supplier and category drivers\n4. Department and entity drivers\n5. One-off versus recurring movements\n6. Budget or forecast implications\n7. Areas requiring review\n\nUse concise tables where useful:\n\n| Driver or area | Spend impact | Evidence | Confidence | Recommended action |\n|---|---:|---|---|---|\n\n### Exceptions and data quality issues\n\nList missing driver data, inconsistent classifications, incomplete periods, mixed currencies, duplicates and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about volume, price, supplier mix, one-off purchases, recurring changes and additional information needed to confirm the drivers.\n\n## Output rules\n\n- Write for a Finance Analyst or FP&A audience.\n- Separate confirmed drivers from hypotheses.\n- Never invent a cost driver.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- Use clear, concise business language.\n- End with practical actions or questions for validation.",{"_uid":188,"role":176,"title":189,"topic":102,"prompt":190,"component":98},"49459d3a-84cc-4f9a-b2f5-f884d7b8f110","Forecast assumptions review","# Forecast assumptions review\n\n## Purpose\n\nReview the assumptions behind a spend forecast and assess whether they are supported by historical data, current trends and available business context.\n\nCreate a concise, Finance Analyst-ready review showing which assumptions appear reasonable, which require validation and how they may affect the forecast.\n\nUse the uploaded files or pasted data provided by the user. Do not create unsupported forecasts or assumptions.\n\n## Inputs\n\nUse the available data for:\n\n- Forecast and forecast assumptions\n- Historical and current-period spend\n- Budget data\n- Recurring and one-off spend\n- Supplier, category, department and entity information\n- Business context or planned changes provided by the user\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to assess the forecast assumptions.\n\nConfirm the forecast period, historical periods, currencies used, forecast scope, level of detail and whether the periods are comparable.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, actual spend, forecast amounts, budget, suppliers, categories, departments, entities and relevant drivers.\n\nIf an assumption cannot be linked to available evidence, flag it as unsupported or requiring validation.\n\n### Step 1.3, Check data quality\n\nCheck for missing periods, incomplete actuals, duplicates, inconsistent classifications, mixed currencies, one-off transactions treated as recurring and forecast lines without a clear basis.\n\nDo not silently exclude problematic records. State how important issues affect the review.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate or validate, where the data supports it:\n\n- Historical average and recent spend\n- Forecast versus historical spend\n- Forecast versus budget\n- Recurring and one-off spend\n- Spend growth or decline assumptions\n- Variance by department, category, supplier and entity\n- Sensitivity to material assumptions, where possible\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify assumptions related to volume, price, supplier changes, recurring commitments, seasonality, timing and planned business changes.\n\nFor each material assumption, show the supporting evidence, forecast impact, confidence level and information needed to validate it.\n\nClassify assumptions as supported, partially supported, unsupported or requiring confirmation.\n\n### Step 2.3, Identify areas for review\n\nIdentify assumptions with a material financial impact, assumptions based on short or incomplete history, one-off costs treated as recurring, missing supplier or business context and areas where a sensitivity analysis would be useful.\n\nFor each priority assumption, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the overall forecast reliability, the most material assumptions, the largest risks and the actions required before the forecast is finalised.\n\n### Main analysis\n\nPresent:\n\n1. Forecast versus historical spend\n2. Forecast versus budget\n3. Main assumptions and evidence\n4. Supported and unsupported assumptions\n5. Material sensitivities\n6. Areas requiring validation\n7. Recommended actions\n\nUse concise tables where useful:\n\n| Assumption | Forecast impact | Supporting evidence | Confidence | Recommended action |\n|---|---:|---|---|---|\n\n### Exceptions and data quality issues\n\nList missing historical data, incomplete periods, unsupported assumptions, mixed currencies, one-off items and assumptions made. Explain their impact.\n\n### Questions for review\n\nEnd with questions about assumptions requiring owner confirmation, expected supplier or volume changes, recurring costs, sensitivity ranges and information needed to finalise the forecast.\n\n## Output rules\n\n- Write for a Finance Analyst or FP&A audience.\n- Do not invent or silently modify forecast assumptions.\n- Separate historical facts, assumptions, sensitivities and recommendations.\n- Clearly label confidence levels.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- End with specific validation actions.",{"_uid":192,"role":176,"title":193,"topic":120,"prompt":194,"component":98},"b40e277f-c8f1-4dac-9573-fa63b0375eff","Recurring reporting workflow","# Recurring reporting workflow\n\n## Purpose\n\nCreate a repeatable workflow for producing a recurring spend or finance report from the available data.\n\nDefine the inputs, validation checks, calculations, output structure and review steps needed to produce a consistent report on a daily, weekly or monthly basis.\n\nUse the uploaded files or pasted data provided by the user. Do not assume that a workflow can be automated or repeated until the required inputs and timing are clear.\n\n## Inputs\n\nUse the available data for:\n\n- Current and previous reporting periods\n- Spend, budget, variance or supplier data\n- Department, category and entity breakdowns\n- Existing reports or reporting requirements\n- Reporting frequency and audience, if provided\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the sources, fields and metrics required for the recurring report.\n\nConfirm the reporting frequency, period definitions, source files, data owner information, currencies and expected output audience.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, amounts, budgets, variances, suppliers, departments, categories, entities and statuses.\n\nIf a required input is missing or unclear, flag it and explain how the workflow should handle it.\n\n### Step 1.3, Check data quality\n\nDefine checks for missing values, duplicates, inconsistent names, mixed currencies, incomplete periods, unexpected totals and changes in source structure.\n\nDo not silently exclude problematic records. Include a step to report important data quality issues each time the workflow runs.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nDefine the recurring calculations required, such as:\n\n- Total spend\n- Budget and variance\n- Change compared with the previous period\n- Spend by department, category, supplier and entity\n- Recurring or unusual spend\n- Key exceptions and data quality indicators\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nDefine how the workflow should identify material increases, decreases, new suppliers, recurring changes, budget variances and unusual transactions.\n\nSet clear prioritisation criteria based on financial impact, percentage change, recurrence and reporting relevance.\n\n### Step 2.3, Identify areas for review\n\nDefine how to flag missing data, unexplained movements, threshold breaches, recurring exceptions and items requiring owner review.\n\nFor each flagged area, require evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nCreate a repeatable executive summary covering the overall position, main movements, risks, data quality issues and actions required.\n\n### Main analysis\n\nStructure the recurring report as follows:\n\n1. Overall financial position\n2. Comparison with the previous period\n3. Budget and variance analysis, if available\n4. Spend by key dimensions\n5. Recurring or unusual movements\n6. Exceptions and data quality\n7. Actions and owners\n\nUse consistent tables and definitions from one reporting period to the next.\n\n### Exceptions and data quality issues\n\nInclude a standard section for missing data, source changes, incomplete periods, duplicates, mixed currencies and assumptions.\n\n### Questions for review\n\nEnd with a recurring checklist of questions for Finance, data owners and business stakeholders.\n\n## Output rules\n\n- Write for a Finance Analyst or FP&A audience.\n- Make the workflow repeatable and clear.\n- Separate input validation, calculations, interpretation and recommendations.\n- Do not invent data or assume automation is available.\n- Flag changes in source structure or data quality.\n- Keep currencies separate unless a reliable conversion method is provided.\n- End with a practical reporting checklist.",{"_uid":196,"role":176,"title":197,"topic":96,"prompt":198,"component":98},"6aed4d2e-9a08-40e0-af21-68ccd95cc07b","Multi-entity spend comparison","# Multi-entity spend comparison\n\n## Purpose\n\nCompare spend across entities and identify meaningful differences in spend levels, categories, suppliers, departments and trends.\n\nCreate a concise, Finance Analyst-ready comparison that highlights material differences while accounting for scope, period, currency and entity size limitations.\n\nUse the uploaded files or pasted data provided by the user. Do not compare entities as if they were directly equivalent when the available data does not support that conclusion.\n\n## Inputs\n\nUse the available data for:\n\n- Spend by entity\n- Current and previous reporting periods\n- Department, category and supplier information\n- Budget or forecast data, if available\n- Entity size or context provided by the user, if available\n- Currency information\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to compare entities.\n\nConfirm the periods covered, entity scope, currencies used, reporting level, data completeness and whether entities can be compared directly.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, amounts, entities, departments, categories, suppliers, transaction counts and statuses.\n\nIf entities use different structures, scopes or currencies, explain how they were compared and flag any limitation.\n\n### Step 1.3, Check data quality\n\nCheck for missing entities, duplicate records, inconsistent entity names, mixed currencies, different reporting periods, missing categories and incomplete data for particular entities.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total spend by entity\n- Number of transactions by entity\n- Average transaction value\n- Spend by category, department and supplier\n- Absolute and percentage change by entity\n- Budget or forecast variance, if available\n- Spend concentration and recurring spend by entity\n\nAnalyse currencies separately unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify the largest differences between entities, changes over time, categories or suppliers concentrated in one entity and unusual entity-level movements.\n\nWhere entity size or other normalising data is available, use relevant ratios. Do not create normalised comparisons without the required denominator.\n\nOnly describe a reason as confirmed when supported by the data. Otherwise, label it as a possible explanation or question for review.\n\n### Step 2.3, Identify areas for review\n\nIdentify material entity differences, inconsistent classifications, unusual supplier or category concentration, recurring spend differences and entities affected by incomplete or non-comparable data.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the overall entity comparison, the largest differences, the main supported drivers, the key limitations and the actions required.\n\n### Main analysis\n\nPresent:\n\n1. Overall spend by entity\n2. Change compared with the previous period\n3. Spend by category and department\n4. Spend by supplier\n5. Budget or forecast comparison, if available\n6. Recurring and unusual entity-level spend\n7. Areas requiring review\n\nUse concise tables where useful:\n\n| Entity | Spend | Transactions | Change | Budget status | Key finding |\n|---|---:|---:|---:|---|---|\n\nClearly state the currency, period and comparison method.\n\n### Exceptions and data quality issues\n\nList missing entity information, non-comparable periods, mixed currencies, duplicates, incomplete entities and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about material differences, entity scope, currency effects, supplier or category concentration, budget changes and additional context needed for interpretation.\n\n## Output rules\n\n- Write for a Finance Analyst or FP&A audience.\n- Distinguish absolute differences from meaningful comparable differences.\n- Never invent reasons for entity-level movements.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- End with practical follow-up actions.",{"_uid":200,"role":201,"title":202,"topic":111,"prompt":203,"component":98},"e58c425e-e116-4499-80f7-dc811a573bf0","procurement-manager","SaaS subscription inventory","# SaaS subscription inventory\n\n## Purpose\n\nIdentify and organise SaaS-related recurring spend to improve visibility of subscriptions, suppliers, payment patterns and review opportunities.\n\nCreate a concise, Procurement-ready inventory using available spend and invoice data. Do not assume that a supplier or transaction is SaaS without supporting evidence.\n\n## Inputs\n\nUse the available data for:\n\n- Spend and invoice history\n- Supplier and description information\n- Payment frequency and dates\n- Amounts and currencies\n- Department, entity and category information\n- Contract, renewal or owner information, if available\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to identify subscription-like spend.\n\nConfirm the period covered, the evidence used to classify SaaS spend, currencies, payment frequency and whether the data is complete.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for suppliers, descriptions, dates, amounts, frequency, departments, entities, categories and statuses.\n\nClassify a record as confirmed, likely or unclear SaaS-related spend based on the available evidence.\n\n### Step 1.3, Check data quality\n\nCheck for inconsistent supplier names, duplicates, mixed currencies, missing payment frequency, incomplete periods, one-off transactions and subscriptions split across different records.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total identified SaaS-related spend\n- Number of suppliers or subscriptions\n- Recurring monthly or periodic cost\n- Spend by supplier, department and entity\n- Change compared with the previous period\n- Subscriptions with unclear ownership or status\n- Potential duplicate or overlapping spend\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify new, stopped, increasing or decreasing subscription-like costs, suppliers with multiple charges and spend with unclear frequency or ownership.\n\nFor each item, show the evidence supporting the classification, amount, frequency, status and information still required.\n\n### Step 2.3, Identify areas for review\n\nIdentify high-value subscriptions, material increases, duplicate or overlapping costs, unclear owners, missing renewal information and items requiring supplier or contract review.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise identified SaaS-related spend, the largest suppliers or costs, the main changes, data limitations and review opportunities.\n\n### Main analysis\n\nPresent:\n\n1. Overall SaaS-related spend\n2. Inventory by supplier\n3. Recurring cost and frequency\n4. Spend by department and entity\n5. New, stopped or changing subscriptions\n6. Potential duplicates or overlaps\n7. Recommended actions\n\nUse a concise table:\n\n| Supplier or subscription | Spend | Frequency | Owner or entity | Classification | Review action |\n|---|---:|---|---|---|---|\n\n### Exceptions and data quality issues\n\nList unclear classifications, inconsistent supplier names, missing frequency or owner data, duplicates, mixed currencies and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about ownership, renewal dates, overlapping tools, inactive subscriptions, supplier review and information needed to confirm the inventory.\n\n## Output rules\n\n- Write for a Procurement Manager or finance operations audience.\n- Do not classify SaaS spend without supporting evidence.\n- Separate confirmed, likely and unclear classifications.\n- Never invent usage, contract, renewal or owner information.\n- Flag missing, ambiguous or unreliable data.\n- End with practical inventory and review actions.",{"_uid":205,"role":201,"title":206,"topic":111,"prompt":207,"component":98},"3431d75c-7c98-4114-aaa9-dd7547fb6664","Supplier comparison","# Supplier comparison\n\n## Purpose\n\nCompare suppliers using available spend, transaction, category and performance information to support procurement review and decision-making.\n\nCreate a concise, Procurement-ready comparison that distinguishes measurable differences from information that is not available.\n\nUse the uploaded files or pasted data provided by the user. Do not recommend a supplier based on unsupported assumptions or incomplete comparisons.\n\n## Inputs\n\nUse the available data for:\n\n- Supplier spend and transaction history\n- Categories or services provided\n- Prices, quantities or average transaction values, if available\n- Payment terms or contract information, if available\n- Departments and entities using each supplier\n- Supplier performance information, if available\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to compare suppliers fairly.\n\nConfirm the period covered, supplier scope, currencies, category or service scope, level of detail and whether the suppliers are comparable.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for suppliers, dates, amounts, quantities, categories, departments, entities, terms and performance measures.\n\nIf suppliers provide different scopes or services, explain the limitation and avoid direct ranking where it is not appropriate.\n\n### Step 1.3, Check data quality\n\nCheck for inconsistent supplier names, duplicates, mixed currencies, different periods, missing quantities, missing terms and incomplete performance data.\n\nDo not silently exclude problematic records. State how important issues affect the comparison.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total spend by supplier\n- Number of transactions\n- Average transaction value\n- Price or unit cost comparison, if quantities are available\n- Spend by category, department and entity\n- Change over time\n- Payment terms or performance measures, if available\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify measurable differences in price, volume, spend, terms, supplier concentration or performance.\n\nFor each significant difference, show the evidence, affected category or service, financial impact and confidence level.\n\nSeparate confirmed findings from possible explanations or areas requiring more information.\n\n### Step 2.3, Identify areas for review\n\nIdentify suppliers with material cost differences, increasing spend, limited data, inconsistent service scope or performance concerns supported by the available information.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the main measurable differences, the strongest evidence, the most important limitations and the procurement questions or actions required.\n\n### Main analysis\n\nPresent:\n\n1. Scope and comparability\n2. Spend and volume comparison\n3. Price or unit cost comparison, if available\n4. Terms and performance comparison, if available\n5. Category, department and entity differences\n6. Areas requiring further review\n7. Recommended actions\n\nUse a concise table:\n\n| Supplier | Spend | Volume | Average value | Key difference | Evidence level |\n|---|---:|---:|---:|---|---|\n\n### Exceptions and data quality issues\n\nList non-comparable scopes, missing quantities, terms or performance data, inconsistent names, mixed currencies and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about scope comparability, price or volume differences, missing supplier information, terms, performance evidence and additional data needed for a decision.\n\n## Output rules\n\n- Write for a Procurement Manager or finance operations audience.\n- Compare suppliers only where the available data supports a fair comparison.\n- Never invent prices, benchmarks, terms or performance results.\n- Separate facts, assumptions and recommendations.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- End with practical procurement follow-up actions.",{"_uid":209,"role":201,"title":210,"topic":111,"prompt":211,"component":98},"b4cc1800-1377-482d-bdb0-e3c5f44fa6db","Supplier negotiation preparation","# Supplier negotiation preparation\n\n## Purpose\n\nPrepare a fact-based negotiation brief using available spend, supplier, pricing, volume, payment and contract information.\n\nCreate a concise, Procurement-ready preparation document showing the evidence, negotiation priorities, questions and information gaps.\n\nUse the uploaded files or pasted data provided by the user. Do not invent market benchmarks, supplier alternatives, contract terms or negotiation outcomes.\n\n## Inputs\n\nUse the available data for:\n\n- Supplier spend and transaction history\n- Categories or services provided\n- Prices, quantities and changes over time, if available\n- Contract, renewal and payment terms, if available\n- Supplier concentration and recurring spend\n- Business requirements or negotiation objectives provided by the user\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to prepare the negotiation brief.\n\nConfirm the period covered, supplier scope, currencies, category or service scope and any objectives or constraints provided.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for suppliers, dates, amounts, quantities, categories, departments, entities, pricing, terms, renewals and statuses.\n\nIf a negotiation point cannot be supported by the data, label it as an information gap rather than presenting it as fact.\n\n### Step 1.3, Check data quality\n\nCheck for inconsistent supplier names, duplicates, mixed currencies, incomplete periods, missing contract terms, unclear quantities and one-off transactions that may distort the analysis.\n\nDo not silently exclude problematic records. State how important issues affect the brief.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total and recurring spend\n- Spend change over time\n- Transaction volume and average value\n- Price or unit cost changes, if available\n- Supplier share of spend\n- Payment terms and renewal timing, if available\n- Spend by category, department and entity\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify material price increases, volume changes, recurring spend, supplier concentration, unused or changing services and available evidence of negotiation leverage.\n\nFor each negotiation point, show the evidence, financial impact, confidence level and information still required.\n\n### Step 2.3, Identify areas for review\n\nIdentify the strongest negotiation priorities, data gaps, renewal or timing considerations, potential consolidation opportunities and issues requiring internal alignment before the negotiation.\n\nFor each priority, provide the evidence, potential implication and recommended preparation action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the supplier relationship, spend position, strongest evidence, negotiation priorities, information gaps and recommended preparation steps.\n\n### Main analysis\n\nPresent:\n\n1. Supplier spend and relationship overview\n2. Historical changes in spend, volume or price\n3. Recurring and concentrated spend\n4. Contract, renewal or payment information, if available\n5. Negotiation priorities and supporting evidence\n6. Questions and information gaps\n7. Recommended preparation actions\n\nUse a concise table:\n\n| Negotiation point | Evidence | Financial impact | Confidence | Preparation action |\n|---|---|---:|---|---|\n\n### Exceptions and data quality issues\n\nList missing terms, quantities, benchmarks, renewal dates, inconsistent records, mixed currencies and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about objectives, acceptable outcomes, supplier alternatives, contract terms, internal stakeholders, benchmarks and information required before the negotiation.\n\n## Output rules\n\n- Write for a Procurement Manager or finance operations audience.\n- Keep the preparation evidence-based.\n- Never invent market benchmarks, alternatives or contract terms.\n- Separate facts, assumptions, negotiation hypotheses and recommendations.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- End with practical preparation actions and questions.",{"_uid":213,"role":201,"title":214,"topic":111,"prompt":215,"component":98},"186f70f1-742d-4df1-aed6-cdcc33942fd9","Open purchase order review","# Open purchase order review\n\n## Purpose\n\nReview open purchase orders and identify remaining commitments, aged orders, unmatched invoices and purchase orders that may require closure or follow-up.\n\nCreate a concise, Procurement-ready review showing the financial value, status, age and next action for open purchase orders.\n\nUse the uploaded files or pasted data provided by the user. Do not assume that an open purchase order is unused, invalid or a financial liability without supporting evidence.\n\n## Inputs\n\nUse the available data for:\n\n- Purchase order records\n- Order dates and expected delivery dates\n- Original and remaining values\n- Supplier information\n- Invoice and payment matching\n- Department and entity information\n- Purchase order and delivery status\n- Contract or project context, if available\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to assess open purchase orders.\n\nConfirm the period covered, the definition of open status, the values available, currencies used and whether invoices or receipts can be matched.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for purchase order references, dates, suppliers, original values, invoiced values, remaining values, departments, entities and statuses.\n\nIf a field is missing or unclear, flag the limitation and explain how it affects the review.\n\n### Step 1.3, Check data quality\n\nCheck for duplicate purchase orders, missing references, inconsistent supplier names, negative or closed values, mixed currencies, incomplete periods and purchase orders with unclear status.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Number and total value of open purchase orders\n- Invoiced and remaining value\n- Open value by age bucket\n- Open orders by supplier, department and entity\n- Orders with no invoices or activity\n- Orders exceeding expected dates\n- Change compared with the previous period, if available\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify aged purchase orders, large remaining commitments, orders with partial invoicing, orders without activity, orders with unmatched invoices and changes in open value over time.\n\nFor each priority order or group, show the value, age, status, supplier, matching evidence and recommended next action.\n\n### Step 2.3, Identify areas for review\n\nIdentify purchase orders that may require closure, amendment, receipt confirmation, invoice matching, supplier follow-up or internal owner confirmation.\n\nDo not classify an order as stale or unnecessary without evidence. For each priority area, provide the evidence, potential implication and recommended action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the overall open purchase order position, remaining value, aged or inactive orders, main suppliers or departments affected and actions required.\n\n### Main analysis\n\nPresent:\n\n1. Overall open purchase order position\n2. Open value by age\n3. Largest remaining commitments\n4. Orders with partial or no invoicing\n5. Supplier, department and entity patterns\n6. Orders requiring closure or follow-up\n7. Recommended actions\n\nUse a concise table:\n\n| Purchase order or area | Remaining value | Age | Current status | Evidence | Recommended action |\n|---|---:|---:|---|---|---|\n\n### Exceptions and data quality issues\n\nList missing references, duplicates, inconsistent supplier names, mixed currencies, unmatched invoices, incomplete periods and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about order owners, expected delivery, remaining commitments, invoice matching, closure criteria, supplier follow-up and purchase orders affecting reporting or budgets.\n\n## Output rules\n\n- Write for a Procurement Manager or finance operations audience.\n- Distinguish open, partially invoiced, inactive and overdue orders.\n- Never assume an open order is unused or invalid without evidence.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- End with a practical purchase order follow-up list.",{"_uid":217,"role":201,"title":218,"topic":111,"prompt":219,"component":98},"035a2d69-a2ee-4344-8f32-e1d8991f9478","Supplier concentration analysis","# Supplier concentration analysis\n\n## Purpose\n\nAnalyse how spend is distributed across suppliers and categories to identify procurement dependencies, concentration patterns and opportunities for further review.\n\nCreate a concise, Procurement-ready analysis that focuses on category-level supplier coverage, dependency and available evidence of alternatives or consolidation opportunities.\n\nUse the uploaded files or pasted data provided by the user. Do not assume that concentration is a risk or that alternative suppliers exist without supporting information.\n\n## Inputs\n\nUse the available data for:\n\n- Supplier spend and transaction history\n- Categories or services provided\n- Department and entity information\n- Current and previous-period spend\n- Supplier status or alternative supplier information, if available\n- Contract or renewal information, if available\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to analyse supplier concentration by category and business area.\n\nConfirm the period covered, supplier scope, categories available, currencies used and whether supplier names are consistently recorded.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for dates, amounts, suppliers, categories, departments, entities, contracts and statuses.\n\nGroup supplier records only when the data supports that they refer to the same supplier. Flag uncertain relationships.\n\n### Step 1.3, Check data quality\n\nCheck for inconsistent supplier names, duplicates, missing categories, mixed currencies, incomplete periods, spend without suppliers and categories with unclear scope.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Total spend by category\n- Number of suppliers by category\n- Top supplier share by category\n- Top 5 and top 10 supplier concentration\n- Supplier concentration by department and entity\n- Change compared with the previous period\n- Recurring or critical spend concentration, if supported by the data\n\nKeep different currencies separate unless a reliable conversion method is provided.\n\n### Step 2.2, Identify the main movements\n\nIdentify categories dependent on one or a small number of suppliers, changes in concentration over time, suppliers gaining or losing share and categories with many fragmented suppliers.\n\nFor each significant pattern, show the spend, supplier share, category, change over time and evidence supporting the assessment.\n\nOnly describe a dependency or procurement risk as confirmed when supported by the data or context provided by the user.\n\n### Step 2.3, Identify areas for review\n\nIdentify categories requiring supplier diversification review, potential consolidation opportunities, high dependency without alternative information and supplier changes requiring further investigation.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise supplier concentration by category, the most dependent areas, key changes, information gaps and recommended procurement actions.\n\n### Main analysis\n\nPresent:\n\n1. Overall supplier concentration\n2. Concentration by category\n3. Concentration by department and entity\n4. Changes over time\n5. Fragmented or highly dependent categories\n6. Available alternative or consolidation information\n7. Recommended actions\n\nUse a concise table:\n\n| Category or area | Total spend | Number of suppliers | Top supplier share | Concentration level | Review action |\n|---|---:|---:|---:|---|---|\n\n### Exceptions and data quality issues\n\nList inconsistent supplier names, missing categories, mixed currencies, incomplete periods, uncertain supplier grouping and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about intentional dependencies, alternative suppliers, category consolidation, renewal timing, supplier diversification and information needed before making a procurement decision.\n\n## Output rules\n\n- Write for a Procurement Manager or finance operations audience.\n- Focus on category and supplier dependency.\n- Do not treat concentration as risk without supporting evidence.\n- Never invent alternative suppliers or market information.\n- Flag missing, ambiguous or unreliable data.\n- Keep currencies separate unless a reliable conversion method is provided.\n- End with practical procurement review actions.",{"_uid":221,"role":201,"title":222,"topic":111,"prompt":223,"component":98},"5248c9f1-5b97-4684-a3dd-8e12b342e94b","Supplier onboarding data quality","# Supplier onboarding data quality\n\n## Purpose\n\nAssess the completeness, consistency and reliability of supplier onboarding data for procurement operations, reporting and supplier management.\n\nCreate a concise, Procurement-ready review showing missing information, duplicate or inconsistent supplier records, potential process issues and actions required to improve onboarding data quality.\n\nUse the uploaded files or pasted data provided by the user. Do not invent missing supplier information or treat a record as invalid without evidence.\n\n## Inputs\n\nUse the available data for:\n\n- Supplier records\n- Supplier names and identifiers\n- Category and service information\n- Entity and department information\n- Supplier status and onboarding stage\n- Contact, payment or contract fields, if available\n- Onboarding rules or required fields, if provided\n\nIf multiple files are provided, explain how they relate to one another before starting the analysis.\n\n## Phase 1, Validate the input data\n\n### Step 1.1, Identify the available fields\n\nReview the available data and identify the information needed to assess supplier onboarding data quality.\n\nConfirm the period or snapshot date, the supplier population, the onboarding stages, the currencies used and any required-field rules provided.\n\n### Step 1.2, Map the available fields\n\nUse the equivalent fields available in the data for supplier names, identifiers, categories, entities, departments, status, onboarding dates, owners and required information.\n\nIf a field is missing or unclear, flag the limitation rather than assuming the information is absent.\n\n### Step 1.3, Check data quality\n\nCheck for missing values, duplicate supplier records, inconsistent names or identifiers, conflicting statuses, missing categories or entities, incomplete onboarding records and outdated information.\n\nDo not silently exclude problematic records. State how important issues affect the results.\n\n## Phase 2, Analyse the data\n\n### Step 2.1, Calculate the main metrics\n\nCalculate, where the data supports it:\n\n- Number of suppliers reviewed\n- Complete and incomplete supplier records\n- Records missing required information\n- Potential duplicate supplier records\n- Suppliers by onboarding stage\n- Suppliers by category, entity and department\n- Changes compared with a previous snapshot, if available\n\n### Step 2.2, Identify the main movements\n\nIdentify the most significant issues by number of suppliers, spend affected if available, onboarding stage, category, entity and department.\n\nFor each priority issue, show the affected supplier or group, missing or inconsistent information, current status, potential impact and recommended next action.\n\nOnly describe a record as a confirmed duplicate or invalid supplier when supported by the data.\n\n### Step 2.3, Identify areas for review\n\nIdentify suppliers blocked in onboarding, records with missing ownership or category, potential duplicates, conflicting statuses, outdated information and issues that may affect procurement reporting or supplier use.\n\nFor each priority area, provide the evidence, potential implication and recommended follow-up action.\n\n## Phase 3, Produce the final output\n\n### Executive summary\n\nSummarise the overall onboarding data quality position, the main missing information, potential duplicates, stages most affected and corrective actions required.\n\n### Main analysis\n\nPresent:\n\n1. Overall supplier onboarding data quality\n2. Missing or incomplete information\n3. Potential duplicate records\n4. Onboarding stage and status issues\n5. Category, entity and department patterns\n6. Suppliers requiring follow-up\n7. Recommended actions\n\nUse a concise table:\n\n| Supplier or issue | Onboarding stage | Missing or inconsistent information | Potential impact | Recommended action |\n|---|---|---|---|---|\n\n### Exceptions and data quality issues\n\nList missing required fields, duplicate candidates, conflicting statuses, outdated records, incomplete periods and assumptions. Explain their impact.\n\n### Questions for review\n\nEnd with questions about required fields, duplicate resolution, ownership, onboarding blockers, status definitions, data refresh frequency and process changes needed to improve supplier data quality.\n\n## Output rules\n\n- Write for a Procurement Manager or finance operations audience.\n- Prioritise issues by operational impact and affected supplier population.\n- Never invent supplier information or required-field rules.\n- Distinguish missing information from invalid information.\n- Flag ambiguous or unreliable data.\n- Keep any financial analysis separate from onboarding data quality findings.\n- End with practical corrective 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Sin embargo, si tienes una empresa en el Espacio Económico Europeo o en el Reino Unido, podemos trabajar contigo y puedes reservar una demo.",{"type":48,"attrs":1462,"content":1463},{"textAlign":17},[1464],{"text":1465,"type":44},"De lo contrario, introduce tu correo electrónico a continuación y te avisaremos cuando podamos ayudarte en tu país.","Gracias por enviar el formulario","Horas","b095740c-b878-41dd-9a7b-f393d2e4de30","El evento comienza en","Ups, algo va mal…","Minutos","Segundos","Actualizar","Aquí no hay opciones.","Se ha producido un error al enviar el formulario. 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