140 skills · sorted by relevance
Validate spreadsheet sources before running Python scripts to transform data, update multiple sheets, or apply formatting. Check required data first, try backup sources when needed, and report errors clearly if processing cannot proceed.
Process Excel workbooks and generate PDF reports by running Python scripts directly. Covers multiple sheets, data transformations, formatting, and error handling, with scripts saved as files for complex tasks.
Create a related Excel workbook, PNG diagram, and PDF report in one workflow. It allocates execution attempts across stages, checks output files, and provides retries or simpler versions when generation encounters errors.
Create Excel files with openpyxl, a Python spreadsheet library, by switching to shell execution when sandbox tools fail. Examples cover cell styling, formulas, merged cells, multiple sheets, error reporting, and checking that the output file exists.
Inspect unfamiliar Excel workbooks before building extraction scripts. Map sheets, headers, columns, and row patterns, then use those findings to distinguish actual records from summaries and blank rows when extracting data.
Handle merged cells before filling Excel templates with openpyxl, a Python library for spreadsheets. This skill shows how to inspect merged ranges, unmerge the required areas, write values, and save the workbook without merged-cell write errors.
Audit generated Excel reports by reopening saved workbooks, listing populated rows and formulas, and comparing subtotal references with independently identified detail rows. Detect missing or extra rows in totals and preserve an inspection log.
Audit existing public equity investment models and spreadsheets for formula errors, source support, assumptions, and scenario quality. Receive a readiness verdict, an issue log, and prioritized fixes showing whether the model supports its intended decision.
Analyze Excel workbooks across multiple sheets, locate matching fields, clean values, and compare groups. Produce counts, cross-tabulations that compare categories, charts, and an Excel report with a download link.
Extract selected ranges from Excel workbooks with multiple sheets, check missing values, and clean numeric data. Fit a straight trend line, save charts and CSV results, and convert larger tables to Parquet for subsequent analysis.
Count rows across Excel sheets to assess data size, then analyze an existing Parquet file, a format for storing tabular data. Calculate category counts and percentages, and save the results as an Excel summary and a pie chart.
Filter rows from a selected Excel sheet, summarize category counts and percentages, and export the required columns to a new workbook. The workflow also cleans filter values, renames columns, and provides a download link.
Clean categorical Excel data and compare counts and percentage shares across groups. Create cross-tabulation tables, heatmaps that show differences through color, and category rankings, then export the analysis to a workbook with multiple sheets.
Extract coefficients associated with a chosen label across Excel sheets and check them against a standard value. Create a comparison workbook showing each value, its source sheet, and red highlighting for rows that fail the check.
Use this skill whenever the user asks for an Excel spreadsheet, a .xlsx file, or a workbook with formulas/pivots/multiple sheets — creating one from scratch or editing an existing one. Covers the rule that computed values must be written as real Excel formulas (never hardcoded numbers), and a static formula-safety check. Formulas are NOT recalculated in this environment — see 'Not supported'.
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Use when platform-reported conversions disagree with GA4/ecommerce, when you suspect Meta and Google are double-counting the same sales, or for a standing (monthly) reconciliation workbook that de-dups stacked credit against an order-ID truth set, normalizes attribution windows and currency, compares attribution models, and reads incrementality from a geo/holdout test. Not for the point-in-time R2 veto or RQS gate — use ad-account-auditor; not for the ROI/ROAS ratio math itself — use roi-calculator; not for organic dark-social share attribution or GA4 direct-traffic decomposition — use dark-social-attributor. 付费广告归因对账/去重/增量
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Create, inspect, edit, recalculate, validate, render, and deliver Excel workbooks while preserving formulas, formatting, drawings, links, macros, and metadata.
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Aligns learning material to the standard it claims — choosing the right framework for the grade and subject, citing standards by code rather than reproducing their text, and telling a real alignment from a decorative one. Use this to align a worksheet, lesson or workbook to Common Core, NGSS or a state framework, to check an alignment claim before publishing, or to decide what may lawfully be printed on the cover.
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SkillsBench task authoring — walk a contributor from idea to submission-ready task following CONTRIBUTING.md and the task-implementation rubric. Use when the user wants to create a new SkillsBench task, scaffold a task from an existing workflow (notebook, Excel workbook, document, dataset), convert a prompt or a benchmark item into a SkillsBench task, write skills for a task, or prepare a SkillsBench PR. Pairs with `task-review` (run that as a self-check before submitting).
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Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and pivot tables. When Claude needs to work with spreadsheets (.xlsx files) for: (1) Creating new spreadsheets with data and formatting, (2) Reading or analyzing Excel data with pandas, (3) Creating pivot tables programmatically with openpyxl, (4) Building multi-sheet workbooks with source data and pivot table sheets, or (5) Any Excel file operations
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Read Microsoft Excel (.xlsx) files robustly with `openpyxl` (or `pandas`). Covers multi-sheet workbooks, header rows, empty cells, merged cells, comma-separated list cells, and converting a sheet to a list-of-dicts the rest of your code can consume. Use when a task input or reference document is an `.xlsx` file rather than JSON/CSV.
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Adds Excel Online (Business) connector to a Power Apps code app. Use when reading or writing Excel workbook data from OneDrive or SharePoint.
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Expert guidance for FedRAMP certification and compliance under CR26 (FedRAMP Consolidated Rules for 2026). Use this skill whenever a user asks about FedRAMP authorization, ATO (Authority to Operate), cloud security for federal government, NIST SP 800-53 controls, CSP compliance, or any of the core FedRAMP document types: SSP, SAP, SAR, POA&M, CIS/CRM workbooks. Also trigger for questions about FedRAMP Certification Classes (A, B, C, D — new baseline labels: A = pilot/transitional, B = LI-SaaS/Low, C = Moderate, D = High, per NTC-0004), FedRAMP 20x (now the primary authorization pathway), OSCAL mandate (September 2026), 3PAO assessments, continuous monitoring (ConMon), gap assessments, system boundary definition, or architecture reviews for federal cloud. FedRAMP Ready retired July 28, 2026 (Legacy FedRAMP Ready). When in doubt, use this skill — it covers the full FedRAMP lifecycle from readiness through continuous monitoring.
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Expert guidance for FedRAMP certification and compliance under CR26 (FedRAMP Consolidated Rules for 2026). Use this skill whenever a user asks about FedRAMP authorization, ATO (Authority to Operate), cloud security for federal government, NIST SP 800-53 controls, CSP compliance, or any of the core FedRAMP document types: SSP, SAP, SAR, POA&M, CIS/CRM workbooks. Also trigger for questions about FedRAMP Certification Classes (A, B, C, D — new baseline labels: A = pilot/transitional, B = LI-SaaS/Low, C = Moderate, D = High, per NTC-0004), FedRAMP 20x (now the primary authorization pathway), OSCAL mandate (September 2026), 3PAO assessments, continuous monitoring (ConMon), gap assessments, system boundary definition, or architecture reviews for federal cloud. FedRAMP Ready retires July 28, 2026. When in doubt, use this skill — it covers the full FedRAMP lifecycle from readiness through continuous monitoring.
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