Data & Analysis ✓ Anthropic · Official xlsxopenpyxlfinancial-modelingheadless-automationexcel-workbooks

Headless Excel Workbook Builder

Generate deliverable Excel files when no Office application is available.

FollowSkills review · FSRS-2.0
Not recommended
51/ 100 5-point scale 2.6 / 5
Trust15 / 25 · 3.0/5

The skill scopes output to ./out/<name>.xlsx and specifies openpyxl, with no evident malicious external effects; however, it lacks user confirmation, sensitive-data handling, dependency-security guidance, rollback, and explicit data-flow disclosure, so points are deducted.

Reliability8 / 20 · 2.0/5

The headless context, output path, openpyxl example, and modeling conventions make the happy path plausible; however, dependencies are neither pinned nor installed, and there is no abnormal-input handling, failure feedback, overwrite protection, or committed testing, warranting a conservative score.

Adaptability10 / 15 · 3.3/5

The intended managed-agent/CMA scenario is clear, and the non-fit condition for available live Excel tools is stated; inputs, naming parameters, trigger boundaries, complex-workbook limits, and Chinese-language support are insufficiently specified, so the score is limited.

Convention8 / 15 · 2.7/5

The document has clear purpose, output contract, example, conventions, and a non-use section; the repository supplies an Apache-2.0 license and verified official provenance, but the skill lacks versioning, changelog, named maintenance responsibility, update path, troubleshooting, and FAQs.

Effectiveness6 / 15 · 2.0/5

It can direct creation of a collectible .xlsx artifact and provides useful input/formula/check conventions; representative outputs, formula correctness, formatting integrity, and compatibility are not verified, and human review remains necessary, so the static score is conservative.

Verifiability4 / 10 · 2.0/5

Repository CI validates plugins and scans for secrets, but it does not cover the skill's workbook-generation key paths; the skill contains only prose and a code example, with no committed tests, execution evidence, or independent corroboration.

Evidence confidence:Low Reviewed Jul 20, 2026 Reviewed revision 4aa51ed3d379
Before you use it
  • Confirm that a compatible Python environment and openpyxl are installed; installation and version requirements are unspecified.
  • Same-named outputs may be overwritten and formulas may be incorrect; manually review the workbook, formulas, checks, and sensitive data before delivery.
  • The skill is intended for headless use when live Excel tools are unavailable; Chinese-language support, localized templates, and complex Excel feature compatibility are unproven.
Review evidence [1][2][3][4][5][6]
See the full review method →

What it does & when to use it

xlsx-author is designed for headless managed-agent or CMA sessions that need to produce an .xlsx file instead of editing an open Excel workbook. It requires the workbook to be saved under ./out/<name>.xlsx and the relative path to be returned in the final response. The skill uses openpyxl and defines conventions for inputs, formulas, links, named ranges, and balance checks. It fits automated file-producing workflows, but not workflows centered on live Excel interaction.

It instructs the agent to write and run a short Python script with openpyxl, create workbook sheets and cells, add formulas, apply font colors, and save the file to the required output directory. Hardcoded inputs are blue, formulas are black, and links to another sheet or file are green; calculation cells must not contain hardcodes, values referenced from a deck or memo should use named ranges, and a Checks sheet should expose TRUE/FALSE balance checks. The resulting file is written to ./out/<name>.xlsx and the relative path is returned.

  1. A managed-agent user needs to deliver an Excel financial model in an environment without an open Office application.
  2. A financial analyst needs to generate a workbook with Inputs, calculation sheets, and a Checks sheet using Python and openpyxl.
  3. An automation pipeline needs the generated .xlsx file as an artifact that a downstream orchestration layer can collect.
  4. A model builder needs consistent conventions for hardcoded inputs, formulas, cross-sheet links, and balance checks.

Pros & cons

Pros
  • Explicitly supports managed-agent environments without an Office application.
  • Produces a collectible .xlsx file artifact with a defined output path.
  • Provides concrete conventions for inputs, formulas, cross-sheet links, named ranges, and checks.
  • Uses Python and openpyxl, making scripted workbook generation practical.
Limitations
  • Requires an environment that can run Bash and Python, plus the openpyxl dependency.
  • Does not drive a live Excel workbook; the source directs users to mcp__office__excel_* when those tools are available.
  • The source provides no test suite, version requirements, or failure-recovery procedure.
  • The skill defines workbook-generation conventions but does not document support for complex templates, charts, or macros.

How to install

In Cowork, open Settings → Plugins → Add plugin, paste https://github.com/anthropics/financial-services, and select Pitch Agent; or use Claude Code: run claude plugin marketplace add anthropics/financial-services, followed by claude plugin install pitch-agent@claude-for-financial-services. The source does not document a separate xlsx-author installation command.

How to use

In a headless managed-agent or CMA session, request an Excel file, for example: “Create a financial model with Inputs, calculation, and Checks sheets, and save it as ./out/model.xlsx.” The agent should use Python and openpyxl, save the output as ./out/<name>.xlsx, and return the relative path in its final response. No dedicated trigger phrase is documented.

Compared to similar skills

Compared with using mcp__office__excel_* to operate a live Excel workbook, xlsx-author targets headless environments and directly produces a file artifact; the source recommends the live-workbook approach when Office tools are available.

FAQ

Does it modify an already-open Excel workbook?
No. It is for generating a file in a headless environment; when mcp__office__excel_* tools are available, those tools should be used for a live workbook.
Where is the output saved?
It must be saved to ./out/<name>.xlsx, creating ./out/ first if necessary.
What runtime dependencies are required?
The source explicitly requires Bash to run a Python script and openpyxl to create the workbook.
Does it guarantee that the model is correct?
The source does not support that claim. It requires a Checks sheet and modeling conventions, but provides no test suite or complete correctness guarantee.

More skills from this repository

All from anthropics/financial-services

Data & Analysis ✓ Anthropic · Official

Three-Statement Model Builder

Populate and validate linked income statement, balance sheet, and cash flow models with formulas.

Data & Analysis ✓ Anthropic · Official

Spreadsheet Auditor

Checks spreadsheet formulas, errors, and financial-model integrity.

Data & Analysis ✓ Anthropic · Official

Three-Statement Model Builder

Complete existing three-statement templates with linked formulas, projections, scenarios, and audit checks.

Data & Analysis ✓ Anthropic · Official

Comparable Company Valuation

Build institutional-grade peer valuation analyses with operating metrics, trading multiples, and statistical benchmarks in spreadsheets.

Data & Analysis ✓ Anthropic · Official

Competitive Landscape Analyst

Turn competitive research into an approved, comparable market landscape deck.

Data & Analysis ✓ Anthropic · Official

Earnings Update Researcher

Turn quarterly results into an institutional-style update focused on beats, estimate changes, valuation, and thesis impact.

Data & Analysis ✓ Anthropic · Official

Sector Landscape Research

Structure industry dynamics, competition, valuation, and investment themes in one research workflow.

Productivity & Collaboration ✓ Anthropic · Official

PE Investment Committee Memo Writer

Turns diligence, financial analysis, and deal terms into a structured memo for private equity investment committee approval.

Data & Analysis ✓ Anthropic · Official

Excel Data Cleaning Assistant

Clean inconsistent spreadsheets before analysis.

Data & Analysis ✓ Anthropic · Official

Financial Deck Refresh

Update financial figures across an existing presentation while preserving its formatting and structure.

Writing & Content ✓ Anthropic · Official

IC Memo Drafting

Turns diligence and financial inputs into a structured IC memo.

Data & Analysis ✓ Anthropic · Official

Financial Model Auditor

Find spreadsheet formula errors and test financial-model integrity before review.

Automation & Ops ✓ Anthropic · Official

Reconciliation Break Tracer

Trace ledger breaks to source entries and state the operational root cause.

Automation & Ops ✓ Anthropic · Official

KYC Intake Parser

Turn onboarding packets into structured KYC data ready for screening.

Data & Analysis ✓ Anthropic · Official

Audit XLS: Spreadsheet Model Review

Systematically checks spreadsheet formulas, errors, and financial-model integrity issues.

Data & Analysis ✓ Anthropic · Official

General Ledger Roll-Forward

Connects a balance-sheet account’s opening balance to its period-end GL balance for close packages and audit support.

Data & Analysis ✓ Anthropic · Official

Investment Banking Pitch Deck Filler

Populate existing investment banking PowerPoint templates with validated data from Excel, CSV, and other source files.

Data & Analysis ✓ Anthropic · Official

Three-Statement Model Filler

Complete and validate integrated three-statement templates with formulas, linkages, and audit checks.

Data & Analysis ✓ Anthropic · Official

Financial Model Audit

Systematically checks spreadsheet formulas and model integrity.

Data & Analysis ✓ Anthropic · Official

GL–Subledger Reconciliation

Reconcile general ledger and subledger data, expose breaks, and suggest likely causes for investigation.

Related skills