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    Workbook Ops: Spreadsheet Build & Audit

    1

    Build, edit, and audit .xlsx, .csv, and .tsv files with Python while keeping live formulas, references, charts, and formatting intact.

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    Workbook Ops: Spreadsheet Build & Audit

    Workbook Ops: Spreadsheet Build & Audit

    Example session with this skill installed

    I have model/roi_forecast.xlsx with an Inputs sheet and a Summary sheet. The Summary totals were pasted as hardcoded values last quarter, and I think some cross-sheet formulas shifted after we inserted two rows into Inputs. Please rebuild the totals as live SUM formulas, fix any broken references, apply #,##0 number formats to the new cells, keep the existing header styles, and save the result as model/roi_forecast_v2.xlsx without touching the original. Then run a formula error scan and give me a short report of what changed and what still needs a manual look in Excel.

    • Read your context and instructions
    • Compiled the workbook ops

    Summary

    Audited and repaired roi_forecast.xlsx and delivered model/roi_forecast_v2.xlsx — 26 hardcoded totals converted to live SUM formulas, 2 shifted cross-sheet references fixed, and number formats applied, with every original input value and header style untouched.

    MetricBeforeAfter
    Hardcoded values in calc cells260 (live formulas)
    Formula errors found (#REF!, #DIV/0!)40
    Formula cells scannednever audited318
    Refs broken by inserted rows2 stalere-pointed to Inputs!B6:B27

    Next steps

    • Open roi_forecast_v2.xlsx once in Excel or LibreOffice so cached values recalculate (openpyxl writes formulas, it does not evaluate them).
    • Confirm Summary!E12 (ROI %) now divides by the repaired Inputs!C9 growth-rate cell.
    • Diff the rendered layout in tmp/workbooks/roi_forecast_v2.pdf against the original before circulating.
    • Keep the original as the system of record; future edits save under new version names.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    The problem

    Standard data tools often strip away Excel formulas, broken references, and custom branding when saving files. Developers struggle to programmatically edit workbooks without destroying the complex logic and formatting that business users rely on.

    What it does

    • Edits existing .xlsx files while preserving live formulas, named ranges, and charts.
    • Builds complex workbooks from scratch with custom styles, number formats, and cross-sheet references.
    • Performs automated audits to detect formula errors like #REF! or #DIV/0! across all sheets.
    • Integrates pandas for heavy data manipulation and openpyxl for high-fidelity spreadsheet styling.

    Frameworks & tools

    Python, openpyxl, pandas, and optional rendering via LibreOffice or Poppler.

    Why this beats prompting it yourself

    General LLMs often suggest overwriting cells with static values, which breaks dynamic models. This skill enforces a "formula-first" workflow and includes specific logic for handling merged cells and caching, preventing the accidental corruption of enterprise-grade spreadsheets.

    Use cases

    • Automate the generation of monthly financial reports with professional IB-style formatting.
    • Audit legacy spreadsheets for broken logic and inconsistent cell references.
    • Inject fresh data into existing templates without damaging pre-built pivot tables or charts.
    • Convert raw CSV exports into polished, multi-sheet workbooks with data validation.

    Known limitations

    openpyxl does not execute formulas. Live calculation results are only visible once the file is opened in a spreadsheet application like Excel or LibreOffice.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

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    2. 2

      Unzip into your skills folder

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    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

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