agentleFS
rmusser01rmusser01/tldw-stuff/skills/chatbook/chatbook-xlsx/SKILL.md

chatbook-xlsx

Skill2 starsChanged 2 months agoApache-2.0View on GitHub

Create, edit and analyze Excel .xlsx workbooks from supplied tables or Chatbook material, preserving formulas and distinguishing calculated results from cached values.

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use openpyxl through available authorized Python execution.

    line 13

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Excel workbooks

Produce an editable .xlsx with traceable inputs and inspectable calculations. Use openpyxl through available authorized Python execution. The skill is standalone: no account or Hermes installation is required. Local execution and filesystem access must actually be available; otherwise provide the table/model specification and state that a workbook has not been generated.

Understand the data

Determine the intended question, units, currency, date range and source tables from the request. Retrieve full relevant Chatbook passages when notes are the source. Keep missing values distinct from zero, preserve identifiers with leading zeros, and retain source links or IDs. Do not turn estimates into observations.

For existing workbooks, inventory sheets, formulas, tables, names, charts, merged ranges and relevant formatting before editing. Load with formulas retained for any workbook you intend to save. Keep a separate output unless replacement was requested. Macro-enabled or complex feature-heavy workbooks need explicit preservation planning; the bundled example targets ordinary .xlsx files.

Build a useful model

Separate assumptions/inputs from derived values, using sheets when that improves clarity. Prefer formulas for relationships the user should be able to change. Label units, style input cells consistently, choose appropriate date/currency/ percentage formats, and use frozen headers and filters for larger tables. Distinguish an empty cell, an unavailable observation and a computed zero.

The runnable example builds a small fictional cost model with formulas, validation and a chart. Replace its data for real work. Resolve its path from the skill directory. Use editing and calculation guidance for existing files, CSV input, structural edits and recalculation.

For analysis, inspect data types, missingness, duplicates and grouping assumptions before calculating results. Write transformations and assumptions into a notes sheet when they affect interpretation. Choose charts that expose the relevant comparison; include units and avoid a misleading axis or unsupported precision.

Check calculations and presentation

Reopen with data_only=False and confirm values, formulas, ranges and changed cells. Independently calculate a few representative totals from the source, including a boundary case such as a blank input or zero quantity. This checks the model's intended arithmetic, not execution of Excel formulas.

openpyxl writes formulas but does not evaluate them. Setting recalculation-on-open is a request to an application, not evidence that the results exist. If Excel or LibreOffice is available, recalculate a separate copy, check cached values and error cells, and compare the formulas/features preserved by the round trip. Otherwise state that recalculation is pending; do not invent cached results.

Inspect column widths, number formats, headers and print areas. When a spreadsheet viewer or rendered preview is available, check the affected sheets visually. Structural read-back cannot prove that every cell displays without clipping.

Deliver the workbook path, relevant findings/assumptions and the exact verification limits. Import does not install dependencies, execute macros, publish files or write notes automatically.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.