CtrlK
BlogDocsLog inGet started
Tessl Logo

xlsx

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

91

1.54x
Quality

90%

Does it follow best practices?

Impact

91%

1.54x

Average score across 8 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

The canonical home for this skill is xlsx in anthropics/skills

SKILL.md
Quality
Evals
Security

Quality

Content

81%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A strong, highly actionable skill body: executable code, exact commands and conventions, and a workflow with a real validate-fix-retry feedback loop anchored by the recalc.py script. The main weakness is token efficiency — generic pandas/openpyxl primer code re-teaches library basics Claude already knows, and the single-file layout inlines financial-modeling standards that would fit a reference file.

Suggestions

Trim the generic library primers: drop the commented pandas basics (df.head/info/describe) and the 'Hello World'-style openpyxl Workbook example, keeping only the non-obvious usage (data_only warning, read_only/write_only, recalc interplay) — Claude already knows these libraries' basic APIs.

Compress the WRONG/CORRECT hardcoding section to one bad/good pair plus the one-line rule ('all calculations as Excel formulas, never Python-computed constants'); the three repeated examples add length without adding information.

Move the financial-model output standards (color codes, number formats, source-documentation formats) into a references/ file (e.g. references/financial-modeling.md) linked from a short summary section, keeping SKILL.md as a lean overview.

DimensionReasoningScore

Conciseness

The genuinely non-obvious material (recalc.py workflow, financial-model color/number conventions, verification checklists) is efficient, but the body also includes boilerplate library primers Claude already knows — e.g. "df.head() # Preview data / df.info() # Column info", "sheet['A1'] = 'Hello'", and generic openpyxl Workbook/Font/PatternFill usage examples. This fits anchor 3 ("mostly efficient but includes some unnecessary explanation or could be tightened"); it is not anchor 2 because the padding is confined to a couple of code-primer sections rather than pervading the document, and not anchor 4-5 because those primers and the three-example WRONG/CORRECT hardcoding section could be cut or compressed without losing information.

3 / 5

Actionability

Guidance is fully executable throughout: copy-paste pandas/openpyxl snippets, the exact command "python scripts/recalc.py output.xlsx", concrete RGB values ("Blue text (RGB: 0,0,255)"), exact format strings ("$#,##0;($#,##0);-"), documented source-comment formats with examples, and a parsed JSON output schema with field meanings. This matches anchor 5 ("copy-paste ready code or commands; specific examples cover the common cases"); unlike anchor 4 there are no real gaps in the covered cases (read, create, edit, recalculate, verify).

5 / 5

Workflow Clarity

The "Common Workflow" is a numbered 6-step sequence with a mandatory recalculation step, and it includes an explicit feedback loop — "If `status` is `errors_found`, check `error_summary`... Fix the identified errors and recalculate again" — plus a Formula Verification Checklist and concrete error-to-fix mapping (#REF! → invalid references, etc.). This matches anchor 5 ("explicit validation steps; feedback loops for error recovery; checklists"); anchor 4 falls short because validation here is not merely mentioned but instrumented with specific commands and output interpretation.

5 / 5

Progressive Disclosure

The body is well-sectioned (output requirements, workflows, recalculation, verification, best practices) and its bundle references are real and one level deep (scripts/recalc.py and scripts/office/soffice.py both exist on disk and are clearly signaled). However, everything lives inline in a single ~290-line SKILL.md with no reference files; the ~60-line financial-modeling standards and the library primers are content that could be split into separate reference docs, matching anchor 4 ("most content is appropriately placed... minor organization gaps") rather than anchor 5 ("content appropriately split" with well-signaled references to detail files).

4 / 5

Total

17

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

An exemplary description: concrete capability list, explicit positive and negative trigger guidance, natural user phrasing with file extensions and synonyms, and clear boundary marking against adjacent skills. The only conceivable criticism is length, but every clause carries trigger or scope information rather than padding.

DimensionReasoningScore

Specificity

The description enumerates many concrete actions — "open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch... or convert between tabular file formats" — giving comprehensive coverage rather than 1-2 generic actions. It clearly exceeds anchor 4 ("several specific actions; minor gaps") since creation, editing, fixing, conversion, and cleaning are all named with concrete sub-examples; it is not vague or abstract like anchors 1-2.

5 / 5

Completeness

Both questions are answered explicitly: the "what" is the enumerated action list (open/read/edit/fix/create/convert), and the "when" is stated twice — "Use this skill any time a spreadsheet file is the primary input or output" and "Trigger especially when the user references a spreadsheet file by name or path" — plus explicit negative triggers ("Do NOT trigger when the primary deliverable is a Word document..."). This matches the anchor-5 example structure exactly and goes beyond anchor 4's "'when' could be more explicit".

5 / 5

Trigger Term Quality

Natural user phrasing is covered comprehensively with synonyms and extensions: "spreadsheet file", ".xlsx, .xlsm, .csv, or .tsv", "references a spreadsheet file by name or path — even casually (like 'the xlsx in my downloads')", "messy tabular data files". This matches the anchor-5 pattern ("PDF files, PDFs, forms, .pdf") of including both natural synonyms and file extensions; nothing common is missing.

5 / 5

Distinctiveness Conflict Risk

It carves out a clear niche (spreadsheet files as the deliverable) and explicitly fences off adjacent skills — "Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved" — which is stronger than anchor 4's "minor overlap risk with closely related skills". Conflict risk with e.g. a docx or data-pipeline skill is directly addressed.

5 / 5

Total

20

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

referenced_paths_exist

Referenced path issues: 1 deeper-than-1-level

Warning

Total

15

/

16

Passed

Repository
ZHangZHengEric/Sage
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.