xlsx
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
77
88%
Does it follow best practices?
Impact
76%
1.35xAverage score across 10 eval scenarios
Passed
No known issues
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong skill description that clearly defines its scope around spreadsheet operations with specific file types, concrete actions, and explicit trigger conditions. It follows the pattern of good examples in the rubric, particularly resembling the presentation skill example structure. The numbered use-case list provides excellent clarity for skill selection.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: creation, editing, analysis, formulas, formatting, data analysis, visualization, reading data, modifying while preserving formulas, and recalculating formulas. | 3 / 3 |
Completeness | Clearly answers both 'what' (comprehensive spreadsheet creation, editing, analysis with formulas, formatting, etc.) and 'when' (explicit numbered list of trigger scenarios starting with 'When Claude needs to work with spreadsheets'). | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'spreadsheet', '.xlsx', '.xlsm', '.csv', '.tsv', 'formulas', 'formatting', 'data analysis', 'visualization'. Good coverage of file extensions and common terms. | 3 / 3 |
Distinctiveness Conflict Risk | Clearly scoped to spreadsheet files with specific file extensions (.xlsx, .xlsm, .csv, .tsv), making it distinct from general data analysis or document processing skills. The focus on formulas, recalculation, and spreadsheet-specific operations creates a clear niche. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid, actionable skill with excellent workflow clarity including validation feedback loops via recalc.py. The code examples are executable and well-chosen. The main weaknesses are the somewhat verbose financial modeling section that could be extracted to a separate reference file, and minor redundancy in explanations that Claude wouldn't need.
Suggestions
Extract the financial modeling standards (color coding, number formatting, documentation requirements) into a separate FINANCIAL_MODELS.md reference file to improve progressive disclosure and reduce the main skill's token footprint.
Trim explanatory text like 'This applies to ALL calculations - totals, percentages, ratios, differences, etc. The spreadsheet should be able to recalculate when source data changes.' which Claude can infer from the examples alone.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill contains some unnecessary verbosity, particularly in the financial modeling section (color coding standards, documentation requirements for hardcodes) which is quite detailed for a general spreadsheet skill. The 'WRONG vs CORRECT' examples are useful but slightly over-explained. However, most sections are reasonably efficient and the code examples are lean. | 2 / 3 |
Actionability | The skill provides fully executable, copy-paste ready code examples for all major operations (reading, creating, editing, recalculating). Commands like `python recalc.py output.xlsx 30` are specific and concrete. The formula verification checklist and recalc.py JSON output format give Claude precise, actionable guidance. | 3 / 3 |
Workflow Clarity | The common workflow is clearly sequenced (choose tool → create/load → modify → save → recalculate → verify and fix errors) with an explicit validation feedback loop: recalculate, check for errors, fix, and recalculate again. The recalc.py output interpretation and error types are well-documented, providing clear checkpoints for error recovery. | 3 / 3 |
Progressive Disclosure | The content is well-structured with clear headers and logical sections, but it's quite long and monolithic for a single file. The financial modeling standards section is substantial and could be split into a separate reference file. No external references to supporting documents are provided despite the complexity warranting them. However, the sections are well-organized internally. | 2 / 3 |
Total | 10 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- majiayu000/claude-skill-registry-data
- Commit
6770aaa
- Reviewed
Table of Contents
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