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, lists concrete capabilities, and provides explicit trigger conditions with a numbered list of use cases. It includes relevant file extensions and natural keywords that users would mention. The description follows the pattern of good examples in the rubric closely, particularly resembling the presentation skill example structure.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: creating spreadsheets with formulas and formatting, reading/analyzing data, modifying existing spreadsheets while preserving formulas, data analysis and visualization, and recalculating formulas. | 3 / 3 |
Completeness | Clearly answers both 'what' (comprehensive spreadsheet creation, editing, analysis with formulas, formatting, visualization) and 'when' (explicit numbered list of trigger scenarios prefaced by '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'. These cover common file extensions and task-related terms users would naturally mention. | 3 / 3 |
Distinctiveness Conflict Risk | Clearly scoped to spreadsheet files with specific file extensions (.xlsx, .xlsm, .csv, .tsv) and spreadsheet-specific operations like formula recalculation and preserving formulas. Unlikely to conflict with general data analysis or document processing skills. | 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 mandatory validation steps and error recovery loops. The code examples are executable and well-chosen. The main weakness is that the financial modeling section adds significant length and could be split into a separate reference file, and some explanatory text could be trimmed to respect Claude's existing knowledge.
Suggestions
Consider splitting the financial model standards (color coding, number formatting, documentation requirements) into a separate FINANCIAL_MODELS.md reference file to reduce the main skill's token footprint.
Trim explanatory phrases like 'which provides powerful data manipulation capabilities' and 'This ensures the spreadsheet remains dynamic and updateable' — Claude already understands these concepts.
| 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. Some sections like library selection tips explain things Claude already knows. | 2 / 3 |
Actionability | The skill provides fully executable, copy-paste ready code examples for all major workflows: reading with pandas, creating with openpyxl, editing existing files, and recalculating formulas. The recalc.py usage, JSON output format, and error handling are all concrete and specific. | 3 / 3 |
Workflow Clarity | The common workflow is clearly sequenced (choose tool → create/load → modify → save → recalculate → verify/fix errors) with an explicit validation feedback loop: recalculate, check for errors, fix, and recalculate again. The formula verification checklist adds additional validation checkpoints. The recalc.py step is marked as MANDATORY. | 3 / 3 |
Progressive Disclosure | The content is reasonably well-structured with clear section headers, but it's a long monolithic document that could benefit from splitting detailed sections (financial model standards, formula verification checklist) into separate referenced files. No bundle files are provided, so everything is inline, making the skill quite lengthy. | 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
- answerzhao/agent-skills
- Commit
aad73ed
- Reviewed
Table of Contents
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