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 employ when requesting spreadsheet-related tasks. The description follows the third-person voice convention and is well-structured.
| 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 use. | 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 preservation. 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 clear workflows and executable code examples. Its main strengths are the concrete code snippets, the mandatory recalculation step with error feedback loop, and the formula verification checklist. Weaknesses include some verbosity (especially the financial modeling standards section which could be a separate reference file) and minor redundancy in explaining concepts Claude already understands.
Suggestions
Move the detailed 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.
Remove or significantly trim the 'Code Style Guidelines' section—Claude doesn't need to be told to write minimal code or avoid unnecessary print statements.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill contains some unnecessary verbosity—the 'WRONG vs CORRECT' examples are somewhat redundant for Claude, and the financial model color coding/documentation standards are quite lengthy. However, most content is practical and relevant. Some sections like 'Code Style Guidelines' tell Claude things it should already know. | 2 / 3 |
Actionability | The skill provides fully executable, copy-paste ready code examples for all major workflows (creating, editing, reading Excel files). Commands for recalc.py are concrete with example usage, and the JSON output format is clearly specified. Formula examples are specific and executable. | 3 / 3 |
Workflow Clarity | The common workflow is clearly sequenced (choose tool → create/load → modify → save → recalculate → verify/fix errors). The recalculation step is marked as MANDATORY, there's an explicit feedback loop for error recovery (fix errors → recalculate again), and the verification checklist provides structured validation checkpoints. | 3 / 3 |
Progressive Disclosure | The content is reasonably well-structured with clear section headers, but it's a monolithic document that could benefit from splitting detailed sections (financial model standards, formula verification checklist) into separate reference files. No bundle files are provided, and the recalc.py script is referenced but not included, which is a gap. The financial modeling standards section is quite long and inline. | 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
- Commit
fa3abd3
- Reviewed
Table of Contents
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