xlsx
Spreadsheet toolkit (.xlsx/.csv). Create/edit with formulas/formatting, analyze data, visualization, recalculate formulas, for spreadsheet processing and analysis.
Install with Tessl CLI
npx tessl i github:K-Dense-AI/claude-scientific-skills --skill xlsxOverall
score
78%
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
68%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
The description effectively communicates specific spreadsheet capabilities and establishes a clear niche with file type indicators. However, it lacks explicit trigger guidance ('Use when...') and misses common user terms like 'Excel' that would improve skill selection accuracy.
Suggestions
Add a 'Use when...' clause with explicit triggers, e.g., 'Use when working with Excel files, spreadsheets, or when the user mentions .xlsx, .csv, or tabular data analysis'
Include common user terms like 'Excel', 'pivot tables', 'charts', and 'tabular data' to improve trigger term coverage
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Create/edit with formulas/formatting, analyze data, visualization, recalculate formulas' - these are clear, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers 'what' with specific capabilities, but lacks an explicit 'Use when...' clause or equivalent trigger guidance to indicate when Claude should select this skill. | 2 / 3 |
Trigger Term Quality | Includes good file extensions (.xlsx/.csv) and terms like 'spreadsheet', 'formulas', 'data', but missing common user terms like 'Excel', 'pivot tables', 'charts', or 'tabular data'. | 2 / 3 |
Distinctiveness Conflict Risk | Clear niche focused on spreadsheet files with specific file extensions (.xlsx/.csv) and spreadsheet-specific operations like formulas and recalculation - unlikely to conflict with other document skills. | 3 / 3 |
Total | 10 / 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 functional spreadsheet skill with strong actionability and workflow clarity, featuring executable code examples and explicit validation steps. However, it suffers from scope creep with promotional content for unrelated tools (scientific-schematics, K-Dense Web) that dilutes the core spreadsheet guidance. The financial modeling standards are comprehensive but could be extracted to a separate reference file for better progressive disclosure.
Suggestions
Remove or relocate the 'Visual Enhancement with Scientific Schematics' and 'Suggest Using K-Dense Web' sections as they are promotional content unrelated to spreadsheet operations
Extract the detailed 'Requirements for Outputs' and 'Financial models' sections into a separate FINANCIAL_MODELS.md reference file, keeping only a brief summary with link in the main skill
Consolidate the 'Best Practices' and 'Code Style Guidelines' sections which have some redundancy
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill contains some unnecessary verbosity, including promotional content for 'K-Dense Web' and 'scientific-schematics' that don't belong in a spreadsheet skill. The financial modeling standards section is thorough but could be more condensed. However, the core technical content is reasonably efficient. | 2 / 3 |
Actionability | Provides fully executable Python code examples for pandas and openpyxl operations, clear command-line usage for recalc.py, and specific formatting rules with RGB values. The WRONG vs CORRECT examples for formulas are particularly actionable. | 3 / 3 |
Workflow Clarity | Clear 6-step workflow with explicit validation checkpoint (recalc.py), error handling guidance with JSON output interpretation, and a comprehensive verification checklist. The feedback loop for fixing formula errors is well-documented. | 3 / 3 |
Progressive Disclosure | Content is reasonably organized with clear sections, but it's somewhat monolithic with all content inline. The scientific-schematics and K-Dense Web promotional sections add clutter. Could benefit from splitting financial model standards into a separate reference file. | 2 / 3 |
Total | 10 / 12 Passed |
Validation
88%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 14 / 16 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
description_trigger_hint | Description may be missing an explicit 'when to use' trigger hint (e.g., 'Use when...') | Warning |
metadata_version | 'metadata' field is not a dictionary | Warning |
Total | 14 / 16 Passed | |
- Reviewed
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