xlsx
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When GLM 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
82
77%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/xlsx/SKILL.mdQuality
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 and concrete actions. It provides explicit trigger conditions through a numbered list of use cases and includes natural keywords users would use. The only minor note is the reference to 'GLM' instead of 'Claude', but this doesn't materially affect the description's quality for skill selection purposes.
| 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 GLM 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) and spreadsheet-specific operations like formula recalculation and preservation. Unlikely to conflict with other document or data skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
55%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill is highly actionable with excellent workflow clarity, providing executable code, clear sequencing, and proper validation/error recovery loops. However, it is severely undermined by extreme verbosity and lack of progressive disclosure - the monolithic structure packs style guides, financial conventions, chart notes, and multiple code examples into one massive file. Significant content (style rules, financial model conventions, chart creation details) should be extracted into referenced sub-files, and redundant explanations should be eliminated.
Suggestions
Extract the style rules (Default Style, Professional Finance Style, font standards, title formatting) into a separate STYLES.md file referenced from the main skill
Extract financial model conventions (color coding, number formatting, formula construction, documentation requirements) into a separate FINANCIAL_MODELS.md file
Remove redundant content: color coding conventions appear twice (Financial Models section and Content Color Conventions section), title formatting examples are repeated across multiple code blocks
Remove explanations of things Claude already knows (e.g., what pandas does, basic openpyxl cell indexing) and trim the pandas reading/analysis section which adds little unique value
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose at ~400+ lines, with significant redundancy. Color coding standards are repeated (financial model section and content color conventions say the same thing). Title formatting rules are stated, then re-demonstrated in multiple code examples. Many concepts Claude already knows (what pandas does, how to use basic openpyxl) are explained at length. The style rules section alone could be cut by 50%+. | 1 / 3 |
Actionability | The skill provides fully executable Python code examples throughout - creating workbooks, loading files, applying styles, using formulas, running recalc.py. Code is copy-paste ready with correct imports and realistic usage patterns. The recalc.py JSON output format and error handling guidance are concrete and specific. | 3 / 3 |
Workflow Clarity | The common workflow is clearly sequenced (choose tool → plan → create/load → modify → save → recalculate → verify). The recalculation step is marked as MANDATORY, with explicit error recovery: check error_summary, fix identified errors, recalculate again. The formula verification checklist provides systematic validation. Chart creation includes the critical plot_visible_only gotcha. | 3 / 3 |
Progressive Disclosure | This is a monolithic wall of text with no references to external files for detailed content. The extensive style rules, color palettes, financial model conventions, and chart creation notes could all be split into separate reference files. Everything is inlined into a single massive document, making it difficult to navigate and consuming excessive context window space. | 1 / 3 |
Total | 8 / 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
- jjyaoao/HelloAgents
- Commit
07048a9
- Reviewed
Table of Contents
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