pandas-pro
Performs pandas DataFrame operations for data analysis, manipulation, and transformation. Use when working with pandas DataFrames, data cleaning, aggregation, merging, or time series analysis. Invoke for data manipulation tasks such as joining DataFrames on multiple keys, pivoting tables, resampling time series, handling NaN values with interpolation or forward-fill, groupby aggregations, type conversion, or performance optimization of large datasets.
89
100%
Does it follow best practices?
Impact
78%
1.11xAverage score across 6 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 an excellent skill description that hits all the marks. It uses proper third-person voice, provides comprehensive specific actions, includes natural trigger terms that data analysts would use, and has explicit 'Use when' and 'Invoke for' clauses that clearly delineate when to select this skill. The pandas-specific terminology creates a distinct niche that minimizes conflict risk with other data-related skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'joining DataFrames on multiple keys, pivoting tables, resampling time series, handling NaN values with interpolation or forward-fill, groupby aggregations, type conversion, performance optimization of large datasets.' | 3 / 3 |
Completeness | Clearly answers both what ('Performs pandas DataFrame operations for data analysis, manipulation, and transformation') and when ('Use when working with pandas DataFrames...') with explicit 'Use when' and 'Invoke for' clauses providing detailed trigger guidance. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'pandas', 'DataFrame', 'data cleaning', 'aggregation', 'merging', 'time series', 'joining', 'pivoting', 'NaN values', 'groupby', 'forward-fill' - these are all terms data analysts naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Clear niche focused specifically on pandas DataFrames with distinct technical triggers like 'DataFrame', 'groupby', 'forward-fill', 'resampling' that are unlikely to conflict with general data or document processing skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is an excellent skill file that demonstrates best practices across all dimensions. It provides concrete, executable code patterns with clear before/after comparisons, maintains a logical workflow with validation steps, and appropriately structures content with a reference table for deeper topics. The constraints section effectively captures both positive and negative guidance without being verbose.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is lean and efficient, assuming Claude's competence with pandas. No unnecessary explanations of what pandas is or basic programming concepts. Every section provides actionable patterns without padding. | 3 / 3 |
Actionability | Provides fully executable, copy-paste ready code examples throughout. Each pattern shows concrete before/after comparisons, specific method calls, and complete working snippets with proper syntax. | 3 / 3 |
Workflow Clarity | Clear 5-step workflow with explicit validation checkpoints including assertions for row counts, null checks, and column verification. The workflow includes feedback loops (validate results, then optimize) appropriate for data transformation tasks. | 3 / 3 |
Progressive Disclosure | Well-structured with a clear reference table pointing to one-level-deep topic files. The main skill provides quick patterns while detailed guidance is appropriately delegated to reference files with clear 'Load When' guidance. | 3 / 3 |
Total | 12 / 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
- jeffallan/claude-skills
- Commit
5b76101
- Reviewed
Table of Contents
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