Content
37%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is concise but lacks substance. It reads more like a job description than actionable guidance, providing no concrete instructions, code examples, or workflows for performing data analysis tasks. The skill needs significant expansion with executable examples and clear processes.
Suggestions
Add concrete code examples for common analysis tasks (e.g., pandas snippets for statistical analysis, visualization code with matplotlib/seaborn)
Define a clear workflow for creating analysis reports with validation steps (e.g., data validation -> analysis -> review -> output)
Include specific templates or examples of expected report formats and dashboard structures
Add references to detailed guides for each responsibility area (e.g., VISUALIZATION.md, REPORT_TEMPLATE.md)
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is extremely brief and doesn't explain concepts Claude already knows. Every line serves a purpose without padding or unnecessary context. | 3 / 3 |
Actionability | The skill provides only vague role descriptions and task categories without any concrete code, commands, specific examples, or executable guidance for performing data analysis tasks. | 1 / 3 |
Workflow Clarity | No workflow steps are defined. The skill lists responsibilities but provides no sequence, process, or validation checkpoints for how to actually perform data analysis or create reports. | 1 / 3 |
Progressive Disclosure | The content is well-organized with clear sections and mentions output locations, but provides no references to detailed materials, examples, or templates that would help with the listed tasks. | 2 / 3 |
Total | 7 / 12 Passed |