Content
76%Weight 40%Scale 1-5Reviews 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 lean, executable code and clear section structure, but lacks validation checkpoints for its batch and destructive-handling steps, which caps workflow clarity.
Suggestions
Add validation checkpoints after outlier detection (e.g. review outlier_ratio before acting) and before applying handle_outliers, especially for the destructive 'drop' method.
Add a brief error-recovery note for common failures (missing file, non-numeric data, empty columns) so the workflow has a feedback loop.
Consider splitting the boxplot visualization and handling-skeleton steps into reference files to keep the main SKILL.md closer to an overview.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is almost entirely executable code with brief section-label comments and no padding or explanations of concepts Claude already knows; a few inline comments merely narrate the following line and could be trimmed. | 4 / 5 |
Actionability | Steps 1–4 are fully executable, copy-paste-ready code covering load, IQR outlier detection, boxplot visualization, and skewness/kurtosis analysis, with the intentionally-labeled Step 5 skeleton clearly marked. | 5 / 5 |
Workflow Clarity | Steps are clearly sequenced 1–5, but the workflow loops over all numeric columns (batch) and includes a destructive handle_outliers skeleton (drop/cap) with no validation checkpoints or error-recovery guidance, capping workflow clarity at 3 per the batch/destructive guideline. | 3 / 5 |
Progressive Disclosure | Content is well-organized into five clearly headed Step sections with no nested references (and no bundle files exist); at ~148 lines it slightly exceeds the simple-skill threshold, so a couple of sections (visualization, handling) could optionally be split out, leaving minor organization gaps. | 4 / 5 |
Total | 16 / 20 Passed |