Content
21%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is extremely verbose and poorly structured, reading more like a product specification document or medical reference guide than an actionable skill for Claude. The massive inline example report (~200 lines) dominates the file and should be a separate template. The actual workflow guidance is thin and lacks validation steps, while the content extensively explains sleep medicine concepts Claude already knows.
Suggestions
Extract the example report template, algorithm code, and data schemas into separate bundle files (e.g., REPORT_TEMPLATE.md, algorithms.py, DATA_SCHEMA.md) and reference them from a concise SKILL.md overview.
Remove explanations of sleep medicine concepts (PSQI, STOP-BANG, CBT-I, sleep stages) that Claude already knows—focus only on project-specific scoring thresholds and data mappings.
Add explicit validation checkpoints to the workflow: validate data completeness before analysis, verify statistical significance before making recommendations, and check for minimum sample sizes.
Make the algorithm code fully executable by implementing the helper functions (time_to_minutes_std, align_data_with_lag, is_weekday) or replace with complete, runnable code.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose at ~500+ lines. The vast majority is an example report output that doesn't teach Claude how to perform the skill—it's a massive template that could be a separate file. Extensive explanations of sleep medicine concepts (PSQI, STOP-BANG, CBT-I) that Claude already knows. The skill describes what to analyze rather than how to do it concisely. | 1 / 5 |
Actionability | Provides Python code for scoring algorithms and references specific data file paths, which is concrete. However, the code is semi-pseudocode (references undefined helper functions like `time_to_minutes_std`, `align_data_with_lag`, `is_weekday`). The massive example report is illustrative but not executable guidance—it shows desired output format rather than actionable steps for producing it. | 3 / 5 |
Workflow Clarity | Steps 1-4 provide a rough sequence (determine scope → read data → analyze → generate report) but are vaguely defined with no validation checkpoints. There's no feedback loop for data quality issues, missing records, or error handling. For a skill involving statistical analysis and health-related recommendations, the absence of data validation steps is a significant gap. | 2 / 5 |
Progressive Disclosure | Monolithic wall of text with everything inlined—the ~200-line example report, all algorithm code, data structures, medical disclaimers, and reference links are all in one file. No bundle files exist to offload content to. The example report template, algorithm implementations, and data schemas should clearly be in separate referenced files. | 1 / 5 |
Total | 7 / 20 Passed |