Content
65%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is highly actionable with concrete executable code, commands, and a clear 8-step workflow, but it is verbose and duplicates reference-level detail inline in SKILL.md. Tightening the overview and moving concept explanations into the existing reference files would improve both conciseness and progressive disclosure.
Suggestions
Trim the concept-explanation prose (e.g., the 'Why Cointegration Matters' bullets, correlation/p-value/z-score interpretation tables) since Claude already knows these; keep only the project-specific thresholds.
Move the detailed statistical methodology and interpretation tables into references/methodology.md and references/cointegration_guide.md, leaving SKILL.md a lean overview that points to them.
Add explicit validate->fix->retry feedback loops for the batch screening and data-validation steps (e.g., 'if data validation fails, re-fetch missing symbols and re-check') to lift workflow clarity.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The ~620-line body restates concepts Claude already knows (what pair trading is, what correlation vs cointegration mean, beta's role) and includes textbook interpretation tables, so it is mostly efficient with a concrete core but padded with unnecessary explanation. | 2 / 3 |
Actionability | Provides fully executable, copy-paste-ready material: a real FMP API endpoint, runnable bash commands for the bundled scripts, real Python (statsmodels adfuller), explicit formulas, and concrete parameter/output schemas. | 3 / 3 |
Workflow Clarity | The 8-step sequence with objectives and validation criteria is clear, but this is a batch screening operation without explicit validate->fix->retry feedback loops, which caps workflow clarity at 2 per the batch-operations guideline. | 2 / 3 |
Progressive Disclosure | Real one-level-deep bundle files (references/methodology.md, references/cointegration_guide.md, scripts/find_pairs.py, scripts/analyze_spread.py) are clearly signaled, but detailed methodology that belongs in those references is duplicated inline, making SKILL.md partially monolithic rather than a lean overview. | 2 / 3 |
Total | 9 / 12 Passed |