Content
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is well-structured and domain-rich with concrete thresholds and tool parameters, but it lacks executable code examples, explicit validation checkpoints in its workflow, and any progressive disclosure to separate reference files.
Suggestions
Add an explicit validation step to the workflow, e.g. 'Verify the factor CSV and return CSV share identical dates/codes before calling factor_analysis; if misaligned, re-align and retry.'
Replace the pseudocode combination formulas with a short executable pandas/numpy snippet (cross-sectional Z-score, IC-weighted sum) so guidance is copy-paste ready.
Move the detailed Common Pitfalls and Factor Combination Methods into separate reference files (e.g. PITFALLS.md, COMBINATION.md) referenced one level deep from SKILL.md to improve progressive disclosure.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is information-dense and avoids explaining concepts Claude already knows, but the interpretation tables and Common Pitfalls sections are verbose and could be tightened without losing clarity. | 2 / 3 |
Actionability | It gives concrete tool parameters, IC/IR thresholds, and combination formulas, but the combination sections are pseudocode/math rather than executable code and the workflow never shows copy-paste-ready code. | 2 / 3 |
Workflow Clarity | The five-step workflow is clearly sequenced, but there is no explicit validation/verification checkpoint or fix-and-retry loop, which caps workflow clarity at 2 for a batch analytical operation. | 2 / 3 |
Progressive Disclosure | The single file is well-organized into clear sections, but no bundle files exist and detailed material (pitfalls, combination methods) that could live in one-level-deep references is all inline. | 2 / 3 |
Total | 8 / 12 Passed |