Content
78%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.
A concise, well-structured analytical workflow that assumes Claude's competence and organizes content cleanly. Its main weakness is actionability: it gives process structure but few executable specifics or concrete computational definitions.
Suggestions
Add a small copy-paste code snippet (e.g., loading JSON/CSV result files and computing mean+/-std and delta-vs-baseline) so the analysis is executable rather than purely descriptive.
Concretize underspecified guidance: define 'delta vs baseline' (relative % vs absolute) and what 'check reproducibility' entails (e.g., a std/mean threshold across seeds).
Insert an explicit validation checkpoint early in the workflow (e.g., 'Verify every result file parsed successfully before building the comparison table; re-inspect any that failed') to add a clear feedback loop.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and directive throughout ('Always compute relative improvement', 'Flag outliers or suspicious results') with no padding of concepts Claude already knows; every line earns its place. | 5 / 5 |
Actionability | Provides concrete structural guidance (the Observation/Interpretation/Implication/Next step framework, variable categorization) but no executable code or commands, and key details are underspecified (what 'delta vs baseline' or 'check reproducibility' mean concretely). | 3 / 5 |
Workflow Clarity | A clear five-step sequence (Locate -> Build Table -> Statistical Analysis -> Generate Insights -> Update Documentation) with verification steps ('Flag outliers', 'check reproducibility'), but no explicit validate-then-proceed feedback loop. | 4 / 5 |
Progressive Disclosure | Under 50 lines with no need for external references and well-organized into Workflow/Output Format sections, meeting the simple-skill exception for top marks. | 5 / 5 |
Total | 17 / 20 Passed |