Content
86%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 well-structured, actionable skill body with executable SQL/bash/python, a clear multi-step workflow with idempotency and QMD feedback loops, and clean one-level-deep reference splitting. Slight conciseness and explicit-vault-write-validation gains keep it from a perfect score.
Suggestions
Consolidate the 'Key data sources ranked by value' list with the three Source sections to remove overlap and tighten token use.
Add an explicit validate-then-proceed checkpoint after Step 5 (e.g., verify each new/updated page renders and its summary frontmatter is present) before updating the manifest in Step 6.
Tighten the Step 1 survey comments — several inline comments repeat info already given in the GitHub Copilot Data Layout section.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Largely lean — directory trees, SQL, and tables assume Claude's competence with little concept padding — though the ranked-by-value list and data-layout section carry some redundancy that could be tightened. | 4 / 5 |
Actionability | Fully executable guidance: concrete SQL queries with schemas, bash scan snippets, a python base64 decoder, and a precise what-goes-where mapping table; placeholder paths are appropriately parameterized rather than pseudocode. | 5 / 5 |
Workflow Clarity | Clear Step 1–6 sequence with idempotency (manifest delta check), append/full modes, and explicit QMD-refresh verification feedback loop; vault-write validation is largely implicit via the manifest rather than an explicit validate-then-proceed checkpoint, keeping it just below a 5. | 4 / 5 |
Progressive Disclosure | Body acts as an overview with a single clearly-signaled one-level-deep reference to the real file references/copilot-data-format.md (cited inline and in a Reference section); detailed data format is correctly deferred. | 5 / 5 |
Total | 18 / 20 Passed |