Content
87%Weight 40%Scale 1-3Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is a tight, highly actionable playbook with strong conciseness, concrete tooling, and clean sectioning; its main gap is the absence of an explicit validation/verification checkpoint in the batch sweep workflow.
Suggestions
Insert an explicit validation step in the workflow, e.g., "5b. Verify each shard returned and that promoted candidates have path+line+score before kg_add_candidate," to add a feedback loop for the batch operation.
Add a one-line guardrail confirming shard coverage (e.g., "confirm sum of shard file counts matches the wc -l estimate") so a dropped shard is caught before ranking.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and punchy — short operating principles, a compact decision table, and a terse workflow — and it never explains concepts Claude already knows (e.g., what grep or a sink is), so every token earns its place. | 3 / 3 |
Actionability | It gives fully concrete, executable guidance: named tools ("scan_shard", "rank_candidates", "kg_add_candidate"), specific shard counts (4/8/16), a file-count decision table, and a copy-pasteable numbered command workflow. | 3 / 3 |
Workflow Clarity | The six-step workflow is clearly sequenced and begins with sanity-check/sizing steps, but for a batch operation over 10^4–10^6 files it has no explicit validation checkpoint or feedback loop (e.g., verify shard outputs before ranking), capping it at 2. | 2 / 3 |
Progressive Disclosure | The skill is short and organized into well-labeled sections (Operating principles, Decision, Workflow, Sink kinds, What NOT to do) and defers the bulky regex table to a single one-level-deep reference ("decepticon/research/scanner_tools.py") rather than inlining it. | 3 / 3 |
Total | 11 / 12 Passed |