Content
100%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.
The body is lean, executable, and well-structured: a complete worked example, concrete output format, an anti-pattern table, and a single well-signaled reference file. Validation feedback loops are present despite batch generation.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean body that assumes Claude's competence — no padding explaining what tests, HTTP status codes, or libraries are; the category list and code examples each earn their tokens. | 5 / 5 |
Actionability | Provides a fully executable, copy-paste-ready worked example with real pytest code, parametrize tables asserting specific status codes and structured error fields, plus a concrete output-format spec and an anti-pattern fix table. | 5 / 5 |
Workflow Clarity | Sequences the work with a run → interpret → commit feedback loop ('Any failure indicates a real gap') and explicit handling of skipped categories; validation checkpoints are present for this batch-generating skill. | 5 / 5 |
Progressive Disclosure | SKILL.md is a clear overview that points one level deep to the verified, well-signaled references/negative-path-catalog.md; detail is appropriately split rather than inlined. | 5 / 5 |
Total | 20 / 20 Passed |