Content
88%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 tight, information-dense methodology with a well-sequenced workflow, an explicit architectural test checklist, and a red-flags feedback loop. The main gap is the absence of a worked example and the lack of any reference/bundle split for a skill that is slightly long for a single file.
Suggestions
Add one short worked example (a speculative endpoint or unused export) traced through Steps 1–7 to make the procedure fully concrete.
Consider moving the Rationalization Guards table and Calibration examples into a references file, keeping SKILL.md as the overview, to improve progressive disclosure for the longer-than-50-line body.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and lean with no padding or explanation of concepts Claude already knows; every section (Principle, Workflow, Rationalization Guards, Red Flags, Calibration) earns its tokens and assumes the reader's competence. | 5 / 5 |
Actionability | It gives concrete procedural guidance — 'List every new surface and exact consumed dimension', a five-part architectural test with explicit criteria, classification taxonomies, and seven named decision outcomes — but provides no worked walkthrough applying the procedure to a realistic example. | 4 / 5 |
Workflow Clarity | A clearly sequenced seven-step workflow is backed by an explicit checklist (the five-part test) and a feedback loop ('Pause and restart from Step 1 when…' in Red Flags), with the 'Decide, then review implementation' step gating downstream work. | 5 / 5 |
Progressive Disclosure | The content is well organized under clear section headers and is self-contained with no nested references, but it is a single ~100-line file with no progressive-disclosure mechanism splitting detail into bundle files, so it sits just below the ideal. | 4 / 5 |
Total | 18 / 20 Passed |