Content
92%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 a well-structured, highly actionable audit process: a clear sequenced workflow with validation checkpoints and a pre-delivery checklist, supported by well-signaled one-level-deep reference files that all exist. The only minor gap is conciseness, where a recap checklist and the inline worked-example block add some redundancy.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense procedural guidance that assumes Claude's competence (it does not re-explain UX, WCAG, or library basics), but the closing "Quality bar" section recapitulates several earlier points and the full worked-example markdown block adds length that could be trimmed, keeping it just short of fully lean. | 4 / 5 |
Actionability | For an instruction-only skill the guidance is highly actionable: concrete evidence-recording formats (`location -> user action or condition -> observed response -> consequence`), an evidence register schema, a journey-map pattern, an exact severity scale (S0-S3 + Opportunity), and a copy-paste-ready finding template with a worked example. | 5 / 5 |
Workflow Clarity | A clear 9-step sequence (Frame, Evidence map, Trace, Lenses, Validate, Synthesize, Calibrate, Recommend, Report) is paired with explicit validation checkpoints (state assumptions, label evidence quality, "Needs verification" handling) and a pre-delivery "Quality bar" checklist; the destructive/batch cap does not apply since this is a read-only diagnostic skill. | 5 / 5 |
Progressive Disclosure | SKILL.md is a clear overview that signals eight one-level-deep reference files, each with conditional reading guidance (e.g. "Read [references/ai-experience.md] only when AI ... affects the experience"), and all referenced paths resolve to real files in ./references/ with no nested references. | 5 / 5 |
Total | 19 / 20 Passed |