Content
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-structured, token-efficient skill body: an executable gate script, concrete schemas, a sequenced five-step workflow with validation/feedback signals, and a single genuine one-level reference for the heavier detail. It avoids re-teaching concepts Claude already knows.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean: it never explains what WCAG/axe-core are, jumps straight into the unified record, baseline, gate decision, and artifact, and every section earns its tokens. It is tighter than the level-2 anchor that pads with unnecessary library justification. | 3 / 3 |
Actionability | Provides a fully executable `run_a11y_gate.py` with real imports, concrete JSON schemas for the unified record and baseline, and a copy-paste-ready severity-tier table — matching the 'fully executable code/commands; copy-paste ready' anchor. | 3 / 3 |
Workflow Clarity | Steps 1–5 are clearly sequenced with the gate's exit code (`sys.exit(0 if verdict == 'go' else 1)`) as an explicit checkpoint, and Step 5's baseline-maintenance workflow gives error-recovery guidance ('Manually remove the fingerprint... otherwise the baseline accumulates stale entries'). This exceeds the level-2 anchor's missing-checkpoint case. | 3 / 3 |
Progressive Disclosure | The core runnable gate lives inline while per-scanner shapes and the full PR-artifact template are split into a single, clearly signaled, one-level-deep reference (`references/gate-implementation.md`, confirmed to exist), matching the 'clear overview with well-signaled one-level-deep references' anchor. | 3 / 3 |
Total | 12 / 12 Passed |