Content
92%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 SKILL.md body is a lean, highly actionable, well-sequenced evaluation workflow with concrete commands and verification checkpoints throughout. Its only real gap is progressive disclosure: it ships reference files that are never linked or signaled from the body.
Suggestions
Link the existing bundle files from the body — e.g., in the scoring section add 'See [evaluation-protocol.md](references/evaluation-protocol.md) for the full black-box/white-box scoring criteria' and '[regression-protocol.md](references/regression-protocol.md) for regression triage' — so the reference files are discoverable.
Consider moving the detailed scoring matrix and token-extraction formulas into the referenced protocols and keeping the body as an overview, to better match the progressive-disclosure intent.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and actionable with no padding explaining concepts Claude already knows (MCP, Home Assistant, git diff); nearly every token earns its place in commands, YAML formats, and scoring matrices. | 3 / 3 |
Actionability | Provides fully executable bash commands, complete Python snippets for token extraction, an exact custom-story YAML template, and a concrete scoring matrix — copy-paste ready with specific file paths and flags. | 3 / 3 |
Workflow Clarity | Steps 0–8 are explicitly ordered ('Follow these steps IN ORDER. Do not skip steps') with verification checkpoints after each story ('ALWAYS verify ... before running the next') and feedback loops for regressions (re-run to check flakiness, white-box analysis). | 3 / 3 |
Progressive Disclosure | Bundle files exist (references/evaluation-protocol.md, references/regression-protocol.md) but the body never signals or links to them, leaving them orphaned; relevant protocol detail is either inline or unreachable rather than cleanly split with one-level-deep navigation. | 2 / 3 |
Total | 11 / 12 Passed |