Content
77%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 well-structured, action-oriented body with an excellent validation workflow and clean progressive disclosure. The main weakness is the measurement justification prose carrying date-sensitive detail that does not earn its tokens.
Suggestions
Move the dated measurement narrative ('Measured on 2026-08-30/31...', probe counts) into references/SPEC.md or trim it to a single clause, so SKILL.md stays lean and date-free.
Add one short 'good vs. broken' Mermaid example pair (e.g. a label with unquoted parentheses) so the hazard list and the validate loop have a concrete anchor.
Tighten the Overview from two paragraphs to one sentence stating the goal, since the rules and steps already convey the motivation.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient and purposeful, but the measurement narrative ('Measured on 2026-08-30/31 over twelve agent-written diagrams', '43 synthetic probes') is time-sensitive justification prose that could be trimmed and is not placed in a deprecated section. | 3 / 5 |
Actionability | Provides a concrete, copy-paste-ready command ('python3 scripts/validate.py path/to/diagram.md') with exit-code semantics and diagram-type selection, but includes no example Mermaid block showing correct vs. fixed output. | 4 / 5 |
Workflow Clarity | A clear numbered sequence (pick type → read SPEC → write → run check → repair and re-check until clean) with an explicit validation checkpoint and a fix→re-run feedback loop, matching the anchor pattern exactly. | 5 / 5 |
Progressive Disclosure | SKILL.md is a concise overview that points one level deep to real, verified files (references/SPEC.md, scripts/validate.py), with both inline and Resources-section signaling for easy navigation. | 5 / 5 |
Total | 17 / 20 Passed |