The body is lean and assumes Claude's competence — it never explains what a session or a tool failure is — and each section (steps, examples, pitfalls, limitations) earns its place without padding.

It provides concrete, copy-paste-ready commands throughout (e.g. `agenttrace --doctor`, `agenttrace --overview -f markdown -o agenttrace-overview.md`, threshold flags), fully executable rather than pseudocode.

The five steps are clearly sequenced with explicit checkpoints — Step 1's `--doctor` discovery and 'if no sessions are detected' fallback, plus the Common Pitfalls error-recovery guidance — and the work is read-only so the destructive-operation cap does not apply.

No bundle files exist, so scoring reflects organization: the single SKILL.md is well-sectioned (Overview, When to Use, How It Works, Examples, Best Practices, Limitations, Pitfalls) with no nested references and easy navigation.

The description lists multiple concrete actions — "cost, tool failures, latency, anomalies, health, diffs, and CI gates" — rather than vague language, matching the 'lists multiple specific concrete actions' anchor.

It clearly states what the skill does but lacks any 'Use when...' clause or equivalent explicit trigger guidance, so per the guidelines completeness is capped at 2 rather than reaching the 'both what AND when' anchor.

It covers natural audit-domain terms a user would say — "cost", "tool failures", "latency", "diffs", "CI gates" — alongside the tool name, giving good coverage rather than only technical jargon.

The niche is clear and specific — auditing local AI coding-agent sessions with agenttrace — making it unlikely to trigger for the wrong skill.