Conciseness

Lean throughout: the motivation is six lines that establish "The rule: when a question is about something that already happened, read the trace before answering", and everything else is a runnable command block, a two-row table, terse hard rules ("No trace, no answer.", "Exit 0 of a compound line is the last command's."), and a compact scripts table. It assumes Claude's competence and explains nothing the model already knows, matching the lean-and-efficient anchor rather than the minor-over-explanation level of 4.

Actionability

Fully executable, copy-paste-ready commands with real flags: "python scripts/trace_finder.py --since 7d --touched config.yaml", "python scripts/trace_timeline.py --trace <path> --files", "--why 9", and "python scripts/claim_checker.py --trace <path> --claim "passed:pytest" --claim "not-edited:config.yaml"", plus per-script exit codes and universal --help/--sample/--output json. Concrete examples cover the common cases, matching the 5 anchor.

Workflow Clarity

The workflow is a numbered 4-step sequence with per-step comments, and validation is explicit and exit-code-driven: finder exit 2 → "say the run is not recorded here. Do not reconstruct it", claim checker "Exit 4 is a contradiction: correct the account first", and "STALE means the tests passed but files changed afterwards" as an error-recovery loop. This is a read-only skill, so the destructive/batch cap does not apply, and checkpoints are explicit rather than merely present as at level 4.

Progressive Disclosure

The body is a true overview (workflow, rules, scripts table) pointing to five clearly labeled, one-level-deep files — references/trace_sources.md, references/recorded_vs_inferred.md, references/claim_verification.md, assets/forensic_answer_template.md, assets/claims_example.txt — each with a one-line description and token count, and all five exist in the bundle with no nested references inside them. This matches the well-signaled one-level-deep anchor; the only adjacent consideration is the parenthetical mention of the plugin's hooks/forensics_hint.py, which is described as plugin behavior rather than offered as a reading reference.

Specificity

Lists several specific capability areas — "why an agent did something", "what a past session or run changed", "whether tests really passed", "verify a session summary" — and grounds them in a concrete mechanism ("Answers from the recorded transcript, not memory, with trace_finder.py, trace_timeline.py and claim_checker.py"). Falls short of 5 because the actions are framed as question types and tool names rather than a comprehensive set of explicit verbs (find runs, build a timeline, check claims are only implied).

Completeness

Explicitly answers both halves: "Answers from the recorded transcript, not memory, with trace_finder.py, trace_timeline.py and claim_checker.py" (what) and "Use when asked why an agent did something..." with four concrete trigger phrases (when). This matches the 5 anchor — clear what AND when with concrete triggers — rather than 4, where the 'when' would be less explicit.

Trigger Term Quality

Natural user phrasings are well covered: "why an agent did something", "whether tests really passed", "verify a session summary", "past session or run", "transcript". A few natural synonyms users might say are missing (e.g., "history", "chat log", "what did you do yesterday", "audit"), so it does not reach the comprehensive-with-synonyms level of 5.

Distinctiveness Conflict Risk

Clear niche — forensics over already-recorded agent runs — with distinct triggers ("whether tests really passed", "verify a session summary") that would not naturally fire a code-analysis or forward-planning skill. Minimal conflict risk; the frontmatter even enumerates adjacent skills it differs from.