Conciseness

Mostly operational with no filler or explanations of known concepts, but it could be tightened: the ~30-line FTS tokenizer/measurement bullets (row counts like "10 rows against 163 substring occurrences", "measured 26s against 0.03s"), the date-stamped "Pitfalls measured 2026-10-03" block, and the dense single-paragraph prompt_cursor contract are inline detail that belongs in reference files. It is above the score-2 anchor (no padded or unnecessary concept explanations) but clearly below score-4 because multiple sections carry measurement trivia and time-sensitive specifics that tax the context budget.

Actionability

Every route ends in a copy-paste-ready invocation with concrete flags (e.g. `read_codex_session.py --session <ID> --tools --contains '<literal clue>' --format json`, `analyze_sessions.py locate-codex <ID>`) and the SQL for the runtime log is complete and executable. The `<skill-dir>` placeholders are explicitly resolved by the instruction "Resolve scripts relative to this SKILL.md", matching the score-5 anchor of fully executable commands covering common cases.

Workflow Clarity

Workflows are explicitly sequenced with validation checkpoints and feedback loops: candidate selection → identity verification → "Stop once the quote and identity are verified" → "If a candidate misses, try the remaining plausible candidates"; a numbered 3-step identity/lineage gate; and a 5-item read-result contract checklist. Error handling is prescribed throughout (exit 2 / `complete: false` as incomplete, briefing safety-limit failures, zero-row scoping), matching the score-5 anchor including checklists and recovery loops.

Progressive Disclosure

Structure is good: four real reference files one level deep, each clearly signaled with a purpose statement ("Read [storage_and_portability.md] for source discovery, timestamps, writer-lock semantics..."), verified anchor links, and a route-by-result table for navigation. It is not score-5 because a substantial amount of deep material (the FTS index constraints section, the runtime-log SQL and pitfalls, the prompt_cursor contract) is inlined in SKILL.md rather than split out, which is the score-4 anchor's 'minor organization gaps'.

Specificity

The description enumerates concrete capabilities — "session inventory, timelines, verbatim user input, indexed search, and rollout identity/fork lineage" — plus the read-only boundary ("without continuing work"), comprehensively covering the skill's surfaces in third person. It exceeds the score-4 anchor ('several specific actions; minor gaps') because no capability area of the skill is left unrepresented.

Completeness

Both questions are explicitly answered: the "what" opens with the enumerated actions, and the "when" is a concrete 'Use when' clause listing three trigger scenarios. It matches the score-5 example structure exactly and additionally supplies boundary routing, so it cannot be the score-4 anchor ('when' could be more explicit).

Trigger Term Quality

Natural user phrasing is present — "what they told Codex", "wants a Session ID", "evidence of what a run did", "Codex history" — which users would genuinely say. It falls short of the score-5 anchor because common synonyms and variations like "transcript", "past conversation", "chat log", or file-format terms are absent.

Distinctiveness Conflict Risk

The niche is unambiguous (local OpenAI Codex history, read-only) and it actively de-conflicts the two nearest sibling skills: "Not for Claude Code (use read-claude-code-history); with no platform named, start at local-conversation-history". This explicit routing gives minimal conflict risk, matching the score-5 anchor.