When the governance machinery itself (the rules, skills, and audit gates that keep a governed codebase honest, plus their wiring surfaces) needs a structural-integrity review, run this skill. It is the periodic guard-rail review: a judgment-based pass over the machinery for overlap (two rules or gates covering the same ground), gap (a stated discipline no gate enforces, a recurring failure mode no rule names), and drift (a rule, skill, or gate whose intent has diverged across its wiring surfaces in a way the mechanical parity gates cannot detect, because they check identity and count, not meaning). Maintainer-triggered, and auto-prompted after any PR that adds, removes, or renames a rule, skill, or gate. Catches the architectural erosion the per-PR and corpus-content sweeps are not built to see. Slash command `/guardrails`.
Composes a CHANGELOG entry (substantive or terse form) for a PR. Use when about to commit, open a PR, or finalize a change. Every PR carries an entry, even if terse; there is no skip path. The entry's required parts (date-and-version header, structured Keep a Changelog sections for substantive entries, file references as markdown links, the "why" not just the "what", verification evidence, phase context) are walked step by step so an entry that would fail the link-coverage gate, the version-monotonicity audit, or the D1 delta gate is caught at the draft stage rather than at CI.
Maintainer-invoked, rare-cadence whole-project deep assessment. Runs the full layered examination of the library and its own quality machinery from a fresh session, composing the existing semantic instruments (/validate, /full-qa, /fitness, /matrix-fit, /claim-fit, /reference-audit, /screen-publications, /guardrails) by invocation and adding the lenses the routine cadence does not apply to itself, gate-efficacy probing (mutation and blind-spot analysis), ground-truth citation sampling, adoptability and pipeline-integrity review, and a QA-ledger meta-audit. Multi-session and re-entrant: a durable register carries phase state across session boundaries, every confirmed finding is routed tiered with none dropped, and the pass terminates only on explicit maintainer sign-off, never on an empty finding set.
Trust-recovery deep quality-assurance pass. A six-subagent forensic review specialized for AI-failure-pattern classes, run over a defined PR window plus the files those PRs reference, when an AI coding assistant's discipline failures (abbreviated QA, skipped post-commit audits, wrong-cadence timers, inferred-not-validated premises) call for a white-box re-examination beyond the routine per-PR and periodic sweeps. Slash command `/full-qa`. Pairs with `library-fitness-review` (`/fitness`): deep-qa-review is one deeply-contextualized lens tuned to how AI assistants fail; fitness is ten context-stripped persona lenses. Together they form the trust-recovery escalation tier. Findings route to the project backlog tiered by severity (High[critical]/High to the top-priority tier, Medium/Low to the next tier), none dropped, for maintainer triage; the pass terminates on explicit maintainer sign-off, not on an empty finding-set.
Trigger a comprehensive whole-corpus library-fitness review with ten persona reviewers when a governance/security documentation library undergoes a major change (new domain dir, new document type, multiple governance rule additions, major restructure) or quarterly minimum. Each invocation dispatches a fan-out of independent persona subagents (executive, security practitioner, GRC practitioner, auditor, policy editor, process owner, skeptical reader, adoption practitioner, privacy officer, newcomer) who review every page from a fresh-reader perspective without inheriting maintainer mental models. Catches comprehensibility, usability, logical-structure, standardization, governance/security quality, auditability, maintainability, and reader-experience gaps that per-PR validation sweeps and mechanical audit gates do not detect. Surfaces prioritized recommendations and a discrete remediation backlog the maintainer drives through subsequent PRs.
Post-merge retrospective on each successful PR. Surfaces what went well, what caused friction, recurring patterns, and proposed improvements. Output is one entry per PR in the improvement-log register; recurring patterns become candidates for pack-rule updates, worker-brief template additions, or new audit gates. Invoke after `/validate-pr` returns and before the next-PR planning step.
Cadenced citation-precision audit of normative-attribution claims. Catches the gate-blind FR-120 class, "attributed value, silent source": a sentence ties a specific value (a retention period, a clock, a threshold) to a named normative source, the source exists and the citation is well-formed (so the existence and citation gates pass), but the source does not actually prescribe the attributed value. Run the one-time full Tier-A pass at adoption, then ad-hoc when a claim is in doubt and after any batch that adds or edits normative-value claims. It dispatches a semantic judge over the tiered worklist that `tools/audit-claim-precision.py` produces, adjudicating each claim against the held source TEXT in the reference base, then routes confirmed misattributions. It catches what the existence gates structurally cannot: claim precision needs a read of the source clause, not a source-exists check.
Cadenced semantic-fit audit of the compliance matrix and per-document framework-alignment tables. Catches the gate-blind "valid code, wrong control" class: a control identifier that EXISTS in its catalogue (so the existence gates 48/49/54/58/61 pass it) but is the WRONG control for the row's document. Run after each FR-167 matrix-expansion batch, once at matrix completion, and ad-hoc when a control-code citation is in doubt. It dispatches a semantic judge over the recall-oriented worklist that `tools/audit-matrix-semantic-fit.py` produces, adjudicating each cited code against the source control TITLE in the reference base, then routes confirmed mismatches. It catches what the existence-and-membership gates structurally cannot: semantic fit needs a read of the source title, not a catalogue-membership check.