<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->

PM Skill Auditor (Dispatch Skill)

Cross-client dispatch wrapper for the pm-skill-auditor sub-agent. Detects runtime; dispatches to the native sub-agent on Claude Code; reads subagents/pm-skill-auditor.md and executes inline on non-Claude clients.

When to Use

• You need a repo-wide audit pass: all enforcing validators, cross-cutting checks (skill-without-command, sample gaps, family contract orphans, etc.), and aggregate counter re-derivation against declared values in CONTEXT.md + AGENTS.md + README.md
• You are running on a non-Claude AI client without native pm-skill-auditor sub-agent support
• You are running on Claude Code and prefer skill-invocation semantics (e.g., for chaining inside a workflow that also uses other dispatch skills)

When NOT to Use

• You want to review a specific PM artifact (PRD, OKR, persona) -> use utility-pm-critic instead
• You want to draft a CHANGELOG entry -> use utility-pm-changelog-curator (ships in Phase 4)
• You want to ship a release -> use utility-pm-release-conductor (ships in Phase 5)
• You want to FIX issues found in an audit -> the auditor is detection-only; remediation is maintainer judgment or future pm-frontmatter-doctor (v2.17+)

Instructions

Runtime detection step. Determine which AI client is invoking this skill.

If you are running in Claude Code with the pm-skills plugin installed

Invoke @agent-pm-skill-auditor on the repo. Pass any scope arguments from $ARGUMENTS (e.g., --scope changed, --since-tag v2.15.0, --severity-floor P1). Return the sub-agent's audit report to the user.

If you are running in any other AI client

Codex CLI, Cursor, Windsurf, Copilot, Gemini CLI, or any other client without native pm-skills plugin sub-agent support:

1. Read the canonical sub-agent definition at subagents/pm-skill-auditor.md
2. Execute the system prompt body in that file as your operating instructions for this turn
3. Run the four-step audit flow:
   • Step 1: Invoke validators via Bash (prefer bash scripts/pre-tag-validate.sh as canonical entry point)
   • Step 2: Run cross-cutting checks from the catalog at docs/internal/release-plans/v2.16.0/spec_pm-skill-auditor.md#cross-cutting-check-catalog
   • Step 3: Re-derive aggregate counters from filesystem and compare to declared values
   • Step 4: Compose layered output report
4. Apply scope and severity-floor arguments from $ARGUMENTS
5. Return the layered output per master plan D26 (full report + Status Summary + Status YAML)

Cross-Client Notes

See Sub-Agent Compatibility Matrix for the canonical cross-client status. Summary for this skill as of v2.16.0: PRODUCTION on Claude Code + Codex CLI (Codex CLI successfully invoked the validator suite via Bash + produced a layered audit report with re-derived aggregate counters); EXPERIMENTAL on Cursor / Windsurf / Copilot CLI / Gemini CLI.

The "read canonical agent definition and execute inline" pattern depends on the AI client being able to:

1. Read a referenced file path
2. Execute Bash to invoke validator scripts
3. Treat the agent definition body as operating instructions for the current turn

Most AI clients support all three. If any are unreliable on a specific client, that client falls back to manual validator invocation + manual cross-cutting checks.

Reference Files

• Canonical sub-agent definition: subagents/pm-skill-auditor.md
• Behavioral spec: docs/internal/release-plans/v2.16.0/spec_pm-skill-auditor.md
• Runtime components catalog: docs/reference/runtime-components.md
• Cross-cutting check catalog: docs/internal/release-plans/v2.16.0/spec_pm-skill-auditor.md#cross-cutting-check-catalog
• Pre-tag validator bundle: scripts/pre-tag-validate.{sh,ps1}
• Output template: references/TEMPLATE.md
• Worked example: references/EXAMPLE.md