define-hypothesis
Defines a testable hypothesis with clear success metrics and a validation approach. Use when…
Run adversarial review on a PM artifact via the pm-critic sub-agent. Returns findings graded P0/P1/P2/P3 with a concrete fix suggestion per finding and a machine-readable status block. Use after producing a PRD, meeting recap, OKR set, persona, or any PM artifact you want
$ npx -y skills add product-on-purpose/pm-skills --skill utility-pm-critic --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/utility-pm-criticContext preview
The summary Claude sees to decide when to auto-load this skill.
Run adversarial review on a PM artifact via the pm-critic sub-agent. Returns findings graded P0/P1/P2/P3 with a concrete fix suggestion per finding and a machine-readable status block. Use after producing a PRD, meeting recap, OKR set, persona, or any PM artifact you want
name: utility-pm-critic description: Run adversarial review on a PM artifact via the pm-critic sub-agent. Returns findings graded P0/P1/P2/P3 with a concrete fix suggestion per finding and a machine-readable status block. Use after producing a PRD, meeting recap, OKR set, persona, or any PM artifact you want stress-tested before it ships. license: Apache-2.0 metadata: classification: utility version: "1.0.1" updated: 2026-06-10 category: review frameworks: [triple-diamond] author: product-on-purpose
<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->
This skill is a cross-client dispatch wrapper for the `pm-critic` sub-agent. It exists so that users on non-Claude clients can run adversarial review with the same intent as Claude Code users, without depending on native plugin sub-agent infrastructure.
Per master plan D11 (amended) + D30, sub-agents are a Claude Code plugin feature. Non-Claude clients (Codex CLI, Cursor, Windsurf, Copilot, Gemini CLI) cannot natively load `agents/pm-critic.md`. This skill bridges the gap.
**Runtime detection step.** Determine which AI client is invoking this skill.
Invoke `@agent-pm-skills:pm-critic` on the target artifact. Pass the artifact path as argument (or the most recent artifact in session context if no argument is provided). Return the sub-agent's findings to the user. No further action needed from this skill - the sub-agent handles the review natively in its own context window.
Codex CLI, Cursor, Windsurf, Copilot, Gemini CLI, ChatGPT, or any other client without native pm-skills plugin sub-agent support:
1. Read the canonical sub-agent definition at `agents/pm-critic.md` 2. Execute the system prompt body in that file as your operating instructions for this turn 3. Read the target PM artifact specified by the user (path from `$ARGUMENTS`, or most recently produced artifact in session) 4. Read the canonical standards docs referenced by the pm-critic system prompt for the artifact type (e.g., `skills/foundation-okr-writer/SKILL.md` for OKR sets, `skills/deliver-prd/SKILL.md` for PRDs) 5. Produce findings graded P0/P1/P2/P3 with concrete fix suggestions, formatted per the output structure documented in `docs/guides/adversarial-review.md` 6. End the output with the layered structure per master plan D26:
See `references/TEMPLATE.md` for the canonical output structure (with the layered Status envelope per D26). See `references/EXAMPLE.md` for a worked example showing a real cross-client dispatch run against a PRD.
See [Sub-Agent Compatibility Matrix](../../docs/reference/sub-agent-compatibility.md) for the canonical cross-client status of all 4 sub-agents + dispatch skills. Summary for this skill as of v2.16.0: PRODUCTION on Claude Code + Codex CLI; EXPERIMENTAL on Cursor / Windsurf / Copilot CLI / Gemini CLI. Maintainers wanting cross-client confidence on a non-Claude client can re-run the [`maintainer-gate-testing-codex.md`](../../docs/internal/release-plans/v2.16.0/maintainer-gate-testing-codex.md) harness on that client.
The "read and execute inline" pattern depends on the AI being able to:
1. Read a file path provided as a reference (most AI clients support this) 2. Treat that file's content as operating instructions for the current turn (most AI clients support this for SKILL.md-style instructions) 3. Read additional referenced standards docs at invocation time (all major AI clients support this)
If any of these are unreliable on a given client, that client cannot use this dispatch skill effectively.
68 plug-and-play, best-practice product management skills for AI agents: 30 Triple Diamond phase + 11 foundation + 12 utility + 15 tool (Foundation Sprint + Design Sprint). Plus 6 sub-agents, workflows, 200+ output samples, guides, and CI-enforced contracts. Apache 2.0.
Repo: product-on-purpose/pm-skills
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