Stakeholder Summary
testdouble/han
Produces a plain-language stakeholder summary from an existing feature specification, for sharing with non-technical stakeholders before implementation kicks off.
Produce a comprehensive, evidence-grounded prioritized action plan from any PM input (notes, transcripts, drafts, executive asks, Slack threads, or a raw situation).
$ npx skills add product-on-purpose/pm-skills --skill foundation-prioritized-action-plan -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install product-on-purpose/pm-skills foundation-prioritized-action-plan --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/product-on-purpose/pm-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/foundation-prioritized-action-plan .claude/skills/foundation-prioritized-action-plan && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "foundation-prioritized-action-plan" agent skill from https://github.com/product-on-purpose/pm-skills/tree/main/skills/foundation-prioritized-action-plan into .claude/skills/foundation-prioritized-action-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "foundation-prioritized-action-plan", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/product-on-purpose/pm-skills/tree/main/skills/foundation-prioritized-action-planType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add product-on-purpose/pm-skills --skill foundation-prioritized-action-plan -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install product-on-purpose/pm-skills foundation-prioritized-action-plan --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/product-on-purpose/pm-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/foundation-prioritized-action-plan .agents/skills/foundation-prioritized-action-plan && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "foundation-prioritized-action-plan" agent skill from https://github.com/product-on-purpose/pm-skills/tree/main/skills/foundation-prioritized-action-plan into .agents/skills/foundation-prioritized-action-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "foundation-prioritized-action-plan", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add product-on-purpose/pm-skills --skill foundation-prioritized-action-plan -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install product-on-purpose/pm-skills foundation-prioritized-action-plan --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/product-on-purpose/pm-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/foundation-prioritized-action-plan .cursor/skills/foundation-prioritized-action-plan && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "foundation-prioritized-action-plan" agent skill from https://github.com/product-on-purpose/pm-skills/tree/main/skills/foundation-prioritized-action-plan into .cursor/skills/foundation-prioritized-action-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "foundation-prioritized-action-plan", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/product-on-purpose/pm-skills.git --path skills/foundation-prioritized-action-plan--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add product-on-purpose/pm-skills --skill foundation-prioritized-action-plan -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install product-on-purpose/pm-skills foundation-prioritized-action-plan --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/product-on-purpose/pm-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/foundation-prioritized-action-plan .gemini/skills/foundation-prioritized-action-plan && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "foundation-prioritized-action-plan" agent skill from https://github.com/product-on-purpose/pm-skills/tree/main/skills/foundation-prioritized-action-plan into .gemini/skills/foundation-prioritized-action-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "foundation-prioritized-action-plan", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install product-on-purpose/pm-skills foundation-prioritized-action-planInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add product-on-purpose/pm-skills --skill foundation-prioritized-action-plan -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/product-on-purpose/pm-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/foundation-prioritized-action-plan .github/skills/foundation-prioritized-action-plan && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "foundation-prioritized-action-plan" agent skill from https://github.com/product-on-purpose/pm-skills/tree/main/skills/foundation-prioritized-action-plan into .github/skills/foundation-prioritized-action-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "foundation-prioritized-action-plan", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add product-on-purpose/pm-skills --skill foundation-prioritized-action-plan -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install product-on-purpose/pm-skills foundation-prioritized-action-plan --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/product-on-purpose/pm-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/foundation-prioritized-action-plan .opencode/skills/foundation-prioritized-action-plan && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "foundation-prioritized-action-plan" agent skill from https://github.com/product-on-purpose/pm-skills/tree/main/skills/foundation-prioritized-action-plan into .opencode/skills/foundation-prioritized-action-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "foundation-prioritized-action-plan", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
foundation-prioritized-action-planProduce a comprehensive, evidence-grounded prioritized action plan from any PM input (notes, transcripts, drafts, executive asks, Slack threads, or a raw situation).
Foundation Prioritized Action Plan is an agent skill from product-on-purpose/pm-skills. Produce a comprehensive, evidence-grounded prioritized action plan from any PM input (notes, transcripts, drafts, executive asks, Slack threads, or a raw situation). Outputs one saveable document with an executive summary, input mirror, situation classification (Cynefin), the binding constraint (Theory of Constraints), prioritized questions and open decisions, a ranked action plan with the critical effort plus follow-ons, risks and pre-mortem, copy/paste prompts for downstream pm-skills, and an evidence map…
Its SKILL.md is about 5.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 16 other files, including reference files (for example `HISTORY.md`, `eval/fixtures/cynefin-fixtures.md` and `eval/fixtures/rubric.md`).
It sits in Writing & Content, covering Summarization. It works with Slack. The repository describes itself as: 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… The licence is Apache-2.0.
9 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 1cef1a9. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Foundation Prioritized Action Plan loads about 5.8k tokens when it runs, and up to ~15k if it reads all its reference files. Until then it costs about 183 tokens; SKILL.md has 3,288 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from product-on-purpose/pm-skills at commit 1cef1a9, republished under its Apache-2.0 licence (© product-on-purpose). 3,288 words, ~5,801 tokens.
.claude/skills/foundation-prioritized-action-plan/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->
You produce a comprehensive, evidence-grounded action plan from PM input the user provides. Your job is to identify the critical next effort, sequence the follow-on efforts behind it, and equip the user with copy/paste prompts to execute. The plan is the deliverable; the prompts are an enabler.
utility-pm-workflow-orchestrator, which runs them behind its own per-step checkpoints (see "Handoff to the orchestrator")One constraint binds at any moment; everything else is noise until it is lifted. Theory of Constraints supplies the prioritization logic: find the single binding constraint, make the critical effort (P1) the one that lifts it. Cynefin supplies the confidence calibrator: how knowable the situation is caps how confident the plan may be.
Evidence is structural, not decorative. You build a source ledger of exact input quotes before writing any section, and every load-bearing claim cites a ledger entry. If you cannot cite, you cannot claim it as fact.
The skill is honest about what it does not know. In Complex or Chaotic situations it refuses to manufacture High-confidence multi-step plans: Complex situations get safe-to-fail probes, Chaotic situations get stabilization actions, both at capped confidence.
utility-pm-critic: if the user asks "is this artifact good, what is wrong with it," use utility-pm-critic. Use this skill when the user asks "what should I do next" with incomplete context. A half-baked draft is in scope here; a finished artifact awaiting critique is not.jp-strategy-brief (jp-library): if the user wants broad strategic exploration, option framing, or "help me think through this," use jp-strategy-brief. Use this skill only when the user wants a ranked next-action plan inside PM delivery work. If both libraries are installed and the ask is ambiguous, prefer jp-strategy-brief for exploration and this skill for committed execution sequencing.using-workflows: if the user wants a multi-skill workflow walkthrough, use using-workflows. This skill may point toward a workflow but hands off rather than reproducing it.define-prioritization-framework: if the user already has a defined candidate list of features or initiatives and wants formal RICE/ICE/MoSCoW/Kano scoring, use define-prioritization-framework. Use this skill when the input is a raw, unstructured situation and the user wants the single critical next effort, not a scored comparison across a list.| Framework | Role in the skill | Where it appears |
|---|---|---|
| Theory of Constraints (Goldratt) | Prioritization engine; identifies THE one binding constraint, which becomes the critical effort P1 | Step 3 (constraint) and Step 5 (plan ranking) |
| Cynefin (Snowden) | Situation classifier; caps plan confidence and shapes the posture (probes vs commitments vs stabilization) | Step 2 (classification) and confidence markers throughout |
Both frameworks are named in the output so the reasoning is auditable. A user can challenge any recommendation by asking "which constraint does this lift, and what evidence?" The one-page primer is in references/frameworks.md.
Required:
Optional, improves quality:
Input acquisition rules:
Inferred (Low confidence) and may NOT justify the binding constraint, P1, or any High-confidence marker. Do not invent or paraphrase-then-quote: ledger quotes must be exact substrings of the input.No source provided and treat the claim as a gap in the questions section, not as fact.Build the output by working these steps in order. The fill-in scaffold for every section lives in references/TEMPLATE.md; use it as the structural contract while you reason through each step here.
Before composing the document, extract a short ledger of exact quotes from the input. Render it as the document's opening block; it also feeds the evidence map in Section 8. Give each entry an ID (S1, S2, ...), the exact quote, and its origin (pasted text, or file path plus heading). Aim for 3 to 12 entries covering the load-bearing facts, or all of them if fewer than 3 exist; do not split one fact into artificial entries to hit a count. Every Source: field in the document references these IDs. If you want to cite something not in the ledger, either add it with an exact quote or mark the claim Inferred.
Reflect the input back so the user can confirm before the analysis carries weight: what they gave you (restated concisely), what they appear to be trying to accomplish (inferred intent, with a confidence level), and adjacent intents you noticed but did not assume.
State the domain and justify it with source-ledger citations, using these decision rules rather than classifying by input genre:
| Domain | Decision rule (how you know) | Plan posture | Confidence ceiling |
|---|---|---|---|
| Clear | Cause and effect obvious and undisputed; a known best practice applies | Apply best practice | High |
| Complicated | Cause and effect knowable with analysis or expertise; good practices exist | Analyze, then commit | Medium-High |
| Complex | Cause and effect only clear in hindsight; input shows conflicting signals, novelty, or unknown unknowns | Run safe-to-fail probes; instrument and sense | Medium-Low |
| Chaotic | No discernible cause and effect; active crisis or breakage in the input | Act to stabilize first, then re-assess | Low |
Distinguish Complicated from Complex by evidence, not topic: a problem is Complex when the input shows the outcome is genuinely unpredictable (new market, untested user behavior, conflicting data), not merely hard. If Complex, the plan MUST contain probes; if Chaotic, the plan MUST contain stabilization actions. Cite the passages that drove the classification.
Identify the ONE thing currently limiting progress. State the system and goal in one line (for example "ship an SMB plan that converts trials"); the constraint, named in plain language; the Source: ledger entries that evidence it; 1 to 2 candidate constraints considered and why they are downstream of or subordinate to this one; and the causal link from the chosen P1 effort to relieving this constraint. If the evidence for a single binding constraint is weak, call it the "primary planning bottleneck (low confidence)" rather than asserting a definitive constraint, flag it as the top gap in Section 4, and demote overall plan confidence one notch.
Rank the unknowns that block higher-confidence planning, merged with decisions only the user can make. Use a table of 3 to 7 entries with: rank, question or gap, why it matters, whether a user decision is required (and whether it blocks P1), and how to resolve it. The "Decision required?" column flags items that need a user call before the relevant effort can start.
This is the primary deliverable: exactly 3 to 5 efforts, ranked P1 (lifts the constraint) through P5 (sequenced behind). Each effort is a block with all eight fields:
Inferred (Low confidence)P1 gets the fullest treatment; P2 to P5 are shorter but keep all eight fields. P1 may NOT be Inferred: if you cannot source the binding constraint and P1, the situation is under-evidenced. Say so and make P1 a discovery effort. After the effort blocks, add a Now / Next / Later sequencing table mapping P1 to P5 to time horizons, and a "What to defer / what NOT to do" list of 2 to 4 explicit non-actions. Pre-committing to deferral is half the value of prioritization.
Assume the plan failed; what went wrong? List 3 to 5 risks, each with likelihood, impact, an early observable signal, a mitigation, and a Source: (ledger ID or Inferred). Generic risks are not acceptable: "the team may lack capacity" is generic; "design is committed to the Q3 redesign that lands the same week as P2 user research (S7)" is specific.
For each effort that maps to a recommendable downstream skill, provide a ready-to-run prompt with the user's context already filled in (skill name, why this skill, the source IDs that justify it, and the full prompt). Routing rules:
references/skill-catalog.md OR in the embedded exact-name Tier 1 list in references/recommendable-tiers.md. If you cannot confirm a skill's exact name from one of those sources, do NOT name a skill: describe the next step in plain language instead. Never invent or approximate a skill name.using-workflows; do not stitch together individual sub-step skills.Consolidate the source ledger and audit coverage in a table of claim or recommendation, source ID, and exact quote. List any load-bearing claim that is Inferred (Low confidence) and confirm none of them drive the binding constraint or P1. State evidence gaps honestly. This section is an audit of the inline sources, not the first place evidence appears.
Produce ONE markdown document. Open with the Step 0 source ledger (the evidence scaffolding built before analysis), then the nine numbered sections in order: 0 executive summary, 1 input mirror, 2 situation classification, 3 binding constraint, 4 prioritized questions and open decisions, 5 the action plan, 6 risks and pre-mortem, 7 recommended prompts, 8 evidence and source map. The executive summary is the first reader-facing section and the fast-skim layer. Use references/TEMPLATE.md as the fill-in scaffold; references/EXAMPLE.md is a fully worked sample.
Completeness is the priority: the executive summary (120 to 180 words, the first reader-facing section, directly below the Step 0 ledger) is the fast-skim layer for busy readers, and the rest is the complete artifact. Do not pad, but do not drop a section to save words. Per-section word targets are guidance; the per-tier hard max below is a real ceiling.
| Input complexity | Target (soft) | Hard max (backstop) |
|---|---|---|
| Simple (one clear thread, brief input) | 900 to 1,300 words | 1,500 |
| Medium (2 to 3 threads, moderate context) | 1,300 to 2,000 words | 2,200 |
| Complex (multiple threads, dense input) | 2,000 to 3,000 words | 3,000 |
If you must shorten, cut in this order: framework explanation, then the lowest-confidence Section 7 prompts, then compress prose. NEVER drop the evidence map (Section 8) or the pre-mortem (Section 6) to save words.
Section 7 may only recommend from this filtered set. The full enumerated lists with exact names live in references/recommendable-tiers.md.
foundation-persona, foundation-lean-canvas, foundation-okr-writer, foundation-stakeholder-update). This is the embedded fallback core.foundation-meeting-* (only for meeting next-steps); the Foundation Sprint and Design Sprint families (recommend the family entry point, or hand to using-workflows); utility-pm-critic (when the next step is reviewing an artifact); utility-mermaid-diagrams and utility-slideshow-creator (when the next step is visualizing or presenting).utility-pm-skill-builder, utility-pm-skill-auditor, utility-pm-skill-validate, utility-pm-skill-iterate, utility-pm-release-conductor, utility-pm-changelog-curator, utility-update-pm-skills (library machinery), and foundation-prioritized-action-plan itself.The build-time catalog generator emits Tier 1 and Tier 2 (with a conditional flag) and omits Tier 3. Skill names are read from frontmatter so they stay correct as the library evolves.
Inferred (Low confidence). Inferred claims may not drive the constraint or P1.--run) to utility-pm-workflow-orchestrator, which runs the steps behind its own checkpoints; you never execute a work-skill yourself.Chat output by default. Optional disk write to _pm-skills/foundation-prioritized-action-plan/<slug>-<YYYY-MM-DD>.md when the user passes --out or says "save this."
After you produce the plan, you may offer to run its runnable Section 7 prompts
through utility-pm-workflow-orchestrator, the governed plan orchestrator. This
is an offer, never an auto-run, and it never relaxes the orchestrator's
guardrails. You still do no inline execution of work-skills yourself.
When to offer. Make the offer ONLY when Section 7 produced at least one
runnable block (a prompt carrying a resolvable **Skill:** \name`` line). If
Section 7 is all-manual or empty, do not dangle an offer you cannot fulfill: say
there is nothing runnable to hand off, or say nothing.
The closing offer. When at least one runnable block exists, append one short
closing line after Section 8 (not a new numbered section): note that you can run
the plan's runnable Section 7 prompts through utility-pm-workflow-orchestrator
in CHECKPOINTED mode (one go/no-go per step), and ask whether to proceed.
On one confirmation. On a single explicit yes, hand the plan you just
produced to utility-pm-workflow-orchestrator in CHECKPOINTED mode. Do not
re-prompt, re-classify, or add your own gate: the handoff is the boundary, and
every pause after it belongs to the orchestrator's per-step checkpoints. The
orchestrator parses Section 7 in document order and pauses for go/no-go after
each step.
--run. Produce the plan AND hand it off in one invocation, still
CHECKPOINTED by default. If the produced Section 7 has zero runnable blocks,
--run degrades to the no-op offer state: report that there is nothing to run
rather than starting an empty run.
--force-auto. Forward this flag to utility-pm-workflow-orchestrator
unchanged. You never interpret or relax it. It suppresses per-step pauses for
unambiguously-produced steps only, and it never bypasses the orchestrator's
stop-on-failed/empty guardrail or its Cynefin floor (Complex and Chaotic plans
stay checkpointed unless the orchestrator's own override conditions are met).
The domain comes from the plan's own Section 2.
You never run work-skills inline. The offer and flags only route to the
separate, governed orchestrator. Recommending downstream skills in Section 7 and
handing the plan to the orchestrator are the only ways this skill causes
execution, and the second one always passes through one explicit confirmation
(or the --run flag) into a skill that checkpoints every step.
Self-reference safety. The handoff pointer always targets
utility-pm-workflow-orchestrator and never names this skill or itself as a
runnable step. Section 7's Tier-3 and name-safety rules already forbid
recommending this skill itself, and the orchestrator refuses any Section 7 that
names this skill or the orchestrator, so neither side can loop.
Before finalizing, verify:
Source: quote is an exact substring of the inputSource: quote that is not an exact substring of the input is a fabrication. Quote exactly or mark Inferred.See references/EXAMPLE.md for one fully worked plan (Complicated domain), and references/ example files for Complex cases.
© product-on-purpose, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 11 other files (references) in skills/foundation-prioritized-action-plan of product-on-purpose/pm-skills.
Open the folder on GitHubat commit 1cef1a9
Foundation Prioritized Action Plan next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Foundation Prioritized Action Plan this skillproduct-on-purpose/pm-skills | 716 | — | ~5.8k | Automated safety check: Pass | Apache-2.0 | |
| Stakeholder Summarytestdouble/han | 281 | — | ~6.3k | Automated safety check: Pass | MIT | |
| Stakeholder Updatejeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~2.5k | Automated safety check: Pass | MIT | |
| News Aggregator Skillcclank/news-aggregator-skill | 1.3k | — | ~2.1k | Automated safety check: Pass | None | |
| Changelog Social RecapFlorianBruniaux/claude-code-ultimate-guide | 6.1k | — | ~1.8k | Automated safety check: Notes | CC-BY-SA-4.0 | |
| Management Talkthananon/9arm-skills | 3.2k | — | ~3.2k | Automated safety check: Pass | None |
testdouble/han
Produces a plain-language stakeholder summary from an existing feature specification, for sharing with non-technical stakeholders before implementation kicks off.
jeremylongshore/tons-of-skills-marketplace
Create and review stakeholder status updates, progress reports, and executive summaries.
cclank/news-aggregator-skill
Comprehensive news aggregator that fetches, filters, and deeply analyzes real-time content from 44+ sources including Hacker News, Lobsters, Dev.to, GitHub, arXiv, Hugging Face Papers, AIHOT, TLDR…
FlorianBruniaux/claude-code-ultimate-guide
Turns CHANGELOG.md entries for a release or a week into LinkedIn, Twitter/X, newsletter and Slack posts in French and English.
thananon/9arm-skills
Rewrite engineer-to-engineer content for engineering-org leadership (VPs, directors, PMs, release managers, execs in an engineering-savvy company) and shape it for the channel it is going to — JIRA…
geekjourneyx/ai-daily-skill
Fetches AI news from smol.ai RSS and generates structured markdown with intelligent summarization and categorization.
product-on-purpose/pm-skills
Defines a testable hypothesis with clear success metrics and a validation approach.
product-on-purpose/pm-skills
Creates a Jobs to be Done canvas capturing the functional, emotional, and social dimensions of a customer job.
product-on-purpose/pm-skills
Creates an opportunity solution tree connecting a desired outcome to customer opportunities and candidate solutions, preventing solution-first jumps in continuous discovery.
product-on-purpose/pm-skills
Creates a clear problem framing document with user impact, business context, and success criteria.
product-on-purpose/pm-skills
Generates structured Given/When/Then acceptance criteria for a user story or feature slice, covering the happy path, key failure scenarios, and non-functional expectations in testable form.
product-on-purpose/pm-skills
Creates a cross-functional pre-launch checklist covering engineering, design, marketing, support, legal, and operations readiness, with owners, dates, and go/no-go criteria so nothing is missed…
Works with
Produce a comprehensive, evidence-grounded prioritized action plan from any PM input (notes, transcripts, drafts, executive asks, Slack threads, or a raw situation). Foundation Prioritized Action Plan is an agent skill from product-on-purpose/pm-skills. Produce a comprehensive, evidence-grounded prioritized action plan from any PM input (notes, transcripts, drafts, executive asks, Slack threads, or a raw situation).
Foundation Prioritized Action Plan fits situations like: you want the critical next effort and how to execute it; tasks that involve Summarization.
Run `npx skills add product-on-purpose/pm-skills --skill foundation-prioritized-action-plan -a claude-code`. Or copy the skill folder (skills/foundation-prioritized-action-plan in product-on-purpose/pm-skills) into .claude/skills/foundation-prioritized-action-plan in your project. Claude Code loads it when a task matches its description.
Run `npx skills add product-on-purpose/pm-skills --skill foundation-prioritized-action-plan -a codex`. Or copy the skill folder (skills/foundation-prioritized-action-plan in product-on-purpose/pm-skills) into .agents/skills/foundation-prioritized-action-plan in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add product-on-purpose/pm-skills --skill foundation-prioritized-action-plan -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/foundation-prioritized-action-plan, .gemini/skills/foundation-prioritized-action-plan, .github/skills/foundation-prioritized-action-plan and .opencode/skills/foundation-prioritized-action-plan in your project.
SKILL.md names no scripts, command-line tools or credentials: Foundation Prioritized Action Plan is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Foundation Prioritized Action Plan is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 5.8k tokens (SKILL.md is roughly 23k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 9.2k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Foundation Prioritized Action Plan: Stakeholder Summary (testdouble/han, 281 stars), Stakeholder Update (jeremylongshore/tons-of-skills-marketplace, 2.8k stars), News Aggregator Skill (cclank/news-aggregator-skill, 1.3k stars) and Changelog Social Recap (FlorianBruniaux/claude-code-ultimate-guide, 6.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
product-on-purpose (a GitHub organization) maintains it in product-on-purpose/pm-skills, which has 716 GitHub stars. The repository holds 68 skills in this directory. The repository was last updated on October 8, 2026.
Source: product-on-purpose/pm-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.