foundation-prioritized-action-plan
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. Builds a source ledger and cites exact input quotes; refuses High-confidence plans for
npx skills add product-on-purpose/pm-skills --skill foundation-prioritized-action-plan --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
The skill generates a comprehensive, evidence-grounded action plan from PM input (notes, transcripts, drafts, executive asks, Slack threads, or a raw situation). It outputs a single saveable document containing 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. It builds a source ledger and cites exact input quotes; refuses High-confidence plans for Complex or Chaotic situations.
How it works
- Build a source ledger of exact quotes from the user-provided input (3 to 12 entries, IDs S1, S2, ...).
- Mirror the input back (concise restatement), infer intent with confidence level, and identify adjacent intents.
- Classify the situation using Cynefin to determine plan posture and confidence ceiling; cite ledger passages that drove the classification.
- Identify the ONE binding constraint via Theory of Constraints; present the constraint, evidence sources, and possible alternative constraints, plus the causal link from P1 to constraint relief.
- List 3 to 7 prioritized questions/gaps with decisions required and resolution approach.
- Produce a prioritized action plan with 3 to 5 efforts (P1 to P5), each including Why, What, How (3–5 steps), Confidence, Source, Expected outcome, Estimated effort, Dependencies; P1 fully detailed, others shorter.
- Include Now / Next / Later sequencing and a What to defer list.
- Develop a pre-mortem with 3–5 risks, each with likelihood, impact, early signal, mitigation, and Source.
- Generate up to 3 copy/paste prompts for downstream skills, drawing only from tiered recommendable skills and exact-name constraints.
- Assemble an evidence map linking each claim to ledger entries.
When to use it
- When the user has input and wants a ranked next-action plan grounded in context.
- When the user is unsure of what to do next and seeks a reference artifact that states what is most important, why, and how to execute.
What it can touch
- The output is a single markdown document containing sections described above and a source ledger.
Caveats
- If the input signals a Complex or Chaotic situation, the plan prioritizes safe-to-fail probes or stabilization actions with capped confidence.
- Every load-bearing claim must cite a ledger entry; claims without sources are marked as Inferred (Low confidence).
<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 --> # Prioritized Action Plan 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. ## Identity - Foundation skill; produces a reusable PM working-document the user saves and reuses - Single-turn; one action plan per invocation - Read-only tools (Read, Grep); produces markdown output - Recommends a bounded, tiered set of downstream pm-skills (see "Recommendable skill tiers") and never invokes them inline; on explicit confirmation it can hand the plan to `utility-pm-workflow-orchestrator`, which runs them behind its own per-step checkpoints (see "Handoff to the orchestrator") ## Core principle **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 k
- Identity
- Core principle
- When to Use
- When NOT to Use
- Frameworks (the analytical engine)
- Inputs
- Refusal and honesty protocols
- Instructions
- Step 0: Build the source ledger (before writing any section)
- Step 1: Mirror the input (Section 1)
- Step 2: Classify the situation with Cynefin (Section 2)
- Step 3: Name the binding constraint with Theory of Constraints (Section 3)
- Step 4: Prioritize questions, gaps, and open decisions (Section 4)
- Step 5: Write the prioritized action plan (Section 5)
What does the foundation-prioritized-action-plan skill do?
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. Builds a source ledger and cites exact input quotes; refuses High-confidence plans for
How do I install it?
Run `npx skills add product-on-purpose/pm-skills --skill foundation-prioritized-action-plan --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From product-on-purpose/pm-skills, a repository with 518 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.