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…
Skill by product-on-purpose
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Use cases: documents, writing, productivity
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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~/.claude/skills/foundation-prioritized-action-plan
What's inside
- Skill name
foundation-prioritized-action-plan- Description
- 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 Complex or Chaotic situations. Use when you want the critical next effort and how to execute it.
- License
- Apache-2.0
- Metadata
- author: product-on-purpose · updated: 2026-07-05 · version: 1.2.0 · category: planning · classification: foundation
- Instructions
- 251 lines in SKILL.md · view on GitHub
Files (12)
- HISTORY.md
- SKILL.md
- cynefin-fixtures.md · eval/fixtures/
- rubric.md · eval/fixtures/
- trigger-fixtures.json · evals/
- 02-interview-transcript.md · examples/
- 03-executive-ask.md · examples/
- EXAMPLE.md · references/
- TEMPLATE.md · references/
- frameworks.md · references/
- recommendable-tiers.md · references/
- skill-catalog.md · references/
SKILL.md (first lines)
<!-- 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 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. ## When to Use - The user has input (notes, transcript, executive ask, draft PRD, customer interview, Slack thread, raw situation) and wants a ranked next-action plan - The user is uncertain what to do next and wants a recommendation grounded in their actual context - The user wants a single referenceable artifact that says what is most important, why, and how to execute it ## When NOT to Use - **vs `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. - **vs `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. - **vs `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. - **vs `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. - The user wants to generate a specific named artifact (persona, OKRs, journey map): invoke that skill directly. - The input is unrelated to PM work: refuse with a one-line redirect. ## Frameworks (the analytical engine) | 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`. ## Inputs Required: - User-provided content pasted into the conversation: notes, text, transcripts, drafts, executive asks, Slack threads, raw situations - Stated or inferred intent (what the user is trying to accomplish) Optional, improves quality: - Stated constraints (deadline, budget, team capacity, stakeholders) - The user's current Triple Diamond phase if known - A prior action plan to revise or extend Input acquisition rules: - **Pasted text is the primary input.** Treat what the user pasted as the authoritative source. - **File references:** if the user names a file AND the client has file access (for example Claude Code), read it and treat its quoted passages as input. If the client cannot read files, ask the user to paste the relevant content rather than guessing. Never fabricate file contents. - **Links and URLs are out of scope for now.** Ask the user to paste the relevant text. Do not assume web-fetch capability. ## Refusal and honesty protocols 1. **Off-topic input.** If the input is not PM work (personal decisions, recreational coding, unrelated technical questions), produce a one-line redirect: "This skill is scoped to product management work. For other contexts, use a general assistant." 2. **Insufficient signal.** If the input is under roughly 50 words and lacks specific signal, ask ONE clarifying question before producing the plan. Do not interrogate. 3. **Complex or Chaotic situation.** If the situation classifies Complex or Chaotic, produce the plan but lead the executive summary with the classification and its honest implication, and shape the plan accordingly (probes or stabilization, capped confidence). 4. **Cite or do not claim.** Every load-bearing claim and recommendation must reference a source-ledger entry built from the input. A claim with no source is tagged `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. 5. **No source available.** If the input genuinely lacks evidence for a needed claim, write `No source provided` and treat the claim as a gap in the questions section, not as fact. ## Instructions 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. ### Step 0: Build the source ledger (before writing any section) 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. ### Step 1: Mirror the input (Section 1) 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. ### Step 2: Classify the situation with Cynefin (Section 2) 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. ### Step 3: Name the binding constraint with Theory of Constraints (Section 3) 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. ### Step 4: Prioritize questions, gaps, and open decisions (Section 4) 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. ### Step 5: Write the prioritized action plan (Section 5) 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: - **Why:** the TOC reasoning; which constraint this lifts and why it is the critical next move - **What:** the concrete deliverable or outcome - **How:** 3 to 5 concrete steps - **Confidence:** High, Medium, or Low with one-line reasoning, respecting the Cynefin ceiling - **Source:** the ledger IDs grounding this effort, or `Inferred (Low confidence)` - **Expected outcome / success signal:** what changes if this works - **Estimated effort:** an honest time estimate - **Dependencies:** what must be true first, or "none" 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. ### Step 6: Pre-mortem the plan (Section 6)
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Signals
- Stars
- 758
- Forks
- 96
- Open issues
- 6
- Last commit (this folder)
- Jul 6, 2026 (3 months ago)
- Last release
- Oct 17, 2026 (16 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 1.2.0
- License
- Apache-2.0
- Repository
- github.com/product-on-purpose/pm-skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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foundation-prioritized-action-plan skill. Agent Mart. https://agentmart.dev/skills/product-on-purpose-foundation-prioritized-action-plan (last updated 2026-10-24)