Idea to plan
Expert UX design and product management skills for AI assistants, built from the Uxcel learning library.
npx -y skills add Uxcel-Lab/product-skills --skill idea-to-planAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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Orchestrated, idea-to-plan PM workflow. Establishes context once, then composes the PM generative ladder in order — problem → discovery → users → riskiest-assumption test → prioritization → spec → metrics — gating each step, enforcing evidence before the spec, and handing the result to product-review. Trigger when the user wants to go from a raw idea to a build-ready plan ("take me from problem to plan", "I have an app idea, where do I start", "turn this idea into a product plan", "plan a new product end to end") — but NOT when they ask for one specific PM artifact (let that skill trigger directly), and NOT for the strategy/launch arc (vision, competitive analysis, roadmap, GTM — offer those next).
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SKILL.md
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Idea → Plan (PM Creation Orchestrator) Skill
How this skill behaves (read first)
This is the front door for taking a raw idea to a build-ready plan, and the PM twin of
ux-design-from-scratch. Where pm-product-review orchestrates the validation direction
(generative → audit), this skill orchestrates the compositional direction
(generative → generative): it sequences the PM scope ladder —
problem → discovery → users → riskiest-assumption test → prioritization → spec → metrics —
pulling in each skill as the work needs it, then hands the result to pm-product-review for
validation.
It is the executable form of the compositional orchestration section (§9) of
docs/orchestration-policy.md, applied to PM. Its whole job is to avoid the failure this skill
was created to fix: a plan that is overdeveloped as a PRD and underdeveloped as a de-risked
product bet — a polished spec resting on an unexamined market and an untested
willingness-to-pay. The spec is the last rung, not the first, and it never runs before the
evidence rungs beneath it.
The one rule that makes this skill earn its place: evidence before spec. Claude's default, asked to "take me from idea to plan," rushes to a plausible-looking PRD — requirements, stories, metrics — built on an unvalidated problem and zero adoption evidence. That document looks complete, which is exactly why it's dangerous: teams build from it. This orchestrator forces the problem, the discovery evidence, and the riskiest-assumption test to come first, and keeps the spec proportionate instead of letting it swallow the plan.
When NOT to use this skill:
- One named artifact — "write me a PRD", "frame this problem", "build a prioritization matrix". Let that skill trigger directly. Explicit scope overrides orchestration.
- The strategy / launch arc — vision & strategy, competitive analysis, roadmap, GTM, launch
experiments. That is a different compositional arc (
pm-vision-strategy,pm-competitive-analysis,pm-roadmap,pm-gtm-plan,pm-experimentation-ab,pm-analytics). This skill stops at a validated, build-ready plan; offer to continue into the strategy arc rather than producing it here.
Step 0 — Establish the context profile (once)
Infer from what the user gave you; ask only the one or two questions that materially change what runs. State the assumptions you're proceeding with, then build in order. Persist this for the rest of the session — don't re-ask.
- The idea, in one line — what's being proposed, for whom. Restating this back is also the first integrity check (if it can only be stated as a solution, the problem isn't framed yet).
- Stakes & reversibility of the build decision — a cheap, reversible experiment needs far less evidence than an expensive, hard-to-undo bet. This sets how much discovery and testing rigor is warranted (over-testing a reversible call is as wrong as under-testing a big one).
- Stage — is the problem still unproven (does anyone care?), is the solution the open question (can they use it / will they switch?), or is it viability/scale (will they pay, does it hold up)? This points each rung at the right depth.
- Market maturity — is this a crowded category? If yes, the riskiest assumption is almost
never "can we build it" — it's switching cost and adoption (why leave the incumbent?).
Flag this early; it changes which assumption gets tested first and makes
pm-competitive-analysisa live offer. - Evidence already in hand — existing research, data, or customer contact. Don't re-run discovery the user has already done; build on it.
Step 1 — Compose the ladder, gating at each rung
Walk the ladder in order. At each rung classify the skill as core (apply now) / offer (name, don't auto-build) / skip (owned elsewhere or already done) — don't apply every skill at full depth by default (that's the creation-side bandwagon).
Child skills are named by their installable skill
name. Compose one only if it's installed; if a named skill isn't present, apply that rung's intent inline with its core best practice and note the gap rather than blocking.
Rung 1 — Frame the problem · pm-problem-statement (core, first)
Pin the problem as a gap with evidence, separated from symptom and solution (problem + consequence + goal). Nothing downstream is trustworthy until this holds. If the user can't supply evidence, proceed but mark the problem as an unvalidated assumption to be retired in Rung 3 — don't paper over it.
Rung 2 — De-risk with discovery · pm-discovery (core — do NOT skip to the spec)
This is the rung the PRD-rushing default drops, and dropping it is exactly what produces a strong spec on a weak bet. Discovery establishes who actually adopts, how it fits their current workflow, whether they'd switch, and whether they'd pay — the evidence the plan stands on. Keep it proportionate to the Step 0 stakes (lightweight continuous contact for a reversible call; a deeper study for a big irreversible one), but always run it before the spec. In a crowded market, this is where switching-cost evidence comes from.
Rung 3 — Define the users · pm-personas-jtbd (core)
Ground the target users in the discovery evidence — jobs-to-be-done and real frustrations, every detail earning a decision. No demographic fiction. This rung consumes Rung 2's output; if discovery was skipped, personas are guesses and should be labelled as such.
Rung 4 — Test the riskiest assumption · pm-assumption-testing (core — and foreground it)
Surface the leap-of-faith belief — the one that, if false, sinks the idea — phrase it falsifiably, and design the cheapest test that answers it, with pre-set success criteria. Foreground the viability/desirability test, do not bury it under the spec. In most idea→plan cases the riskiest belief is "the people we're targeting will actually adopt this and pay/switch" — so a painted-door, concierge, or pre-sell test that checks real behavior before a line of code usually belongs here as an explicit build/no-build gate. A plan that frames this test as a buried sub-section of the PRD has failed this rung.
Rung 5 — Prioritize what to build first · pm-prioritization (core)
Decide the first slice with a method that traces to the strategy/outcome and exposes trade-offs, not fake-precise scores. Prioritization comes after the riskiest assumption is named — you prioritize against validated risk, not against a wish list.
Rung 6 — Write the plan · pm-product-spec (core, last — and proportionate)
Only now write the spec/PRD, and keep it proportionate to the evidence beneath it. Every
requirement testable, full flows (not happy paths), explicit scope-out, a
dependencies/constraints/assumptions section, and each assumption traced back to whether it's
been tested (Rung 4) or is still open. The spec's job is to carry forward the evidence and the
open risks, not to paper over them with polished requirements. pm-user-story is owned by this
rung (defer to it).
Rung 7 — Define success · pm-okrs-kpis (offer → core if metrics carry weight)
pm-product-spec already contains a success-metrics section; pull in pm-okrs-kpis when the plan
needs first-class outcome metrics — outcomes with baseline/target + guardrails, not vanity
counts. Offer it; make it core when the user asked for success metrics or when the spec's metrics
need real rigor.
Consistency rule: decisions propagate up the ladder. The problem framed in Rung 1, the evidence from Rung 2, and the validated/open assumptions from Rung 4 are reused by every rung above — don't re-litigate them inside the spec. This is the whole point of building idea-up.
Step 2 — Validate via product-review
When the plan exists, hand it to pm-product-review (if installed), which applies the audit
policy: it auto-runs pm-assumption-rigor-audit (the always-relevant lens — was the riskiest
assumption targeted, falsifiable, matched to a right-fidelity method with pre-set criteria?), and
routes by artifact type — spec → pm-spec-quality-audit, metrics → pm-okr-metric-validity-audit,
prioritization → pm-prioritization-rigor-audit, with pm-decision-quality-audit offered for the
build/no-build call. It returns one prioritized, de-duplicated report — not one per audit.
Resolve any findings back toward the Step 0 decision. If pm-product-review isn't installed, run
whichever audit skills are present directly, or self-review against the policy.
Step 3 — Offer the strategy / launch arc (don't auto-run it)
A validated plan is the handoff point, not the finish line. Once the plan passes review, offer
to continue into the strategy arc rather than producing it unprompted: product vision & strategy
(pm-vision-strategy), competitive analysis (pm-competitive-analysis — make this a strong
offer in a crowded market, since switching cost is a strategic question this arc owns), roadmap
(pm-roadmap), go-to-market (pm-gtm-plan), and launch experiments + analytics
(pm-experimentation-ab, pm-analytics). Naming the next arc is the service; auto-generating it
is the bandwagon.
Common do/don't patterns
| ❌ Don't | ✅ Do |
|---|---|
| Jump straight to a PRD when handed an idea | Frame the problem, then de-risk with discovery, before the spec |
| Skip discovery because the idea "obviously" has a market | Run discovery proportionate to stakes — adoption, workflow fit, switching cost, willingness to pay |
| Bury the validation test as a PRD sub-section | Foreground the riskiest-assumption test (often a concierge/pre-sell) as an explicit build gate |
| Let the spec become the whole plan | Keep the spec the last, proportionate rung; it carries the evidence forward |
| Treat "will they pay/switch" as a detail | In a crowded market, make switching cost the riskiest assumption and test it first |
| Prioritize a feature wish list | Prioritize against validated risk, traced to strategy, with trade-offs exposed |
| Run this orchestrator for a single named artifact | Let that skill trigger directly (explicit scope wins) |
| Auto-produce vision/competitive/roadmap/GTM | Stop at a validated plan; offer the strategy arc next |
| Declare done after generating | Hand to pm-product-review for one merged, severity-rated report |
Relationship to the policy
This skill is the compositional-orchestration section (§9) of docs/orchestration-policy.md in
executable form for PM work. Its validation twin is pm-product-review; its UX counterpart is
ux-design-from-scratch. If this skill and the policy ever diverge, the policy governs — update
this skill to match it.
Source lessons (Uxcel)
This is an orchestrator — most of its substance lives in the skills it composes (see the source
lessons in pm-problem-statement, pm-discovery, pm-personas-jtbd, pm-assumption-testing,
pm-prioritization, pm-product-spec, pm-okrs-kpis). The staging itself — idea → plan, with
evidence and definition before build — is grounded in: