Point an agent at a rough idea and it writes features. product makes it decide what to build, for whom, and why first — discovery, strategy, positioning, PRDs, prioritization, metrics, and a living risk register, each grounded in the named PM canon and specified precisely enough for design and engineering to build the right thing.
runs onClaude CodeCodexCursorAntigravityopencodeGrok BuildHermes
discovery.mdsurface-agentic.md
2 of 15 loaded · read fully
Route before acting. Pick one job and at most one surface, read only those references — never the whole library. An agentic product always adds its overlay, because it changes the acceptance criteria.
The router is the skill. There is no fixed pipeline to run start-to-finish — each job stands alone and enters where your question is. The animation traces one path; the sections below map the whole surface it routes across.
product owns the front of the lifecycle — the decision about what to build and why. Experience, code, and systems belong to sibling skills; product feeds them a validated decision and a clean handoff, and recommends them by name rather than silently taking their work.
the front of the product lifecycle
contribute to; own none
Own the decision about what to build; not its execution. When upstream artifacts (research, a founder brief, analytics) are supplied, product uses them without silently overriding decisions already made.
SKILL.md is a router, not a script. Every request selects the smallest sufficient route: one primary job — the nine below — combined with at most one surface overlay that reshapes discovery, metrics, and the PRD for the product type. Read the selected references completely; load nothing unrelated. The nine jobs and five surfaces compose into 9 × 5 = 45 routes — from a two-file read to a full front-of-lifecycle pass — without ever reading all fifteen references at once.
| facet | options | rule |
|---|---|---|
| ① Primary job | discover · strategy · position · business model · market · PRD · prioritize · metrics · risk | Exactly one. Identify the single job the request needs. |
| ② Surface overlay | website · app & SaaS · mobile · agentic · internal | At most one. It reshapes the artifact for the product type — agentic always added when the model acts. |
Each job is one reference, read fully only when its route is selected — grounded in named canon, producing a checkable artifact. This is the whole surface, not a headline slice.
| I need to… | Read | Grounded in | Produces |
|---|---|---|---|
| Discover & validate the problem | discovery.md |
Torres Opportunity Solution Tree · Christensen JTBD · Fitzpatrick The Mom Test · MITRE Problem Framing | Validated problem, OST, interview plan/synthesis, JTBD statements |
| Set vision & strategy | strategy.md |
Rumelt strategy kernel · Perri strategy pyramid · Maurya Lean Canvas · Foundation Sprint | Strategy kernel, vision & principles, Lean Canvas |
| Position & frame the value | positioning.md |
Moore statement & beachhead · Dunford Obviously Awesome · Osterwalder Value Proposition Canvas | Positioning statement, VPC, named best-fit segment |
| Model the business & price it | business-model.md |
Osterwalder Business Model Canvas · value-based pricing · Van Westendorp · tier psychology | Business Model Canvas, pricing hypothesis (WTP bands, tiers) |
| Size the market & competitors | market.md |
TAM/SAM/SOM (top-down · bottom-up · comparable) · Porter Five Forces · SWOT · PESTEL | Source-calibrated size ranges, competitor profiles, landscape |
| Write the PRD & acceptance criteria | prd.md |
Rachitsky one-pager · ProductSpec machine-readable spec · Given/When/Then · job & user stories | Altitude-flexed PRD (1-pager ↔ full ↔ spec), checkable criteria |
| Prioritize & build a roadmap | prioritization.md |
RICE · ICE · Opportunity Score (Olsen) · Kano · MoSCoW · Weighted Scoring | Cross-framework score table + divergence, Now/Next/Later roadmap |
| Define success metrics | metrics.md |
North-star metric tree · HEART (Google) · AARRR (McClure) · Lean Analytics · OKRs (Doerr) | North star + metric tree, HEART/AARRR mapping, guardrails, OKRs |
| Surface & maintain risks | risk-register.md |
Cagan 4→8 risk taxonomy · demand hierarchy L0–L4 · evidence ladder · red-team · pre-mortem (Klein) | Living register: assumptions, verdicts, red-team & pre-mortem log |
Full router table & invariants: SKILL.md.
One overlay, at most, reshapes the job for the product type — the same PRD is scoped differently for a marketing site than a SaaS app. Agentic is the first-class differentiator, expanded below.
Nearly no PM discipline covers products whose value comes from a model acting, not a deterministic feature wrapped around a model call. For an agentic feature, desirability and feasibility collapse — a job is desirable only if a model can do it reliably, and reliability is empirical. So the headline move:
# productspec-ai-evals — an acceptance criterion, re-checked # every time the model or prompt changes id: EVAL-1 job: draft a support reply from the ticket thread task_set: 40 real transcripts, not invented cases evaluator: llm_judge # state the judge's own error rate pass_threshold: ≥ 90% · 0 hallucination-flagged offline_eval: fixed set, before every release online_eval: sampled prod traffic — catches drift regression_gate: block release if it regresses
actSix rules govern every route, whichever references it loads — the load-bearing ones, condensed.
When downstream build work is expected, product emits a compact handoff.yaml beside
the human artifact — a routing index into the PRD, strategy, or metric tree, never a copy of
it. Standalone by default; the companion appears only in pipeline mode, when a consumer will
actually read it.
skill: product status: complete objective: "" # only required field artifacts_created: [prd, metric-tree] decisions: · assumptions: · constraints: risks: [R-01, R-04] # pointers, not the register validation: performed / remaining recommended_next: design · architecture
Validated problem, target segment, the success metrics to design toward, hard constraints, and the open questions it must not silently resolve.
Non-functional requirements, constraints, technical-feasibility risks, and acceptance criteria that gate technical decisions — an agentic eval threshold constrains model choice.
Seam discipline. The human artifact is the real deliverable; if a consumer needs more than the index gives, the artifact itself is incomplete — the yaml never grows to compensate. Every downstream skill tolerates every field but objective being absent.
Install once. It's a plain SKILL.md router — no flags, no config, no scripts — so it
activates on natural-language phrasing ("validate this problem", "write a PRD", "prioritize this
backlog") rather than a fixed command.
The same install runs on any Agent Skills
host. Codex installs to ${CODEX_HOME:-$HOME/.codex}/skills and triggers with
$product; agents remains a separate cross-agent installation target.
| host | install target | command |
|---|---|---|
| Claude Code | ~/.claude/skills | ./install.sh claude |
| Codex | ${CODEX_HOME:-$HOME/.codex}/skills | ./install.sh codex |
| Cross-agent path | ~/.agents/skills | ./install.sh agents |
| Cursor CLI | ~/.cursor/skills | ./install.sh cursor |
| Antigravity (IDE + agy) | ~/.gemini/…/skills | ./install.sh antigravity |
| opencode | ~/.config/opencode/skills | ./install.sh opencode |
| Grok Build | ~/.grok/skills | ./install.sh grok |
| Hermes | ~/.hermes/skills | ./install.sh hermes |
Prefer npx skills add gabros20/product-skill -g -y when you have Node — it maps supported clients itself.
More docs: docs/installation.md · docs/usage.md · docs/recipes.md.