product
Skill1 starsChanged 4 months agoMITView on GitHub
Decide what to build, for whom, and why, then specify it for delivery — product discovery, strategy, and PRDs across websites, web/SaaS apps, mobile, agentic/AI products, and internal tools. Use for opportunity discovery, user and market research, jobs-to-be-done, strategy and positioning, business-model and pricing, dunning/billing-failure recovery, market sizing, PRDs and acceptance criteria, prioritization and roadmaps, success metrics and metric-trees, and risk/assumption registers. Not for UI/experience design, implementation, system architecture, marketing/GTM, or growth experiments — recommend those sibling skills.
14 other projects use a version of this.
Adopted by
Most recently taken up by
- Astatide1337/Skillstheir own version, first seen Nov 8, 2026
- PeterPartridge/CooperativeAICodingtheir own version, first seen Nov 8, 2026
- Mark-Life/agent-skillstheir own version, first seen Nov 6, 2026
- malinskibeniamin/skillstheir own version, first seen Nov 1, 2026
- simscal/sapiens-dtjtheir own version, first seen Oct 20, 2026
- Dev-PGVAA/skillstheir own version, first seen Oct 16, 2026
Used with
Projects with it also use research and review.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
NVIDIASkillresearch
Before designing a feature, research how comparable libraries solve the problem, check best practices, known pitfalls, and upstream changes. Use when starting a new feature, investigating an unfamiliar area, or the user asks to research something.
Also in 3 projects that use this
SentrySkillreview
Fixture review skill.
Also in 3 projects that use this
Other versions14 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 14
- nitinjain999/platform-skills★ 71same name
- malinskibeniamin/skills★ 4same name
- Mark-Life/agent-skills★ 4same name
- websublime/mister-anderson★ 3same name
- alex-voloshin-dev/ai-skills★ 2same name
- PeterPartridge/CooperativeAICoding★ 2same name
- tikhomirovv/agents-knowledge★ 2same name
- Astatide1337/Skills★ 1same name
- donatassimkus/claude-ai-skills★ 1same name
- LukeJMadden/Veltrix-skills★ 1same name
4 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository13 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- site/llms.txtllms.txt
- mediabunnySkill
- remotion-best-practicesSkill
- remotion-captionsSkill
- remotion-createSkill
- remotion-docsSkill
- remotion-interactivitySkill
- remotion-markupSkill
- remotion-renderSkill
- remotion-saasSkill
- remotion-upgradeSkill
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 13 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 39
Read every selected reference completely before producing the affected artifact.
- Distinctive: line 77
Prioritization is multi-engine: Run every applicable framework, report the *divergence* as the finding, and refuse to fabricate missing …
- Very specific: line 109
When downstream work is expected, emit the handoff.yaml companion with artifact paths, constraints, decisions, risks, and the recommended …
“Common” is measured: kept by at least 6 in 10 of the 13 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Product Strategy
Mission and boundary
Decide what to build, for whom, and why it matters — then specify it precisely enough that design and engineering can build the right thing. Own the front of the product lifecycle: discovery, strategy, definition, prioritization, and the measures of success. Produce validated problems, strategy, positioning, PRDs, prioritized roadmaps, success metrics, and a living risk register.
Own the decision about what to build; not its execution. Experience and UI design belong to
design; production code to frontend, server behavior to backend, the analytical data plane to
data, and model-driven behavior to ai; system and technical decisions to architecture; the
ship/no-ship decision and independent verification to quality; running the product in production
to operate; demand generation, positioning-as-market-copy, and go-to-market to marketing; funnel
experimentation and growth loops to growth; qualification and CRM to sales; onboarding, support,
and adoption to success; and business processes spanning systems the product does not own to
automation. Contribute to those; own none. Operate independently when invoked alone;
when upstream artifacts (research, founder brief, existing analytics) are supplied, use them without
silently overriding established decisions. Recommend adjacent skills; never invoke them
automatically unless the user requested a composition workflow.
Route before acting
- Identify the one primary job the request needs.
- Select at most one surface overlay — the product type reshapes discovery, metrics, and the PRD.
- Read every selected reference completely before producing the affected artifact; do not load unrelated references.
- For an agentic/AI product, always add the agentic overlay — it changes acceptance criteria, metrics, and risk.
Primary job
| User intent | Read | Produce |
| Discover the problem, talk to users, synthesize research | Discovery | Opportunity Solution Tree, interview plan/synthesis, validated problem, JTBD |
| Set product vision and strategy | Strategy | Strategy kernel, vision, principles, Lean Canvas |
| Position the product and define its value proposition | Positioning | Positioning statement, value-proposition canvas, beachhead (segment/audience) selection with disqualifiers, proof-backed claim ledger |
| Model the business and price it | Business model | Business Model Canvas, economic-value (ROI) model, pricing hypotheses (value-based, tiers, Van Westendorp), dunning/billing-failure recovery (involuntary churn) |
| Size the market and analyze competitors | Market | TAM/SAM/SOM with source-calibrated confidence, competitor profiles, landscape |
| Write the PRD, spec, or acceptance criteria | PRD | Altitude-flexed PRD (1-pager ↔ full ↔ machine-readable), Given/When/Then criteria, user/job stories |
| Prioritize and build a roadmap | Prioritization | Multi-engine prioritization (RICE/ICE/Opportunity-Score/Kano/MoSCoW) + outcome roadmap |
| Define success metrics | Metrics | North-star + metric tree, HEART/AARRR mapping, guardrails, OKRs |
| Surface and maintain risks and assumptions | Risk register | Living register: assumption taxonomy, demand hierarchy, evidence ladder, red-team, pre-mortem |
Surface overlay (at most one)
| Product type | Read | Reshapes |
| Marketing or content website | Website | Conversion goal, positioning-led discovery, audience journey |
| Web or SaaS application | App & SaaS | Activation/retention, pricing tiers, MRR/churn metric trees, commercial lifecycle |
| Mobile app (iOS/Android) | Mobile | App-store context, platform expectations, mobile discovery |
| Agentic / AI product | Agentic | Capability & failure-mode mapping, eval-as-acceptance-criteria, human-in-loop, non-determinism/latency/cost/safety risk, model choice |
| Internal or enterprise tool | Internal | Stakeholder-driven, adoption over acquisition |
Universal invariants
- Discovery before solution. Frame opportunities, not features; never let stakeholders design the solution before the problem is validated. When uncertainty is about desirability, run the cheapest probe that tells the harshest truth before committing to build.
- Label evidence. Tag every claim as Fact (source-supported), Inference (reasoned), or Assumption (unvalidated). Assumptions flow to the risk register, not into a fabricated fact.
- Numbers carry calibrated confidence. Market sizes and metric targets are ranges with a source-quality tier, never a false single point. TAM is a ceiling; derive revenue from SOM.
- Prioritization is multi-engine. Run every applicable framework, report the divergence as the finding, and refuse to fabricate missing inputs rather than forcing one rank.
- Outcomes over outputs; specificity over superlatives. A metric, a %, a timeframe, a named segment — never "great results" or "everyone."
- State the surface and the register. Name the product type; recommend — never silently invoke — sibling skills for work you do not own.
Core workflow
- Inspect the request, evidence, constraints, and existing artifacts.
- Select the smallest sufficient route: one primary job, at most one surface overlay.
- Record material assumptions and unresolved inputs; open a risk-register entry for each.
- Produce the requested artifact grounded in the named framework the reference specifies.
- Validate it against the request, constraints, and acceptance criteria; state confidence.
- Emit a compact handoff when downstream design/architecture work is expected.
Artifact contract
Each reference defines its artifact. Every product artifact must record: the objective and target
segment; facts/inferences/assumptions distinguished; the decisions made and their evidence; success
metrics or acceptance criteria; open questions with owners. A PRD additionally states scope
(in/out/future), and — for an agentic product — its eval set as acceptance criteria. Provide a
machine-readable companion (handoff.yaml) whenever downstream work is expected; see
Handoff.
Completion and handoff
Before completion:
- Confirm every requested artifact exists and its acceptance criteria are checkable.
- Record decisions, assumptions, risks, and unresolved questions with owners.
- Distinguish validation performed from validation remaining; state confidence honestly.
- When downstream work is expected, emit the
handoff.yamlcompanion with artifact paths, constraints, decisions, risks, and the recommended next skill — without duplicating the full artifact.
Resources
Load only what the selected route requires.
- Primary jobs: discovery · strategy · positioning · business-model · market · prd · prioritization · metrics · risk-register
- Surface overlays: website · app-saas · mobile · agentic · internal
- Pipeline: handoff — standalone vs pipeline behavior and the
handoff.yamlcompanion consumed bydesignandarchitecture.
Artifact home
Deliverables this skill produces default to digital-product/product/ at the working repository's
root, with cross-skill state in digital-product/LEDGER.md — created on first use and committed
with the repo. The digital-product composer skill owns this convention; solo use writes to the
same place. Never write into .orchestrate/ — that folder belongs to an orchestration run's
execution state, not to this family's deliverables.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

