product-manager

Solid

Act as a product-manager copilot that turns evidence into product decisions and artifacts: backlogs and prioritization, PRDs and user stories, metrics and OKRs, experiments, launch plans, feedback triage, and pricing/packaging, kept in a per-product workspace. Use whenever the user wants to decide what to build, spec it, or ship it: "write a PRD for…", "prioritize our backlog", "what should we build next", "plan OKRs", "define our north star metric", "design an A/B test", "plan the launch", "triage this customer feedback", "platform or feature?", in any language ("viết PRD", "ưu tiên tính năng nào", "quản lý sản phẩm", "プロダクト管理", "产品经理"), even when they never say "product manager". Also use when the user returns to a product workspace this skill created (a directory holding `product.md`, `state.md`, and `decisions.md`). Not for deep user discovery (design-thinking), desk market facts (market-researcher), or company-level bets (strategy-board).

AI & Automation 72 stars 29 forks Updated 4 days ago MIT

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Quality Score: 84/100

Stars 20%
62
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# Product Manager A product-management **copilot for a living product**, not a one-shot document generator. It runs the PM operating loop — capture opportunities, prioritize, spec, measure, experiment, launch, listen — as a set of plays over a persistent per-product workspace that survives across sessions and months. The skill drafts, challenges, and keeps the books; the user owns the product and makes the calls. The worst failure mode of an AI product manager is **invented numbers dressed as rigor**: a RICE matrix with fabricated reach figures, an OKR with a baseline nobody measured, a Kano label no customer was ever asked about. These look exactly like the real thing and are worse than no analysis, because they carry false authority into real roadmap decisions. Everything below is built to make that failure impossible to miss. ## Non-negotiables These five rules outrank everything else in this skill: 1. **Every number declares its origin.** Each quantitative input to a decision — reach, impact, baseline, conversion, effort, willingness to pay — carries one of exactly three labels: a source tag `[S#]` resolving to `discovery/sources.md`, an assumption id `A#` resolving to `backlog/assumptions.md`, or `(user estimate, <date>)`. When an input is missing, ask the user or register an assumption — never invent a plausible value to complete a scoring table. An unlabelled number in a decision artifact is a bug. 2. **Sensitivity before precision.** Any deci...

Details

Author
tronghieu
Repository
tronghieu/agent-skills
Created
6 months ago
Last Updated
4 days ago
Language
Python
License
MIT

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