claude-pm-skills
Skill32 starsChanged 6 months agoMITView on GitHub
Product-management decision skills for solo founders and startup PMs: problem clarity, outcome definition, assumption mapping, prioritization, experiment design, PRD critique, launch readiness, and post-launch learning. Focused on deciding what is worth building rather than writing documents faster.
In this repository170 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
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- The first 60 shown.
The file
Files
claude-pm-skills
Catalogue stub — full package: pratikshadake/claude-product-management-skills
<!-- das:install:start — generated from stub.yaml by `npm run generate`; edit stub.yaml, not this block -->Decision tree
- Is the full skill already installed?
This package installs 15 skills (
problem-clarity,outcome-definition,assumption-mapper,jtbd-extractor,value-vs-effort,user-segment-prioritizer,tradeoff-articulator,roadmap-reality-checker,experiment-design,feature-adoption-analyzer,retention-drop-diagnoser,prd-critic,stakeholder-alignment-checker,launch-readiness,post-launch-learning); checking the first.- Global:
f=~/.agents/skills/problem-clarity/SKILL.md; [ -f "$f" ] && ! grep -q "^das:" "$f" && echo "installed" || echo "pointer" - Project:
f=.agents/skills/problem-clarity/SKILL.md; [ -f "$f" ] && ! grep -q "^das:" "$f" && echo "installed" || echo "pointer" installed→ the skill is installed asproblem-clarity, invoke it and proceedpointer→ go to step 2
- Global:
Detect scope, then install:
[ -e ~/.agents/skills/claude-pm-skills ] && echo "global" || echo "project"Global:
npx skills add pratikshadake/claude-product-management-skills --skill problem-clarity outcome-definition assumption-mapper jtbd-extractor value-vs-effort user-segment-prioritizer tradeoff-articulator roadmap-reality-checker experiment-design feature-adoption-analyzer retention-drop-diagnoser prd-critic stakeholder-alignment-checker launch-readiness post-launch-learning -g -yProject:
npx skills add pratikshadake/claude-product-management-skills --skill problem-clarity outcome-definition assumption-mapper jtbd-extractor value-vs-effort user-segment-prioritizer tradeoff-articulator roadmap-reality-checker experiment-design feature-adoption-analyzer retention-drop-diagnoser prd-critic stakeholder-alignment-checker launch-readiness post-launch-learning -yClaude Code: send a command as a chat message starting with
!to run it without leaving the conversation.
Heads-up
- License: MIT
- Name collision:
experiment-designis also written byassimovt-productskills(its install or its catalogue pointer); installing both overwrites the earlier one.
<!-- das:install:end -->Invoke after install
Each skill installs under its own name and is picked up automatically from a normal product question ("Is this problem worth solving?", "Which feature first?", "Why is retention dropping?"), or call it explicitly:
- Problem discovery:
problem-clarity,outcome-definition,assumption-mapper,jtbd-extractor - Prioritization and strategy:
value-vs-effort,user-segment-prioritizer,tradeoff-articulator,roadmap-reality-checker - Validation and learning:
experiment-design,feature-adoption-analyzer,retention-drop-diagnoser - Delivery and launch:
prd-critic,stakeholder-alignment-checker,launch-readiness,post-launch-learning
What it does
A set of short, opinionated product-management skills by pratikshadake. Each one is a compact decision prompt (purpose, when to use, a few steps, a fixed output template ending in a verdict or recommendation, and a worked example) rather than a long methodology. The package is aimed at solo founders and startup PMs who want help deciding what to build and whether it worked. The skills are small, so they cost little context but also carry far less depth than the larger PM suites.
When NOT to use
- Deep frameworks and templates (journey maps, opportunity-solution trees, story mapping, PRD process) → use
deanpeters-pm-skills - Full Triple Diamond methodology → use
pm-skills - UX research and journey mapping → use
phuryn-pm-skills - Marketing and CRO tasks → use
coreyhaines-marketing
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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- It worked
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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
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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.

