product-discovery
Use when validating product opportunities, mapping assumptions, planning discovery sprints, or testing problem-solution fit before committing delivery resources.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/alirezarezvani/claude-skills --skill product-discovery- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads product-discovery automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Product Discovery
Run structured discovery to identify high-value opportunities and de-risk product bets.
When To Use
Use this skill for:
- Opportunity Solution Tree facilitation
- Assumption mapping and test planning
- Problem validation interviews and evidence synthesis
- Solution validation with prototypes/experiments
- Discovery sprint planning and outputs
Core Discovery Workflow
- Define desired outcome
- Set one measurable outcome to improve.
- Establish baseline and target horizon.
- Build Opportunity Solution Tree (OST)
- Outcome -> opportunities -> solution ideas -> experiments
- Keep opportunities grounded in user evidence, not internal opinions.
- Map assumptions
- Identify desirability, viability, feasibility, and usability assumptions.
- Score assumptions by risk and certainty.
Use:
python3 scripts/assumption_mapper.py assumptions.csv
- Validate the problem
- Conduct interviews and behavior analysis.
- Confirm frequency, severity, and willingness to solve.
- Reject weak opportunities early.
- Validate the solution
- Prototype before building.
- Run concept, usability, and value tests.
- Measure behavior, not only stated preference.
- Plan discovery sprint
- 1-2 week cycle with explicit hypotheses
- Daily evidence reviews
- End with decision: proceed, pivot, or stop
Opportunity Solution Tree (Teresa Torres)
Structure:
- Outcome: metric you want to move
- Opportunities: unmet customer needs/pains
- Solutions: candidate interventions
- Experiments: fastest learning actions
Quality checks:
- At least 3 distinct opportunities before converging.
- At least 2 experiments per top opportunity.
- Tie every branch to evidence source.
Assumption Mapping
Assumption categories:
- Desirability: users want this
- Viability: business value exists
- Feasibility: team can build/operate it
- Usability: users can successfully use it
Prioritization rule:
- High risk + low certainty assumptions are tested first.
Problem Validation Techniques
- Problem interviews focused on current behavior
- Journey friction mapping
- Support ticket and sales-call synthesis
- Behavioral analytics triangulation
Evidence threshold examples:
- Same pain repeated across multiple target users
- Observable workaround behavior
- Measurable cost of current pain
Solution Validation Techniques
- Concept tests (value proposition comprehension)
- Prototype usability tests (task success/time-to-complete)
- Fake door or concierge tests (demand signal)
- Limited beta cohorts (retention/activation signals)
Discovery Sprint Planning
Suggested 10-day structure:
- Day 1-2: Outcome + opportunity framing
- Day 3-4: Assumption mapping + test design
- Day 5-7: Problem and solution tests
- Day 8-9: Evidence synthesis + decision options
- Day 10: Stakeholder decision review
Tooling
scripts/assumption_mapper.py
CLI utility that:
- reads assumptions from CSV or inline input
- scores risk/certainty priority
- emits prioritized test plan with suggested test types
See references/discovery-frameworks.md for framework details.
FAQ
What does the product-discovery skill do?
Use when validating product opportunities, mapping assumptions, planning discovery sprints, or testing problem-solution fit before committing delivery resources.
How do I install product-discovery?
Run npx skills add https://github.com/alirezarezvani/claude-skills --skill product-discovery in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/product-discovery/ (personal) or .claude/skills/product-discovery/ (project).
Which AI agents can use product-discovery?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is product-discovery safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains product-discovery?
It is published by alirezarezvani in alirezarezvani/claude-skills. It has 717 recorded installs.
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