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Product Discovery TEXT

Facilitates structured product discovery by mapping assumptions, building Opportunity Solution Trees, and planning validation sprints to test problem-solution fit before development.

0 uses this weeksource alirezarezvanilicence MIT
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Security scan: clean · 2026-10-24 · 3 files · ran in sandbox
no network calls, shell tricks, credential access or instruction tampering found in its files.

Try asking

Say it in your own words; the assistant finds this recipe by itself. Examples:

“Jeg har en liste over brugerproblemer fra vores seneste interviews. Kan du hjælpe mig med at strukturere dem i en Opportunity Solution Tree?”
“Kortlæg de vigtigste antagelser for vores nye onboarding-flow og rangér dem efter risiko og sikkerhed, så vi ved, hvad vi skal teste først.”
“Vi skal validere, om brugerne faktisk vil have en mørk tilstand. Hvilke specifikke eksperimenter bør vi køre i en 1-ugers discovery-sprint?”
“I have a list of user pain points from our last interview round. Can you help me structure these into an Opportunity Solution Tree?”
“Map the key assumptions for our new onboarding flow and rank them by risk and certainty so we know what to test first.”
“We need to validate if users actually want a dark mode feature. What specific experiments should we run in a 1-week discovery sprint?”
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Good for

product-discoveryopportunity-solution-treeassumption-mappingproblem-validationsolution-validationdiscovery-sprintuser-researchrisk-assessment

Not for

Do not use this skill for executing the actual software development, writing code, or managing project timelines after the discovery phase is complete. For pure market sizing or financial modeling without user validation, use a business-case or financial-analysis skill instead.

Details

When it is the right choice

Use this skill when you need to validate a new product idea or feature before committing engineering resources. It is appropriate for structuring discovery sprints, mapping high-risk assumptions, or synthesizing user interview data to confirm problem-solution fit.

The full recipe the assistant reads

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

  1. Define desired outcome
  2. Set one measurable outcome to improve.

  3. Establish baseline and target horizon.

  4. Build Opportunity Solution Tree (OST)

  5. Outcome -> opportunities -> solution ideas -> experiments

  6. Keep opportunities grounded in user evidence, not internal opinions.

  7. Map assumptions

  8. Identify desirability, viability, feasibility, and usability assumptions.
  9. Score assumptions by risk and certainty.

Use:

python3 scripts/assumption_mapper.py assumptions.csv
  1. Validate the problem
  2. Conduct interviews and behavior analysis.
  3. Confirm frequency, severity, and willingness to solve.

  4. Reject weak opportunities early.

  5. Validate the solution

  6. Prototype before building.
  7. Run concept, usability, and value tests.

  8. Measure behavior, not only stated preference.

  9. Plan discovery sprint

  10. 1-2 week cycle with explicit hypotheses
  11. Daily evidence reviews
  12. 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.

Files in this skill (4)
  • LICENSE
  • SKILL.md
  • references/discovery-frameworks.md
  • scripts/assumption_mapper.py
Where it comes from

Vendored from alirezarezvani/claude-skills, commit 27cfcd0fb0a4, path product-team/skills/product-discovery, licence MIT. The upstream licence file ships inside the skill.