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From thinking-frameworks-skills
Designs structured interview guides, surveys, and JTBD probes for user research while avoiding biases. Use for product discovery, unmet needs, concept testing, and problem validation.
How this skill is triggered — by the user, by Claude, or both
Slash command
/thinking-frameworks-skills:discovery-interviews-surveysThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
- [Workflow](#workflow)
Copy this checklist and track your progress:
Discovery Research Progress:
- [ ] Step 1: Define research objectives and hypotheses
- [ ] Step 2: Identify target participants
- [ ] Step 3: Choose research method (interviews, surveys, or both)
- [ ] Step 4: Design research instruments
- [ ] Step 5: Conduct research and collect data
- [ ] Step 6: Analyze findings and extract insights
Step 1: Define research objectives
Specify what you're trying to learn, key hypotheses to test, success criteria for research, and decision to be informed. See Common Patterns for typical objectives.
Step 2: Identify target participants
Define participant criteria (demographics, behaviors, firmographics), sample size needed, recruitment strategy, and screening questions. For sampling strategies, see resources/methodology.md.
Step 3: Choose research method
Based on objective and constraints:
Step 4: Design research instruments
Create interview guide or survey with bias-avoidance techniques. Use resources/template.md for structure. Avoid leading questions, focus on past behavior, use "show me" requests. For advanced question design, see resources/methodology.md.
Step 5: Conduct research
Execute interviews (record with permission, take notes) or distribute surveys (pilot test first). Use proper techniques (active listening, follow-up probes, silence for thinking). See Guardrails for critical requirements.
Step 6: Analyze findings
For interviews: thematic coding, affinity mapping, quote extraction. For surveys: statistical analysis, cross-tabs, open-end coding. Create insights document with evidence. Self-assess using resources/evaluators/rubric_discovery_interviews_surveys.json. Minimum standard: Average score ≥ 3.5.
Pattern 1: Problem Discovery Interviews
Pattern 2: Jobs-to-be-Done Research
Pattern 3: Concept Testing (Qualitative)
Pattern 4: Survey for Quantitative Validation
Pattern 5: Continuous Discovery
Key requirements:
Avoid leading questions: Phrase questions neutrally rather than telegraphing the "right" answer. Instead of: "Don't you think our UI is confusing?" use: "Walk me through using this feature. What happened?"
Focus on past behavior, not hypotheticals: What people did reveals truth; what they say they'd do is often wrong. Instead of: "Would you use this feature?" use: "Tell me about the last time you needed to do X."
Use "show me" over "tell me": Actual behavior is more reliable than described behavior. Ask to screen-share, demonstrate current workflow, show artifacts (spreadsheets, tools).
Recruit right participants: Screen carefully. Wrong participants waste time. Define inclusion/exclusion criteria and use screening surveys.
Sample size appropriate for method: Interviews: 5-15 for themes to emerge. Surveys: 100+ for statistical significance, 30+ per segment if comparing.
Seek disconfirming evidence: Actively look for evidence against your hypothesis. If 9/10 interviews support the hypothesis, focus heavily on the 1 that does not.
Record and transcribe (with permission): Memory is unreliable. Record interviews, transcribe for analysis. Take notes as backup.
Analyze systematically: Use thematic coding, count themes, and present contradictory evidence rather than cherry-picking supportive quotes.
Common pitfalls:
Key resources:
Typical workflow time:
When to escalate:
Inputs required:
Outputs produced:
discovery-interviews-surveys.md: Complete research plan with interview guide or survey, recruitment criteria, analysis plan, and insights templatenpx claudepluginhub lyndonkl/claude --plugin thinking-frameworks-skillsDesigns complete user interview research packages: research brief, screener, interview guide, and analysis framework. Supports discovery interviews, switch interviews, contextual inquiry, and evaluative interviews. Use when the user needs to validate JTBD hypotheses, test a concept with users, understand switching behavior, or observe how users interact with a product. Also triggers when the user says "I need to talk to users," "help me plan user interviews," "write an interview guide," "I need to validate this assumption," or "design a research study." Do NOT use for quantitative research (surveys, A/B tests) or for conducting the research itself.
Guides user research from planning through synthesis. Use when designing studies, writing interview guides, or synthesizing findings into insights.
Creates a structured user discovery interview guide with screener questions, discussion guide, and synthesis framework for planning user interviews, customer discovery, or problem validation.