Individual skill
product-research
Use when planning or synthesizing user research: choosing the method, deciding how many participants, or turning coded notes into insights. Runs study_designer.py, saturation_planner.py and insight_synthesizer.py, which refuses single-source insights.
research-ops/skills/product-research/SKILL.md
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- agentic-ai Repository topic
- anthropic-claude Repository topic
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- claude-code Repository topic
- claude-skills Repository topic
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- research-ops Declared skill tag
- product-research Declared skill tag
- ux-research Declared skill tag
- jtbd Declared skill tag
- usability Declared skill tag
- saturation Declared skill tag
- insight-synthesis Declared skill tag
- research-repository Declared skill tag
- design Derived category
- productivity Derived category
- research Derived category
- design-interface Derived category
- productivity-notes Derived category
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# product-research
Product / user research as an operational discipline: choosing the right method, sizing it honestly, and synthesizing findings into governed insights. The core rule: **method must match the goal**, and **an insight requires recurrence across independent participants** — a single quote is an anecdote.
## Purpose
Product researchers, ResearchOps teams, and PMs running discovery need method rigor and an insight repository they can trust. This skill structures three decisions:
Three deterministic tools:
1. `study_designer.py` — Maps (research goal × product stage) to an appropriate method and emits a method-matched plan skeleton (objective, participant criteria, guide structure, success criteria). Redirects live A/B to `product-team/experiment-designer`.
2. `saturation_planner.py` — Method-based sample guidance with an explicit **confidence label**: Nielsen problem-discovery (5/segment), Guest et al. thematic saturation (~12), and evaluative coverage. Never claims a prevalence rate from a small-n usability test.
3. `insight_synthesizer.py` — Clusters coded observations by tag, counts distinct participants, ranks by cross-participant recurrence, and flags any candidate below the source threshold as an **ANECDOTE**, never promoting it to an insight.
