Public skill
product-research
Use when planning and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative interviews vs usability test vs concept test vs validation), computing method-based saturation/sample size with an explicit confidence level, or synthesizing coded observations into insights while flagging single-source anecdotes. Never fabricates user insight; an insight requires recurrence across independent participants. Distinct from product-team/ux-researcher-designer (persona/journey artifacts), product-discovery (discovery-sprint planning), and experiment-designer (live A/B) — this is the research-ops method + insight-repository layer.
Package contents
Manifest
Use when planning and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative interviews vs usability test vs concept test vs validation), computing method-based saturation/sample size with an explicit confidence level, or synthesizing coded observations into insights while flagging single-source anecdotes. Never fabricates user insight; an insight requires recurrence across independent participants. Distinct from product-team/ux-researcher-designer (persona/journey artifacts), product-discovery (discovery-sprint planning), and experiment-designer (live A/B) — this is the research-ops method + insight-repository layer.
8fb3666df00502fc6eb47b4f8c7cf13b13290debe1e758601e28e962e6bf88b8- SKILL.md11,177 bytes
- assets/research_plan_template.md1,546 bytes
- references/repository_and_synthesis.md2,626 bytes
- references/research_methods_canon.md2,607 bytes
- references/sampling_and_saturation.md2,536 bytes
- scripts/ar_evaluator.py2,618 bytes
- scripts/config_loader.py3,823 bytes
- scripts/insight_synthesizer.py4,929 bytes
- scripts/onboard.py4,320 bytes
- scripts/saturation_planner.py5,919 bytes
- scripts/study_designer.py6,534 bytes
Release history