cookiy-ai/user-research-skill
Cookiy AI Skill for AI agents (Claude, Codex, Cursor, OpenClaw) — end-to-end user research: AI interviews, synthetic users, quant surveys, participant recruitment. observed · 2026-08-28
Health v2 · maintenance only
63/100
- Activity 98
- Release rhythm 48
- Longevity 10
Flags: young
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 145
- days_rel: 139
- days_push: 14
- n_releases_24m: 1
Adoption not part of the score
1508 stars · 58 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
An open-source AI agent skill (installed as a CLI) that lets AI coding agents like Claude Code, Codex, Cursor, and OpenClaw plan, run, and synthesize user research — including AI-moderated interviews, synthetic users, and quantitative surveys. It connects to the Cookiy AI platform for end-to-end studies with real or synthetic participants and participant recruitment.
Use cases
- run user interviews from my AI coding agent
- recruit research participants for a UX study
- generate an interview guide and research plan
- synthesize interview transcripts into a research report
- run a quantitative survey with conditional logic
- simulate synthetic users for product feedback
- do ux research without leaving the terminal
When to choose
- you already work inside Claude Code, Codex, Cursor, or another agent and want research capabilities in that workflow
- you want end-to-end studies (recruit, interview, survey, synthesize) with real or synthetic participants
- you want an MIT-licensed, scriptable research skill rather than a closed SaaS-only tool
When to avoid
- you need a polished standalone GUI for research rather than an agent/CLI workflow
- you require full data control or air-gapped operation, since studies run through the Cookiy AI hosted platform
- you need statistically rigorous academic survey tooling with fine-grained sampling controls
Facets
cli-tool · maturity active
agent-framework cli nlp chatbot data-science analytics artificial-intelligence large-language-models developer-tools hr cli cross-platform python ai-skill user-research ux-research claude-code cursor codex synthetic-users interviews surveys participant-recruitment qualitative-research quantitative-research ai-agents nodejs
3 sources
- readme: https://github.com/cookiy-ai/user-research-skill · fetched 2026-08-28 · 0379cc6146e8
- homepage: https://cookiy.ai · fetched 2026-08-29 · 46b7900ff21f
- site_page: https://cookiy.ai/about · fetched 2026-08-29 · bf680672113c
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| cookiy-ai/user-research-skill | main | 63 |
For agents
markdown · JSON · MCP: product_card(name="cookiy-ai/user-research-skill")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem