run-user-interview
Skill1 starsChanged 31 days agoMITView on GitHub
Plan, configure and launch a structured user interview with AI participants against a live URL on Stunt Double, then read the synthesised report (summary, themes, recommendations).
In this repository20 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .claude/CLAUDE.mdCLAUDE.md
- check-agent-readinessSkill
- check-brandSkill
- check-complianceSkill
- check-continuitySkill
- check-design-systemSkill
- cloudSkill
- create-actor-panelSkill
- design-reviewSkill
- doctorSkill
- maintain-automationsSkill
- openSkill
- run-qa-suiteSkill
- runSkill
- run-ux-validationSkill
- setup-guardrailsSkill
- setupSkill
- triage-feedbackSkill
- verify-changeSkill
The file
Files
Run user interview
- Context:
list_workspaces(),list_projects(workspace_id). - Create:
create_interview(workspace_id, project_id, name, target_url, research_brief?).target_urlis where participants land; the brief is 1 to 3 paragraphs on what you want to learn and what it informs. - Guide:
add_interview_section(interview_id, title, intro_script?), then 2 to 5 items each viaadd_interview_item(section_id, type, prompt_text, expected_evidence?).type: "task"has the participant act in the browser;"question"is an open-ended answer. Tasks beat questions for journey research; use questions for reactions and "why". Keep to 1 to 3 sections and about 15 items at most. - Participants:
add_interview_participant(interview_id, …)with anactor_id(fromlist_actors, seecreate-actor-panel) or apersona_spec(name,bio, 3 to 5traits). Use 3 to 5, varying segment, device and locale. - Launch:
launch_interview(interview_id)is async; participants run in parallel. - Watch:
get_interview(interview_id)shows each participant's status (pending,running,completed,failed).get_interview_participant(participant_id)returns the full transcript with actions. - Report: once all participants land,
get_interview_report(interview_id)returns{ summary, themes, recommendations, per_question_rollup }. After changing participants or fixing a failed one,regenerate_interview_report(interview_id). Retry failed participants (dashboard) before regenerating.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

