User Intuition Skills

User Intuition skills are short, copy-pasteable instruction files that teach a compatible AI agent how to drive the MCP server for a specific research workflow. Connect the hosted OAuth endpoint first when the client supports it; local stdio remains available for clients that need a local process. Where the MCP server gives an agent the tools, a skill gives it the play. The skill is the difference between “the agent can call create_study” and “the agent knows to ask whether you want Panel or BYOP recruitment, conduct the customize_study conversation, verify the saved study, and dry-run panel cost before requesting launch approval.”

When skills help

Repeatable workflows. Creating a study from a brief, screening panel respondents, generating an insights report — anything you do more than twice.
Cross-team consistency. Two PMs on different machines run the same workflow the same way because the skill ships the playbook.
Onboarding. A new teammate installs the skills and immediately runs the team’s standard research patterns.

How skills work

A skill is a Markdown file with YAML frontmatter. The frontmatter tells the agent when the skill applies; the body tells it how to execute. Example shape:

---
name: field-a-panel
description: Use when the user wants to recruit respondents from the User Intuition panel for an existing Panel study.
---

When the user wants to field a panel:

1. Verify the study is a provisioned Panel study via `get_study`.
2. Return the complete persisted plan and obtain approval of that exact version.
3. Ask the user to choose one launch country; never infer it.
4. Call `launch_panel` with `dry_run: true` and show the resolved country, language, cost, and timeline.
5. Wait for explicit approval of the estimate, then launch with `dry_run: false` using the same country.

Agents that support skills load the frontmatter at session start, then read the body when the description matches the user’s request.

Installing skills

Claude Code (plugin marketplace)
Agent-native
Claude Code (single skill)
Cursor
Claude Desktop

One command installs all eight skills, with updates delivered on marketplace refresh:

/plugin marketplace add user-intuition/skills
/plugin install user-intuition-research@user-intuition

Source: github.com/user-intuition/skills.

The whole skills library is served as raw Markdown. Tell your agent:

Fetch https://docs.userintuition.ai/skills/library.md and install each skill as ~/.claude/skills/<name>/SKILL.md — one directory per skill

The agent reads the page, writes each skill to its own file, and they’re live on the next session.

Claude Code discovers skills as one directory per skill with a SKILL.md entrypoint — a flat .claude/skills/<name>.md file is not discovered. Copy any skill block from the library into .claude/skills/<name>/SKILL.md (project-local) or ~/.claude/skills/<name>/SKILL.md (global):

mkdir -p ~/.claude/skills/field-a-panel
# paste the skill into ~/.claude/skills/field-a-panel/SKILL.md

Claude Code auto-discovers skills on next session start.

Cursor Project Rules live in .cursor/rules/<name>.mdc (the .mdc extension matters). Translate the skill’s frontmatter into rule metadata rather than dropping it — carry the skill’s description over, and set alwaysApply: false so Cursor applies the rule only when the description matches the task:

---
description: Use when the user wants to recruit respondents from the User Intuition panel for an existing Panel study.
alwaysApply: false
---

<paste the skill body here>

mkdir -p .cursor/rules
# save as .cursor/rules/field-a-panel.mdc

What’s in the library

The skills library covers the full research loop — every tool call verified against the current MCP schemas:

create-study-from-brief

Turn a research brief into a launch-ready interview study.

design-screeners

Recruit exactly the right respondents — panel and custom screeners, done safely.

field-a-panel

Recruit N respondents from the panel, with cost approved before any spend.

invite-your-own-participants

Interview your own customers — invites, share links, and rewards (BYOP).

run-a-concept-test

Put a concept, prototype, or landing page in front of participants.

monitor-fielding

Daily digest of every fielding study — progress, quality, stalls.

analyze-completed-study

From transcripts to stakeholder-ready findings, with real quotes only.

curate-interview-quality

Review low-quality interviews and delete only the exact interviews the user confirms.

Skill vs MCP vs CLI — which goes where

You want…	Use
An agent to autonomously run a research workflow from a vague prompt	Skill (built on MCP)
An agent to call User Intuition tools when you ask, with you in the loop	MCP alone
To run a tool from a shell script, CI job, or cron	CLI
To call User Intuition from your own backend code	REST API

Skills sit on top of MCP, while the MCP study-design workflow intentionally routes through the same Customize Plan backend used by the dashboard. The CLI and raw REST API are separate integration surfaces and may expose lower-level fields that MCP does not. Pick the highest level that gets the job done.

Get Started

Library

When skills help

How skills work

Installing skills

What’s in the library

create-study-from-brief

design-screeners

field-a-panel

invite-your-own-participants

run-a-concept-test

monitor-fielding

analyze-completed-study

curate-interview-quality

Skill vs MCP vs CLI — which goes where

Next steps

Skills library

MCP quickstart

​When skills help

​How skills work

​Installing skills

​What’s in the library

create-study-from-brief

design-screeners

field-a-panel

invite-your-own-participants

run-a-concept-test

monitor-fielding

analyze-completed-study

curate-interview-quality

​Skill vs MCP vs CLI — which goes where

​Next steps

Skills library

MCP quickstart

When skills help

How skills work

Installing skills

What’s in the library

Skill vs MCP vs CLI — which goes where

Next steps