MultiClaude: Command for Claude Code

.claude/commands/lean/user-research.md

user-research is a command for Claude Code from nguyennguyenit/MultiClaude. It costs 14 tokens per session (718 once invoked), scanned A, original, MIT.

A command that creates user-research documentation, including user profiles and maps of their journey through a product, before defining a minimum viable product. A minimum viable product is the smallest version made to test an idea.

In plain words
What is it for?
Use it to clarify a target audience, research competitors or trends when needed, create two or three personas, and document customer journeys for MVP and UX planning.
Why use it?
It helps teams understand users, their goals, current tools, and frustrations before deciding what to build.

Command for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: names the AskUserQuestion tool.

This is nguyennguyenit/MultiClaude's own configuration. It tells Claude Code how to work on MultiClaude itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything MultiClaude configures →

Reuse

Borrowing it

Nothing to install: this file belongs to nguyennguyenit/MultiClaude. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/nguyennguyenit/MultiClaude/master/.claude/commands/lean/user-research.md
Clone the repo
git clone --depth 1 https://github.com/nguyennguyenit/MultiClaude

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for user-research

README.md
[![agentmods](https://agentmods.dev/badge/commands/nguyennguyenit/multiclaude/user-research/github.svg)](https://agentmods.dev/commands/nguyennguyenit/multiclaude/user-research)
Your own site
<a href="https://agentmods.dev/commands/nguyennguyenit/multiclaude/user-research"><img src="https://agentmods.dev/badge/commands/nguyennguyenit/multiclaude/user-research/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for user-research

Your own site · 80×15
<a href="https://agentmods.dev/commands/nguyennguyenit/multiclaude/user-research"><img src="https://agentmods.dev/badge/commands/nguyennguyenit/multiclaude/user-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 14 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 718 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00014 $0.00718
Opus 5 $0.00007 $0.00359
Sonnet 5 $0.00003 $0.00144
Haiku 4.5 $0.00001 $0.00072

Measured 9d ago against content hash 1c0cc9abd6f6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

user-research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/commands/lean/user-research.md · 154 lines

How it starts

The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Purpose

Generate docs/USER_RESEARCH.md with personas and journey maps to inform /lean MVP definition and /ipa:bd UX design.

Input

Examples:

  • "SaaS product managers struggling with tool fragmentation"
  • "Small business owners managing inventory manually"

Role

You are a User Researcher specializing in:

  • Persona development (demographics, behaviors, goals, pain points)
  • Customer journey mapping (touchpoints, emotions, opportunities)
  • Empathy-driven design

Workflow

Step 1: Clarify Context

Use AskUserQuestion to gather:

  • Who is the target user? (role, demographics)
  • What problem are they experiencing?
  • What do they currently use?
  • What constraints do they have?

Step 2: Research

If needed:

  • WebSearch for competitor analysis
  • WebSearch for industry trends
  • ai-multimodal to analyze competitor screenshots

Step 3: Generate Personas (2-3)

### Persona 1: [Name + Archetype]

**Demographics:**
- Age: [range]
- Role: [job title]
- Location: [geography]

**Behaviors:**
- [Key activities]
- [Tool patterns]

**Goals:**
- [Primary]
- [Secondary]

**Pain Points:**
- [Frustration 1]
- [Frustration 2]

**Quote:** "[Mindset statement]"
**Tech Savviness:** [Low/Medium/High]

Step 4: Map Customer Journey

For primary persona, map 5 stages:

### Stage 1: Discovery
**Touchpoint:** [Where they encounter product]
**Emotion:** [Feeling]
**Actions:** [What they do]
**Pain Points:** [Frustrations]
**Opportunities:** [Improvements]
**Design Implications:** [UI/UX decisions]

Stages: Discovery → Onboarding → Usage → Retention → Advocacy

Step 5: Output docs/USER_RESEARCH.md

# User Research

**Generated:** {date}
**Context:** {problem-space}

---

## Executive Summary

**Target Users:** [Description]
**Key Insights:**
- Insight 1
- Insight 2

---

## Personas

[Persona 1]
[Persona 2]

---

## Customer Journey Map

[Journey for primary persona]

---

## Competitor Landscape

| Competitor | Features | Strengths | Weaknesses | Differentiation |
|------------|----------|-----------|------------|-----------------|

---

## Assumptions to Validate

- [ ] Assumption 1 (validate via...)
- [ ] Assumption 2 (validate via...)

---

## Next Steps

1. Use personas in /lean MVP definition
2. Map journey stages to screens in /ipa:bd
3. Validate assumptions via interviews/testing

Read the full file on GitHub · 154 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 154 lines · 14 tokens per session scan A 1c0cc9abd6f6

Subscribe to this mod's changes

user-research is a command published in the GitHub repository nguyennguyenit/MultiClaude (22 stars, last pushed 28d ago), licensed MIT. It adds 14 tokens to every session and 718 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.