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.
curl -O https://raw.githubusercontent.com/nguyennguyenit/MultiClaude/master/.claude/commands/lean/user-research.mdgit clone --depth 1 https://github.com/nguyennguyenit/MultiClaudeWrote 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.
[](https://agentmods.dev/commands/nguyennguyenit/multiclaude/user-research)<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.
<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>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00014 | $0.00718 |
| Opus 5.5 | $0.00006 | $0.00287 |
| Sonnet 5.5 | $0.00003 | $0.00144 |
| Haiku 4.5 | $0.00001 | $0.00072 |
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 2mo 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.
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
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.
- 2mo ago First seen · 154 lines · 14 tokens per session scan A 1c0cc9abd6f6
user-research is a command published in the GitHub repository nguyennguyenit/MultiClaude (23 stars, last pushed 2mo ago), licensed MIT. It adds 14 tokens to every session and 718 once invoked, about $0.0001 per session on Opus 5.5. 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.
user-research compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| user-researchnguyennguyenit/MultiClaude | Command | 23 | 2mo ago | MIT | A | 14 | Claude Code |
| checklistgithub/spec-kit | Command | 148k | yesterday | MIT | A | 13 | Claude Code |
| clarifygithub/spec-kit | Command | 148k | yesterday | MIT | A | 27 | Claude Code |
| specifygithub/spec-kit | Command | 148k | yesterday | MIT | A | 13 | Claude Code |
| analyzegithub/spec-kit | Command | 148k | yesterday | MIT | A | 26 | Claude Code |
| convergegithub/spec-kit | Command | 148k | yesterday | MIT | A | 35 | Claude Code |
| implementgithub/spec-kit | Command | 148k | yesterday | MIT | A | 14 | Claude Code |