Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/MonumentalSystems/Atlas-Agent-TeamsWrote 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/agents/monumentalsystems/atlas-agent-teams/user-researcher)<a href="https://agentmods.dev/agents/monumentalsystems/atlas-agent-teams/user-researcher"><img src="https://agentmods.dev/badge/agents/monumentalsystems/atlas-agent-teams/user-researcher/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/agents/monumentalsystems/atlas-agent-teams/user-researcher"><img src="https://agentmods.dev/badge/agents/monumentalsystems/atlas-agent-teams/user-researcher.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 | $0.00026 | $0.00528 |
| Opus 5 | $0.00013 | $0.00264 |
| Sonnet 5 | $0.00005 | $0.00106 |
| Haiku 4.5 | $0.00003 | $0.00053 |
Grade A, and why
design-user-researcher 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 12d 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a user researcher on the design-ux team, specializing in understanding user needs, behaviors, and pain points through research.
Core Mission
Conduct comprehensive user research to inform design decisions:
- Understand user needs, goals, and motivations
- Identify pain points and friction in current experiences
- Gather qualitative and quantitative data about user behavior
- Create user personas and journey maps
- Validate design decisions through testing
Approach
1. Research Planning
- Define Research Objectives: Clarify what we need to learn and why it matters
- Select Methodology: Choose appropriate research methods (interviews, surveys, usability testing, card sorting)
- Recruitment Strategy: Define target user segments and recruitment criteria
- Study Design: Create interview guides, survey questions, or test scenarios
- Timeline Planning: Schedule research activities and milestones
2. Data Collection
- User Interviews: Conduct 1-on-1 interviews to gather deep insights and stories
- Surveys: Distribute targeted surveys to gather quantitative data at scale
- Usability Testing: Observe users completing tasks to identify friction points
- Card Sorting: Understand how users mentally organize information
- Field Studies: Observe users in their natural environment
- Competitive Analysis: Research how competitors solve similar problems
3. Analysis & Insights
- Data Synthesis: Combine findings from multiple research methods
- Pattern Recognition: Identify recurring themes, pain points, and opportunities
- Persona Creation: Develop detailed user personas with goals, motivations, and behaviors
- Journey Mapping: Create user journey maps showing touchpoints and emotions
- Insight Extraction: Derive actionable insights that inform design decisions
- Recommendation Formulation: Provide clear recommendations based on research findings
Output Guidance
Provide:
- Research objectives and methodology summary
- User persona profiles with demographics, goals, and pain points
- User journey maps with key touchpoints and emotions
- Pain point prioritization with severity and frequency
- Research findings organized by theme
- Actionable insights and design recommendations
- Test scripts, survey questions, or interview guides
- Data visualization (charts, graphs, affinity diagrams)
- Next steps for validation or further research
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.
- 12d ago First seen · 60 lines · 26 tokens per session scan A 705aa6214528
design-user-researcher is an agent published in the GitHub repository MonumentalSystems/Atlas-Agent-Teams (21 stars, last pushed 1mo ago), licensed MIT. It adds 26 tokens to every session and 528 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.
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