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.
npx skills add cosmicstack-labs/mercury-agent-skills --skill user-researchgit clone --depth 1 https://github.com/cosmicstack-labs/mercury-agent-skillsWrote 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/skills/cosmicstack-labs/mercury-agent-skills/user-research)<a href="https://agentmods.dev/skills/cosmicstack-labs/mercury-agent-skills/user-research"><img src="https://agentmods.dev/badge/skills/cosmicstack-labs/mercury-agent-skills/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/skills/cosmicstack-labs/mercury-agent-skills/user-research"><img src="https://agentmods.dev/badge/skills/cosmicstack-labs/mercury-agent-skills/user-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00045 | $0.06138 |
| Opus 5 | $0.00023 | $0.03069 |
| Sonnet 5 | $0.00009 | $0.01228 |
| Haiku 4.5 | $0.00005 | $0.00614 |
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 8d 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 — 683 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Research
Core Principles
Great user research produces not just data, but decision-grade insights. These principles underpin every effective research practice:
-
Research without action is entertainment. Every study should end with a clear "so what" — actionable recommendations that change what you build or how you build it.
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Bias is always present. The best you can do is name it, design around it, and account for it in your analysis. Common biases: confirmation bias, interviewer bias, selection bias, social desirability bias.
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Quality over quantity. Five well-recruited, well-moderated interviews produce more insight than fifty poorly run surveys. Depth beats breadth for generative work.
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Triangulate methods. No single method tells the whole story. Combine qualitative (what people say/do) with quantitative (how many, how often) for robust insights.
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Participant comfort is paramount. Research participants are giving you their time, attention, and vulnerability. Respect that. Make them feel safe, valued, and heard.
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Share raw data, not just summaries. Teams make better decisions when they can watch recordings, read transcripts, and see patterns themselves. Don't gatekeep the data.
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Research is a team sport. Invite engineers, designers, and PMs to observe sessions. Direct exposure to users builds empathy and conviction that second-hand reports cannot match.
Research Maturity Model
Understand your organization's research maturity to identify the right next step.
| Level | Name | Characteristics |
|---|---|---|
| 1 | Ad-hoc | No dedicated researcher. Decisions based on intuition or stakeholder opinions. Research is reactive and rare. |
| 2 | Foundational | Occasional usability tests and surveys. Research is done but not systematic. Findings may not influence decisions. |
| 3 | Operational | Dedicated research function exists. Research is planned quarterly. Methods are consistent. Findings reach product teams. |
| 4 | Integrated | Research is embedded in every product team. Continuous discovery is practiced. Researchers participate in roadmap decisions. |
| 5 | Strategic | Research drives company strategy. Research-led innovation is standard. The org runs experiments to test strategic hypotheses. |
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.
- 8d ago First seen · 683 lines · 45 tokens per session scan A 55ac553d2c7e
User Research is a skill published in the GitHub repository cosmicstack-labs/mercury-agent-skills (471 stars, last pushed 17d ago), licensed MIT. It adds 45 tokens to every session and 6,138 once invoked, about $0.0002 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 2026-09-03.
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