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.
/plugin marketplace add cookiy-ai/user-research-skillnpx agentmods add plugins/cookiy-ai/user-research-skill/user-researchgit clone --depth 1 https://github.com/cookiy-ai/user-research-skillWrote 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/plugins/cookiy-ai/user-research-skill/user-research)<a href="https://agentmods.dev/plugins/cookiy-ai/user-research-skill/user-research"><img src="https://agentmods.dev/badge/plugins/cookiy-ai/user-research-skill/user-research.svg" alt="Measured on agentmods" height="20"></a>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 4d 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.
What it actually says
{
"name": "user-research",
"version": "1.1.3",
"description": "End-to-end user research skill for AI agents — plan qualitative studies (research plans, screening questionnaires, interview guides), synthesize interview transcripts into evidence-backed reports with codebooks and personas, run AI-moderated interviews with real or synthetic participants, and design and distribute multilingual quantitative surveys with conditional logic — all via natural language, powered by Cookiy AI.",
"author": {
"name": "Cookiy AI",
"email": "[email protected]",
"url": "https://cookiy.ai"
},
"homepage": "https://cookiy.ai",
"repository": "https://github.com/cookiy-ai/user-research-skill",
"license": "MIT",
"keywords": [
"user research",
"qualitative research",
"quantitative research",
"user interviews",
"interview guide",
"discussion guide",
"research plan",
"screening questionnaire",
"research synthesis",
"thematic analysis",
"survey design",
"participant recruitment",
"synthetic users",
"AI-moderated interviews",
"usability study",
"research report",
"discovery research",
"contextual inquiry",
"diary study"
]
}
What it installs
The manifest is a name and a version. 1 skill travel with it, and installing the plugin installs all of them — 0 tokens a session between them. Each is measured on its own page, and each can be installed alone.
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.
- 4d ago First seen · 36 lines scan A fb0f14a5cb4d
user-research is a plugin published in the GitHub repository cookiy-ai/user-research-skill (1,532 stars, last pushed 15d ago), licensed MIT. Its token cost is not measured: this kind of file is read by the harness, not the model. 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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