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 j4flmao/agent-skills --skill ux-researchgit clone --depth 1 https://github.com/j4flmao/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/j4flmao/agent-skills/ux-research)<a href="https://agentmods.dev/skills/j4flmao/agent-skills/ux-research"><img src="https://agentmods.dev/badge/skills/j4flmao/agent-skills/ux-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/j4flmao/agent-skills/ux-research"><img src="https://agentmods.dev/badge/skills/j4flmao/agent-skills/ux-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 | $0.00088 | $0.05837 |
| Opus 5 | $0.00044 | $0.02919 |
| Sonnet 5 | $0.00018 | $0.01167 |
| Haiku 4.5 | $0.00009 | $0.00584 |
Grade A, and why
design-ux-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.
How it starts
The opening of the file, as written. The whole thing — 588 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design UX Research
Purpose
Design and execute UX research with method selection, structured protocols, and systematic synthesis. Covers generative and evaluative methods, user interview protocols, moderated and unmoderated usability testing, data-driven persona creation, journey mapping, and findings synthesis frameworks. The goal is to reduce design risk by validating assumptions with real user data.
Agent Protocol
Trigger
Exact user phrases: "UX research", "user research", "usability testing", "user interview", "persona", "user journey", "information architecture", "card sorting", "research plan", "research method", "user study", "affinity mapping", "thematic analysis", "moderated test", "unmoderated test", "NPS", "SUS", "CSAT".
Input Context
Before activating, verify:
- Product stage: discovery / alpha / beta / live
- Research question or hypothesis
- Available participants and timeline
- Budget and tools available (remote testing platforms, recording)
- Existing UX artifacts (analytics, support tickets, previous research)
- Stakeholder expectations and key decisions riding on this research
- Acceptable risk level (how wrong can we afford to be?)
Output Artifact
UX research plan with method selection, interview or test protocol, and synthesis framework.
Response Format
- Research plan: method, participants, timeline
- Protocol: questions, tasks, scenarios with time allocations
- Synthesis framework: affinity mapping, persona, journey map
- No preamble. No postamble. No explanations. No filler/hedging/transitions. Compress output — why use many token when few do trick.
Completion Criteria
- Research question defined with hypothesis
- Method selected (generative or evaluative) with rationale
- Participant criteria defined (segments, sample size, screener)
- Interview or test protocol written with timed sections
- Synthesis method chosen (affinity mapping, thematic analysis)
- Output artifacts specified (personas, journey maps, findings report)
- Metrics defined for evaluative research (task completion, SUS, NPS)
- Research artifacts stored in shared repository
- Findings presented to stakeholders with actionable recommendations
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 588 lines · 88 tokens per session scan A 90ef4e9190ac
design-ux-research is a skill published in the GitHub repository j4flmao/agent-skills (23 stars, last pushed 6d ago), licensed MIT. It adds 88 tokens to every session and 5,837 once invoked, about $0.0004 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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