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 joao-aires/agent-skills-public --skill usability-researchgit clone --depth 1 https://github.com/joao-aires/agent-skills-publicWrote 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/joao-aires/agent-skills-public/usability-research)<a href="https://agentmods.dev/skills/joao-aires/agent-skills-public/usability-research"><img src="https://agentmods.dev/badge/skills/joao-aires/agent-skills-public/usability-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/joao-aires/agent-skills-public/usability-research"><img src="https://agentmods.dev/badge/skills/joao-aires/agent-skills-public/usability-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 | $0.00047 | $0.00746 |
| Opus 5.5 | $0.00019 | $0.00298 |
| Sonnet 5.5 | $0.00009 | $0.00149 |
| Haiku 4.5 | $0.00005 | $0.00075 |
Grade A, and why
usability-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 yesterday.
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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Investigate usability with observable tasks
Choose research to resolve a user question or inform a decision. Use for requested study preparation or supplied observations; routine UI work can use interface quality without a study. Interaction design owns the proposed flow.
Frame the decision and method
Begin with the decision the team cannot yet make. Identify whose experience matters, what those people are trying to accomplish, and which uncertainty observation could resolve. Inspect the supplied flow, frame or prototype to see whether it supports that task, including the states the study intends to observe.
Form research questions about behavior or understanding that could change the design. Choose the method after framing the question: watching task performance can reveal where people become stuck, while asking for opinions alone cannot establish that they can use the interface. Reuse available context; ask only for facts that change the study and label planning assumptions.
| Question | Suitable method |
|---|---|
| Can participants complete or recover a task? | Observe realistic task performance. |
| How do participants understand a concept or wording? | Use a scoped concept/wording inquiry. |
Justify participant variation, recruitment, session length and sample through the decision and access limits. Quantitative coverage or population claims need an applicable source/model, assumptions and uncertainty; otherwise state the qualitative learning aim. A proposed sample remains a plan until recruitment occurs.
Observe without coaching
Give participants realistic goals and observable end states while leaving them to discover the interaction.
- Separate moderator setup, participant instructions and neutral follow-up probes.
- Recovery tasks can start from naturally occurring failures or a moderator-prepared failed state; instructions should preserve the original goal without teaching an invalid attempt or its correction.
- Instructional/comprehension exercises answer a different question and need their own interpretation.
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.
- yesterday Changed · +16 lines c854f26bbf62
- 3d ago Changed · -2 lines 65e11b6e3b79
- 5d ago First seen · 36 lines · 47 tokens per session scan A 5013ad5496a4
usability-research is a skill published in the GitHub repository joao-aires/agent-skills-public (2 stars, last pushed yesterday), licensed MIT. It adds 47 tokens to every session and 746 once invoked, about $0.0002 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 2026-10-17.
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