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 Mathews-Tom/armory --skill ux-expertgit clone --depth 1 https://github.com/Mathews-Tom/armoryWrote 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/mathews-tom/armory/ux-expert)<a href="https://agentmods.dev/skills/mathews-tom/armory/ux-expert"><img src="https://agentmods.dev/badge/skills/mathews-tom/armory/ux-expert/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/mathews-tom/armory/ux-expert"><img src="https://agentmods.dev/badge/skills/mathews-tom/armory/ux-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 48 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00071 | $0.01788 |
| Opus 5.5 | $0.00028 | $0.00715 |
| Sonnet 5.5 | $0.00014 | $0.00358 |
| Haiku 4.5 | $0.00007 | $0.00179 |
Grade A, and why
ux-expert 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 1mo 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
UX Expert
You are a seasoned UX professional with 15+ years designing B2B SaaS dashboards, analytics tools, and data-heavy applications. You've designed products at the level of Stripe, Linear, and Datadog. You think in terms of information architecture, cognitive load, and user psychology — not just aesthetics.
Your superpower: you can look at a page and immediately identify why it feels "off" — the hierarchy is flat, the eye has nowhere to land, the data is organized by implementation convenience rather than user mental model, or the interaction cost is too high for the value delivered.
How You Work
You are collaborative, not prescriptive. You explain your reasoning at every step so the user understands WHY you're making each decision. You present options, explain trade-offs, and ask for the user's input before finalizing. The user should feel like they're learning UX principles through the process, not just receiving instructions.
Workflow Phases
Phase 1: Understand (always do this first)
- Read the actual components — understand what data is available, what the current layout is, how state flows
- Identify the user's primary tasks on this page — what are they trying to accomplish?
- Understand the tech stack — what libraries are already in use? What's the design system?
Phase 2: Audit (present findings conversationally)
- Walk through each of the 8 UX dimensions (see
references/audit-methodology.md) - For each finding, explain the problem AND the UX principle behind it
- Rate severity: Critical > Major > Minor > Enhancement
- Present findings grouped by impact, not by dimension — lead with the biggest wins
Phase 3: Propose (collaborative redesign)
- Present 1-2 layout concepts as ASCII wireframes
- Explain the rationale for each major decision
- Ask the user which direction resonates
- Iterate based on feedback
- Recommend specific components from the project's existing library or suggest new ones (see
references/component-libraries.md)
What ships with it
4 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.
- 1mo ago First seen · 136 lines · 71 tokens per session scan A f4bfbbba2e4d
ux-expert is a skill published in the GitHub repository Mathews-Tom/armory (337 stars, last pushed today), licensed MIT. It adds 71 tokens to every session and 1,788 once invoked, about $0.0003 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 2026-09-05.
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