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 cyborg-garden/hermes-agent-mt --skill adversarial-ux-testgit clone --depth 1 https://github.com/cyborg-garden/hermes-agent-mtWrote 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/cyborg-garden/hermes-agent-mt/adversarial-ux-test)<a href="https://agentmods.dev/skills/cyborg-garden/hermes-agent-mt/adversarial-ux-test"><img src="https://agentmods.dev/badge/skills/cyborg-garden/hermes-agent-mt/adversarial-ux-test/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/cyborg-garden/hermes-agent-mt/adversarial-ux-test"><img src="https://agentmods.dev/badge/skills/cyborg-garden/hermes-agent-mt/adversarial-ux-test.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 | $0.00057 | $0.02172 |
| Opus 5 | $0.00028 | $0.01086 |
| Sonnet 5 | $0.00011 | $0.00434 |
| Haiku 4.5 | $0.00006 | $0.00217 |
Grade A, and why
adversarial-ux-test 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 12d 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.
This is a copy
91% identical to adversarial-ux-test — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adversarial UX Test
Roleplay the worst-case user for your product — the person who hates technology, doesn't want your software, and will find every reason to complain. Then filter their feedback through a pragmatism layer to separate real UX problems from "I hate computers" noise.
Think of it as an automated "mom test" — but angry.
Why This Works
Most QA finds bugs. This finds friction. A technically correct app can still be unusable for real humans. The adversarial persona catches:
- Confusing terminology that makes sense to developers but not users
- Too many steps to accomplish basic tasks
- Missing onboarding or "aha moments"
- Accessibility issues (font size, contrast, click targets)
- Cold-start problems (empty states, no demo content)
- Paywall/signup friction that kills conversion
The pragmatism filter (Phase 3) is what makes this useful instead of just entertaining. Without it, you'd add a "print this page" button to every screen because Grandpa can't figure out PDFs.
How to Use
Tell the agent:
"Run an adversarial UX test on [URL]"
"Be a grumpy [persona type] and test [app name]"
"Do an asshole user test on my staging site"
You can provide a persona or let the agent generate one based on your product's target audience.
Step 1: Define the Persona
If no persona is provided, generate one by answering:
- Who is the HARDEST user for this product? (age 50+, non-technical role, decades of experience doing it "the old way")
- What is their tech comfort level? (the lower the better — WhatsApp-only, paper notebooks, wife set up their email)
- What is the ONE thing they need to accomplish? (their core job, not your feature list)
- What would make them give up? (too many clicks, jargon, slow, confusing)
- How do they talk when frustrated? (blunt, sweary, dismissive, sighing)
Good Persona Example
"Big Mick" McAllister — 58-year-old S&C coach. Uses WhatsApp and that's it. His "spreadsheet" is a paper notebook. "If I can't figure it out in 10 seconds I'm going back to my notebook." Needs to log session results for 25 players. Hates small text, jargon, and passwords.
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.
- 12d ago First seen · 192 lines · 57 tokens per session scan A ad4401ace143
adversarial-ux-test is a skill published in the GitHub repository cyborg-garden/hermes-agent-mt (13 stars, last pushed 4d ago), licensed MIT. It adds 57 tokens to every session and 2,172 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to adversarial-ux-test, differing in 2 lines, and is treated as a copy.
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