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 Owl-Listener/designpowers --skill synthetic-user-testinggit clone --depth 1 https://github.com/Owl-Listener/designpowersWrote 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/owl-listener/designpowers/synthetic-user-testing)<a href="https://agentmods.dev/skills/owl-listener/designpowers/synthetic-user-testing"><img src="https://agentmods.dev/badge/skills/owl-listener/designpowers/synthetic-user-testing/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/owl-listener/designpowers/synthetic-user-testing"><img src="https://agentmods.dev/badge/skills/owl-listener/designpowers/synthetic-user-testing.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 | $0.00071 | $0.02100 |
| Opus 5.5 | $0.00028 | $0.00840 |
| Sonnet 5.5 | $0.00014 | $0.00420 |
| Haiku 4.5 | $0.00007 | $0.00210 |
Grade A, and why
synthetic-user-testing 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 2mo 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 — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Synthetic User Testing
Synthetic user testing is the closest thing to putting the design in front of real people without leaving the pipeline. You walk through the interface as each persona, attempting real tasks, and report what works, what breaks, and what feels wrong — from their perspective, not yours.
This is not a checklist exercise. It is an act of empathy disciplined by specifics. When you test as Jordan (low-vision, uses 200% zoom and high contrast), you don't ask "is contrast sufficient?" — you ask "can Jordan find the 'continue reading' button at 200% zoom when three articles are competing for attention?"
When to Use
- After the fix round — the design-builder has addressed findings from critic, accessibility-reviewer, and heuristic-evaluator. Now validate that the fixes work and no new issues were introduced
- Before verification-before-shipping — synthetic testing feeds directly into the persona walkthrough in the verification report
- When the design-critic flags persona coverage gaps — if the critique says "unclear whether Persona X can complete Task Y," run a synthetic test to find out
- When the team is unsure about a flow — synthetic testing turns "I think this works for screen reader users" into "here's exactly where a screen reader user would get stuck"
Process
Step 1: Gather Test Context
Before testing, assemble:
- Personas from
inclusive-personas(viadesign-state.md) - Key tasks from the design brief — the things the design must enable
- The build — test the actual implementation, not the spec
- Assistive technology context — for each persona, what tools they use and how (zoom level, screen reader, keyboard-only, switch access, etc.)
Step 2: Define Test Scenarios
For each key task in the brief, write a scenario that a persona would actually encounter. Scenarios are not "test case 1" — they are moments:
Format:
SCENARIO: [Natural situation trigger]
TASK: [What the persona is trying to accomplish]
PERSONA: [Name] — [key ability context]
SUCCESS: [What "done" looks like for this persona]
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.
- 2mo ago First seen · 193 lines · 71 tokens per session scan A b92662cd20ce
synthetic-user-testing is a skill published in the GitHub repository Owl-Listener/designpowers (255 stars, last pushed 4mo ago), licensed MIT. It adds 71 tokens to every session and 2,100 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 2026-08-30.
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