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 porcupine-md/jonggrang --skill auditing-interface-qualitygit clone --depth 1 https://github.com/porcupine-md/jonggrangWrote 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/porcupine-md/jonggrang/auditing-interface-quality)<a href="https://agentmods.dev/skills/porcupine-md/jonggrang/auditing-interface-quality"><img src="https://agentmods.dev/badge/skills/porcupine-md/jonggrang/auditing-interface-quality.svg" alt="Measured on agentmods" 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 | $0.00021 | $0.00653 |
| Opus 5 | $0.00010 | $0.00327 |
| Sonnet 5 | $0.00004 | $0.00131 |
| Haiku 4.5 | $0.00002 | $0.00065 |
Grade A, and why
auditing-interface-quality 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 8d 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 — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auditing Interface Quality
Role Constraints: Reviewer (STRICTLY READ-ONLY for application code). You MAY NOT modify, fix, or write to application source code.
File Access: Use the glob tool to search for the active feature directory under .jonggrang/.output/features/. You may only use the write tool to save your audit report inside this specific directory.
Objective
Perform a systematic audit of the interface quality across accessibility (A11y), performance, theming, and responsive design.
Execution Steps
- Discover Context: Use
globandreadto review the frontend components built or modified for the current feature. - Live Browser Check (anoa): Whenever the app can be served, validate the
rendered UI — not just the source — with the
anoaCLI (preinstalled in the sandbox). It only observes the page, so it is safe under the read-only Reviewer role. The browser is a session: start it once, then every command attaches to it.
Save screenshots into the active feature directory. Seeanoa --headless --port 9222 & # once; `anoa status` exit 3 = not running anoa open <app-url> && anoa wait --load anoa snapshot -i # interactive elements with @refs anoa screenshot audit-desktop.png anoa set viewport 375 812 # re-check responsive anoa screenshot audit-mobile.png anoa set media dark && anoa screenshot audit-dark.png anoa errors # a page can look right and still throwskills/core/anoa/SKILL.mdfor the tool andskills/library/frontend/validating-visual-design/SKILL.mdfor the full workflow. - Diagnostic Scan (use the snapshot/screenshots as evidence):
- Accessibility (A11y): Check for contrast issues, missing ARIA roles, poor keyboard navigation, semantic HTML, and alt text.
- Performance: Look for layout thrashing, expensive animations, unoptimized images, or unnecessary re-renders.
- Theming: Look for hard-coded colors instead of design tokens, and broken dark mode implementations.
- Responsive Design: Check for fixed widths, touch target sizes (<44px), and horizontal scrolling issues on narrow viewports.
- Compile Audit Report:
- Document each issue with its Location, Severity (Critical/High/Medium/Low), Category, Impact, and Recommendation.
- Summarize the overall UI/UX compliance.
- Save Report:
- Write the final audit report using the
writetool to.jonggrang/.output/features/<active-feature-dir>/interface-audit.md.
- Write the final audit report using the
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.
- 8d ago First seen · 51 lines · 21 tokens per session scan A 662b40fc1aba
auditing-interface-quality is a skill published in the GitHub repository porcupine-md/jonggrang (11 stars, last pushed 12d ago), licensed MIT. It adds 21 tokens to every session and 653 once invoked, about $0.0001 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 2026-08-30.
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