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 agentmods add skills/guillermoscript/lms-front/auditnpx skills add guillermoscript/lms-front --skill auditgit clone --depth 1 https://github.com/guillermoscript/lms-frontWhat 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 | $0.00031 | $0.01373 |
| Opus 5 | $0.00015 | $0.00687 |
| Sonnet 5 | $0.00006 | $0.00275 |
| Haiku 4.5 | $0.00003 | $0.00137 |
Grade A, and why
audit 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 2d 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
100% identical to audit — 0 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Run systematic quality checks and generate a comprehensive audit report with prioritized issues and actionable recommendations. Don't fix issues - document them for other commands to address.
First: Use the frontend-design skill for design principles and anti-patterns.
Diagnostic Scan
Run comprehensive checks across multiple dimensions:
-
Accessibility (A11y) - Check for:
- Contrast issues: Text contrast ratios < 4.5:1 (or 7:1 for AAA)
- Missing ARIA: Interactive elements without proper roles, labels, or states
- Keyboard navigation: Missing focus indicators, illogical tab order, keyboard traps
- Semantic HTML: Improper heading hierarchy, missing landmarks, divs instead of buttons
- Alt text: Missing or poor image descriptions
- Form issues: Inputs without labels, poor error messaging, missing required indicators
-
Performance - Check for:
- Layout thrashing: Reading/writing layout properties in loops
- Expensive animations: Animating layout properties (width, height, top, left) instead of transform/opacity
- Missing optimization: Images without lazy loading, unoptimized assets, missing will-change
- Bundle size: Unnecessary imports, unused dependencies
- Render performance: Unnecessary re-renders, missing memoization
-
Theming - Check for:
- Hard-coded colors: Colors not using design tokens
- Broken dark mode: Missing dark mode variants, poor contrast in dark theme
- Inconsistent tokens: Using wrong tokens, mixing token types
- Theme switching issues: Values that don't update on theme change
-
Responsive Design - Check for:
- Fixed widths: Hard-coded widths that break on mobile
- Touch targets: Interactive elements < 44x44px
- Horizontal scroll: Content overflow on narrow viewports
- Text scaling: Layouts that break when text size increases
- Missing breakpoints: No mobile/tablet variants
-
Anti-Patterns (CRITICAL) - Check against ALL the DON'T guidelines in the frontend-design skill. Look for AI slop tells (AI color palette, gradient text, glassmorphism, hero metrics, card grids, generic fonts) and general design anti-patterns (gray on color, nested cards, bounce easing, redundant copy).
CRITICAL: This is an audit, not a fix. Document issues thoroughly with clear explanations of impact. Use other commands (normalize, optimize, harden, etc.) to fix issues after audit.
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.
- 2d ago First seen · 128 lines · 31 tokens per session scan A 42f37804554e
audit is a skill published in the GitHub repository guillermoscript/lms-front (24 stars, last pushed 2d ago), licensed MIT. It adds 31 tokens to every session and 1,373 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to audit, differing in 0 lines, and is treated as a copy.
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Survey a codebase's animation and motion code as a senior motion advisor, then produce a prioritized audit and self-contained implementation plans for other agents (or cheaper models) to execute. Read-only on source code — it plans improvements, it does not apply them. Use when the user asks to "improve the…