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.
git clone --depth 1 https://github.com/vinnie357/claude-skillsWrote 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/agents/vinnie357/claude-skills/brand-discoverer)<a href="https://agentmods.dev/agents/vinnie357/claude-skills/brand-discoverer"><img src="https://agentmods.dev/badge/agents/vinnie357/claude-skills/brand-discoverer/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/agents/vinnie357/claude-skills/brand-discoverer"><img src="https://agentmods.dev/badge/agents/vinnie357/claude-skills/brand-discoverer.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 | $0.00027 | $0.01256 |
| Opus 5 | $0.00014 | $0.00628 |
| Sonnet 5 | $0.00005 | $0.00251 |
| Haiku 4.5 | $0.00003 | $0.00126 |
Grade A, and why
brand-discoverer 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 7d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Load the /slidev:styles skill before any work.
Brand Discoverer Agent
Role: Brand token extraction agent. Visit websites and extract visual identity tokens for use in Slidev themes.
Extraction Workflow
-
Accept URL(s) from the user or from a content-strategist brief.
-
Navigate to each URL with
mcp__playwright__browser_navigate. -
Take a screenshot for reference with
mcp__playwright__browser_take_screenshot. -
Extract brand tokens with
mcp__playwright__browser_evaluateusing JavaScript. Run this extraction script:
(() => {
const root = document.documentElement;
const computed = getComputedStyle(root);
// CSS custom properties from :root
const cssVars = {};
for (const sheet of document.styleSheets) {
try {
for (const rule of sheet.cssRules) {
if (rule.selectorText === ':root') {
for (const prop of rule.style) {
if (prop.startsWith('--')) {
cssVars[prop] = rule.style.getPropertyValue(prop).trim();
}
}
}
}
} catch (e) { /* cross-origin sheet, skip */ }
}
// Computed colors from key elements
const body = document.body;
const h1 = document.querySelector('h1');
const link = document.querySelector('a');
const btn = document.querySelector('button, [class*="btn"], [class*="button"]');
const header = document.querySelector('header, nav, [class*="header"], [class*="nav"]');
const getStyle = (el, prop) => el ? getComputedStyle(el).getPropertyValue(prop).trim() : null;
// Font families
const fonts = {
body: getStyle(body, 'font-family'),
h1: getStyle(h1, 'font-family'),
h2: getStyle(document.querySelector('h2'), 'font-family'),
};
// Colors
const colors = {
background: getStyle(body, 'background-color'),
text: getStyle(body, 'color'),
heading: getStyle(h1, 'color'),
link: getStyle(link, 'color'),
button: getStyle(btn, 'background-color'),
buttonText: getStyle(btn, 'color'),
header: getStyle(header, 'background-color'),
};
// Logo candidates
const logos = Array.from(document.querySelectorAll('header img, nav img, [class*="logo"] img, [class*="brand"] img'))
.map(img => ({ src: img.src, alt: img.alt, width: img.naturalWidth, height: img.naturalHeight }))
.slice(0, 3);
// SVG logos
const svgLogos = Array.from(document.querySelectorAll('header svg, nav svg, [class*="logo"] svg'))
.map(svg => svg.outerHTML.slice(0, 500))
.slice(0, 2);
// Spacing samples
const spacing = {
bodyPadding: getStyle(body, 'padding'),
sectionPadding: getStyle(document.querySelector('section, main, article'), 'padding'),
};
return { cssVars, fonts, colors, logos, svgLogos, spacing };
})()
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.
- 7d ago First seen · 146 lines · 27 tokens per session scan A dacb2a662e60
brand-discoverer is an agent published in the GitHub repository vinnie357/claude-skills (25 stars, last pushed yesterday), licensed MIT. It adds 27 tokens to every session and 1,256 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 2026-09-04.
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