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 agentry-ai/agentry --skill brand-guidelinesgit clone --depth 1 https://github.com/agentry-ai/agentryWrote 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/agentry-ai/agentry/brand-guidelines)<a href="https://agentmods.dev/skills/agentry-ai/agentry/brand-guidelines"><img src="https://agentmods.dev/badge/skills/agentry-ai/agentry/brand-guidelines/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/agentry-ai/agentry/brand-guidelines"><img src="https://agentmods.dev/badge/skills/agentry-ai/agentry/brand-guidelines.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 | $0.00078 | $0.01111 |
| Opus 5.5 | $0.00031 | $0.00444 |
| Sonnet 5.5 | $0.00016 | $0.00222 |
| Haiku 4.5 | $0.00008 | $0.00111 |
Grade A, and why
brand-guidelines 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brand consistency
The job of this skill is to keep what you build feel like it came from one place. When the operator or user has defined a brand — colors, fonts, voice — every page, component, and email must read as part of the same system.
Three modes
1. Apply an existing brand
If the project has any of the following, read them BEFORE writing any visual code:
tailwind.config.{js,ts}→ brand tokens (colors, fonts) live intheme.extendsrc/styles/globals.cssorsrc/styles/tokens.css→ CSS custom propertiesDESIGN.md,BRAND.md,tokens.jsonat repo root → designer hand-offcomponents/ui/from shadcn → already-tuned primitives; use them, don't rebuildpublic/logo.svgorpublic/brand/→ official assets
Reuse the tokens verbatim. Do NOT invent new colors. Do NOT replace the brand font with your favorite. Identity preservation wins over personal aesthetic.
2. Establish a new brand (no prior assets)
If no brand tokens exist, build one before scaffolding any pages. The brand is the design system; pages are instances of it.
- Choose a color strategy from
../frontend-design/references/design-rules.md(Restrained / Committed / Full palette / Drenched). - Pick a primary brand color in OKLCH based on mood and audience. Avoid the saturated AI defaults (cyan-on-dark, purple-to-blue gradients, cream/sand bodies).
- Compose the rest of the palette around it: bg, surface, ink, accent, muted. Tinted neutrals get 0.005-0.015 chroma toward the brand hue.
- Pick typography: one display family + one body family (+ optional mono). Pair on a contrast axis (serif + sans, geometric + humanist). Avoid Inter, Roboto, Open Sans as the primary.
- Pick a voice: 2-3 adjectives ("warm, precise, direct" — not "professional and modern"). Every copy block must read in that voice.
- Commit to disk: write the brand to
src/styles/tokens.css(CSS vars),tailwind.config.ts(theme.extend), and a shortBRAND.mdat repo root that records the why so future turns don't drift.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 67 lines · 78 tokens per session scan A dc0892cbe0a6
brand-guidelines is a skill published in the GitHub repository agentry-ai/agentry (6 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 78 tokens to every session and 1,111 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 2026-08-31.
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