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 biggora/claude-plugins-registry --skill brand-guidelinesgit clone --depth 1 https://github.com/biggora/claude-plugins-registryWrote 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/biggora/claude-plugins-registry/brand-guidelines)<a href="https://agentmods.dev/skills/biggora/claude-plugins-registry/brand-guidelines"><img src="https://agentmods.dev/badge/skills/biggora/claude-plugins-registry/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/biggora/claude-plugins-registry/brand-guidelines"><img src="https://agentmods.dev/badge/skills/biggora/claude-plugins-registry/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 | $0.00166 | $0.02993 |
| Opus 5 | $0.00083 | $0.01496 |
| Sonnet 5 | $0.00033 | $0.00599 |
| Haiku 4.5 | $0.00017 | $0.00299 |
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 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 — 336 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brand Guidelines Creator
Create professional brand guidelines documents (brand books) for any brand. Collect brand assets through a structured interview, then generate a self-contained HTML brand book.
Output: Single self-contained HTML file — no dependencies, opens in any browser, printable to PDF via Ctrl+P.
Pipeline
[User Request]
|
v
[Detect Mode] -----> Express / Guided / Discovery
|
v
[Brand Interview] 6 stages, batched questions
|
v
[Confirmation] Summary for user approval
|
v
[Generate HTML] Self-contained brand book
|
v
[brand-guidelines.html]
Modes
Determine the mode from the user's input:
Express — User provides brand assets upfront ("Here are my colors: #2563EB, #1E293B; font: Inter; brand name: Acme"). Validate inputs, fill gaps with smart defaults, confirm, generate.
Guided — User has some ideas but needs structure ("I want a brand guide for my SaaS startup"). Run the full 6-stage interview with suggestions.
Discovery — User starts from scratch ("Help me create a brand identity"). Start from personality/values, derive palette and typography suggestions, then proceed through all stages.
Brand Interview Protocol
Present questions in batches by stage — not one at a time. Allow "skip" or "default" for any stage. After all stages, present a confirmation summary before generating.
Stage 1: Brand Identity (required)
Brand name:
Tagline / slogan (optional):
Industry / domain:
Brand personality (3-5 adjectives, e.g. bold, friendly, minimal):
Stage 2: Color Palette
Primary color (hex or describe, e.g. "deep blue"):
Secondary color:
Accent color(s):
Background light:
Background dark:
Semantic colors — success / warning / error / info (or "default"):
If user provides personality adjectives but no colors, generate 2-3 palette suggestions. Read references/brand-interview-guide.md for the personality-to-palette algorithm and industry defaults.
What ships with it
4 files 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.
- 8d ago First seen · 336 lines · 166 tokens per session scan A de37743634fc
brand-guidelines is a skill published in the GitHub repository biggora/claude-plugins-registry (2 stars, last pushed 10d ago), licensed MIT. It adds 166 tokens to every session and 2,993 once invoked, about $0.0008 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 2026-08-31.
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