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/datascienceworld-kan/vinagent/brand-guidelinesnpx skills add datascienceworld-kan/vinagent --skill brand-guidelinesgit clone --depth 1 https://github.com/datascienceworld-kan/vinagentWrote 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/datascienceworld-kan/vinagent/brand-guidelines)<a href="https://agentmods.dev/skills/datascienceworld-kan/vinagent/brand-guidelines"><img src="https://agentmods.dev/badge/skills/datascienceworld-kan/vinagent/brand-guidelines.svg" alt="Measured on agentmods" 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 | $0.00050 | $0.00518 |
| Opus 5 | $0.00025 | $0.00259 |
| Sonnet 5 | $0.00010 | $0.00104 |
| Haiku 4.5 | $0.00005 | $0.00052 |
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 5d 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 brand-guidelines — 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.
What it actually says
Anthropic Brand Styling
Overview
To access Anthropic's official brand identity and style resources, use this skill.
Keywords: branding, corporate identity, visual identity, post-processing, styling, brand colors, typography, Anthropic brand, visual formatting, visual design
Brand Guidelines
Colors
Main Colors:
- Dark:
#141413- Primary text and dark backgrounds - Light:
#faf9f5- Light backgrounds and text on dark - Mid Gray:
#b0aea5- Secondary elements - Light Gray:
#e8e6dc- Subtle backgrounds
Accent Colors:
- Orange:
#d97757- Primary accent - Blue:
#6a9bcc- Secondary accent - Green:
#788c5d- Tertiary accent
Typography
- Headings: Poppins (with Arial fallback)
- Body Text: Lora (with Georgia fallback)
- Note: Fonts should be pre-installed in your environment for best results
Features
Smart Font Application
- Applies Poppins font to headings (24pt and larger)
- Applies Lora font to body text
- Automatically falls back to Arial/Georgia if custom fonts unavailable
- Preserves readability across all systems
Text Styling
- Headings (24pt+): Poppins font
- Body text: Lora font
- Smart color selection based on background
- Preserves text hierarchy and formatting
Shape and Accent Colors
- Non-text shapes use accent colors
- Cycles through orange, blue, and green accents
- Maintains visual interest while staying on-brand
Technical Details
Font Management
- Uses system-installed Poppins and Lora fonts when available
- Provides automatic fallback to Arial (headings) and Georgia (body)
- No font installation required - works with existing system fonts
- For best results, pre-install Poppins and Lora fonts in your environment
Color Application
- Uses RGB color values for precise brand matching
- Applied via python-pptx's RGBColor class
- Maintains color fidelity across different systems
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.
- 5d ago First seen · 74 lines · 50 tokens per session scan A 1120b3769e29
brand-guidelines is a skill published in the GitHub repository datascienceworld-kan/vinagent (74 stars, last pushed 5mo ago), licensed MIT. It adds 50 tokens to every session and 518 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to brand-guidelines, differing in 0 lines, and is treated as a copy.
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