image-generation-branding

image-generation-branding is a skill for Claude Code, Codex from cxcscmu/SkillLearnBench. It costs 22 tokens per session (154 once invoked), scanned A, original, MIT.

Guidelines for generating technical images that follow a fixed brand palette, simple visual style, consistent line weights, and specified typography.

In plain words
What is it for?
Use it to plan branded illustrations by mapping components to colour tokens and checking the background, hierarchy, and visual style.
Why use it?
It reduces visual inconsistencies such as unintended gradients, colours, shadows, or unclear technical layers.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to plan branded illustrations by mapping components to colour tokens and checking the background, hierarchy, and visual style.

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Install with agentmods
npx agentmods add skills/cxcscmu/skilllearnbench/image-generation-branding
Install

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.

Any agent
npx skills add cxcscmu/SkillLearnBench --skill image-generation-branding
Clone the repo
git clone --depth 1 https://github.com/cxcscmu/SkillLearnBench

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for image-generation-branding

README.md
[![agentmods](https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/image-generation-branding.svg)](https://agentmods.dev/skills/cxcscmu/skilllearnbench/image-generation-branding)
Your own site
<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/image-generation-branding"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/image-generation-branding.svg" alt="Measured on agentmods" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 154 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00022 $0.00154
Opus 5 $0.00011 $0.00077
Sonnet 5 $0.00004 $0.00031
Haiku 4.5 $0.00002 $0.00015

Measured 4d ago against content hash 67b3ad6e949f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

image-generation-branding 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 4d 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.

skills/b1-one-shot-gemini-3.1-flash-lite-preview/anthropic-poster-design/image-generation-branding/SKILL.md · 17 lines

What it actually says

Branding Principles

  • Minimalism: Avoid gradients, shadows, or high-saturation colors unless explicitly requested.
  • Palette Control: Utilize strict hex-based mapping for corporate components.
  • Visual Hierarchy: Clearly separate technical layers using consistent line weights (Muted Mid Gray).
  • Typography: Use sans-serif, low-weight headers for technical documentation.

Implementation Checklist

  1. Identify all required components (e.g., Casing, PCB, Battery).
  2. Map components to requested color tokens.
  3. Ensure background matches the Brand Identity Light.
  4. Final Review: Compare against core brand tokens for saturation and style adherence.
Changes

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.

  1. 4d ago First seen · 17 lines · 22 tokens per session scan A 67b3ad6e949f

Subscribe to this mod's changes

image-generation-branding is a skill published in the GitHub repository cxcscmu/SkillLearnBench (83 stars, last pushed 2mo ago), licensed MIT. It adds 22 tokens to every session and 154 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 2026-09-03.