color-accessibility-expert

color-accessibility-expert is a skill for Claude Code, Codex from vosslab/vosslab-skills. It costs 56 tokens per session (3,192 once invoked), scanned A, original, MIT.

A guide for finding and fixing text and image colors that do not have enough contrast for accessibility. WCAG is a set of web accessibility guidelines that includes minimum contrast requirements.

In plain words
What is it for?
Use it to audit palettes, repair contrast failures in source files, check dark-mode colors, inspect rendered screenshots, and document the result in a palette audit.
Why use it?
It replaces hard-to-read colors with measured alternatives while preserving their general hue, then checks the result again.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present. Also seen: mentions subagents.

Part of the vosslab-skills plugin — 42 skills, 14 agents shipped together

Good fit Use it to audit palettes, repair contrast failures in source files, check dark-mode colors, inspect rendered screenshots, and document the result in a palette audit.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/vosslab/vosslab-skills/color-accessibility-expert
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 vosslab/vosslab-skills --skill color-accessibility-expert
Clone the repo
git clone --depth 1 https://github.com/vosslab/vosslab-skills

Made for: Claude Code, Codex.

Or install vosslab-skills, the plugin that ships this one along with the rest of its 42 skills, 14 agents.

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 color-accessibility-expert

README.md
[![agentmods](https://agentmods.dev/badge/skills/vosslab/vosslab-skills/color-accessibility-expert/github.svg)](https://agentmods.dev/skills/vosslab/vosslab-skills/color-accessibility-expert)
Your own site
<a href="https://agentmods.dev/skills/vosslab/vosslab-skills/color-accessibility-expert"><img src="https://agentmods.dev/badge/skills/vosslab/vosslab-skills/color-accessibility-expert/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.

agentmods 80×15 button for color-accessibility-expert

Your own site · 80×15
<a href="https://agentmods.dev/skills/vosslab/vosslab-skills/color-accessibility-expert"><img src="https://agentmods.dev/badge/skills/vosslab/vosslab-skills/color-accessibility-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 56 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,192 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 $0.00056 $0.03192
Opus 5 $0.00028 $0.01596
Sonnet 5 $0.00011 $0.00638
Haiku 4.5 $0.00006 $0.00319

Measured 10d ago against content hash 106fbfe8f4b8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

color-accessibility-expert 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 10d ago.

The scan reads SKILL.md. This mod also ships 12 executable files (scripts/adjust_color.py, scripts/apply_color_fixes.py, scripts/audit_palette.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/experts/color-accessibility-expert/SKILL.md · 227 lines

How it starts

The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Color accessibility expert

Overview

Detect and fix WCAG color contrast across a repo. The primary outcome is a set of source files whose colors all pass: locate color literals, measure their contrast ratios, compute hue-preserving replacements for the failing ones, and apply those replacements directly to the source files with apply_color_fixes.py. Then re-audit to confirm every color passes, optionally spot-check contrast in rendered images, and record the audited result in docs/PALETTE_CONTRAST_AUDIT.md from evidence gathered during the current run. The audit file documents the fix; the fixed source is the deliverable.

Behavioral contract

This skill edits exactly two kinds of target-repo files, and both are first-class outcomes:

  • Color values in source files -- the primary deliverable. During a fix run (steps 3 and 4 below), replace each failing hex with the value adjust_color.py or audit_palette.py computes, applied through apply_color_fixes.py. This is the surface where the accessibility problem actually gets fixed.
  • docs/PALETTE_CONTRAST_AUDIT.md -- the per-repo palette audit that documents the fixed result. Write or refresh that file only through generate_palette_audit.py.

The generic WCAG method doc, docs/COLOR_CONTRAST_ACCESSIBILITY.md, is propagated read-only from starter-repo-template and assumed present. Cite it from the audit file, but never write it here.

Treat every other file in the target repo as read-only reference for this skill's own scripts, references, and generated output.

Ground every file path and color value in the generated audit table in files Read during the current run: the "Evidence rule" section below states the exact standard.

Project shape

Before step 1, frame the target: improve-existing (the repo has colors to audit and fix -- the common case) versus greenfield (the repo needs a palette created). Detection and both paths live in references/project_workflow.md. Classify one-off requests (single pair, one color, one image) with references/task_selection.md; route observed symptoms through references/topic_index.md.

Read the full file on GitHub · 227 lines

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. 10d ago First seen · 227 lines · 56 tokens per session scan A 106fbfe8f4b8

Subscribe to this mod's changes

color-accessibility-expert is a skill published in the GitHub repository vosslab/vosslab-skills (2 stars, last pushed 15d ago), licensed MIT. It adds 56 tokens to every session and 3,192 once invoked, about $0.0003 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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