colorize

A design review and editing workflow that adds deliberate colour to interfaces that look overly grey or uniform. It first considers the audience, use case, brand personality, and existing brand colours.

In plain words
What is it for?
Use it to review colour choices and introduce colour into a monochrome interface, provided the necessary design context is available.
Why use it?
It helps avoid adding random colours that do not fit the product or its users. It provides a way to make a visually flat interface feel warmer and more expressive.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/childrentime/reactuse/colorize
Any agent
npx skills add childrentime/reactuse --skill colorize
Clone the repo
git clone --depth 1 https://github.com/childrentime/reactuse

Made for: Claude Code, Codex.

Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,671 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00025 $0.01671
Opus 5 $0.00013 $0.00835
Sonnet 5 $0.00005 $0.00334
Haiku 4.5 $0.00003 $0.00167

Measured 2d ago against content hash 3243c4db2620, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

colorize 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 2d 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.

Origin

Copies of this mod

8 near-identical copies found in the catalogue:

  • colorize — 100% identical, 0 lines differ
  • colorize — 100% identical, 0 lines differ
  • colorize — 100% identical, 0 lines differ
  • colorize — 100% identical, 0 lines differ
  • colorize — 97% identical, 14 lines differ
  • colorize — 94% identical, 9 lines differ
  • i-colorize — 89% identical, 29 lines differ
  • colorize — 88% identical, 27 lines differ
packages/website-astro/.agents/skills/colorize/SKILL.md · 158 lines

How it starts

The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Strategically introduce color to designs that are too monochromatic, gray, or lacking in visual warmth and personality.

MANDATORY PREPARATION

Context Gathering (Do This First)

You cannot do a great job without having necessary context, such as target audience (critical), desired use-cases (critical), brand personality/tone, and especially existing brand colors.

Attempt to gather these from the current thread or codebase.

  1. If you don't find exact information and have to infer from existing design and functionality, you MUST STOP and STOP and call the AskUserQuestionTool to clarify. whether you got it right.
  2. Otherwise, if you can't fully infer or your level of confidence is medium or lower, you MUST STOP and call the AskUserQuestionTool to clarify. clarifying questions first to complete your context.

Do NOT proceed until you have answers. Guessing leads to generic AI slop colors.

Use frontend-design skill

Use the frontend-design skill for design principles and anti-patterns. Do NOT proceed until it has executed and you know all DO's and DON'Ts.


Assess Color Opportunity

Analyze the current state and identify opportunities:

  1. Understand current state:

    • Color absence: Pure grayscale? Limited neutrals? One timid accent?
    • Missed opportunities: Where could color add meaning, hierarchy, or delight?
    • Context: What's appropriate for this domain and audience?
    • Brand: Are there existing brand colors we should use?
  2. Identify where color adds value:

    • Semantic meaning: Success (green), error (red), warning (yellow/orange), info (blue)
    • Hierarchy: Drawing attention to important elements
    • Categorization: Different sections, types, or states
    • Emotional tone: Warmth, energy, trust, creativity
    • Wayfinding: Helping users navigate and understand structure
    • Delight: Moments of visual interest and personality

If any of these are unclear from the codebase, STOP and call the AskUserQuestionTool to clarify.

Read the full file on GitHub · 158 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. 2d ago First seen · 158 lines · 25 tokens per session scan A 3243c4db2620

Subscribe to this mod's changes

colorize is a skill published in the GitHub repository childrentime/reactuse (1,048 stars, last pushed 12d ago), licensed Unlicense. It adds 25 tokens to every session and 1,671 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 2026-08-30.

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