Borrowing it
Nothing to install: this file belongs to FavioVazquez/learnship. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/FavioVazquez/learnship/main/.windsurf/skills/impeccable/colorize/SKILL.mdgit clone --depth 1 https://github.com/FavioVazquez/learnshipWrote 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/faviovazquez/learnship/colorize)<a href="https://agentmods.dev/skills/faviovazquez/learnship/colorize"><img src="https://agentmods.dev/badge/skills/faviovazquez/learnship/colorize/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/faviovazquez/learnship/colorize"><img src="https://agentmods.dev/badge/skills/faviovazquez/learnship/colorize.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 | $0.00025 | $0.01650 |
| Opus 5.5 | $0.00010 | $0.00660 |
| Sonnet 5.5 | $0.00005 | $0.00330 |
| Haiku 4.5 | $0.00003 | $0.00165 |
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 1mo 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
91% identical to colorize — 26 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.
How it starts
The opening of the file, as written. The whole thing — 159 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.
- If you don't find exact information and have to infer from existing design and functionality, you MUST STOP and Ask the user: whether you got it right.
- Otherwise, if you can't fully infer or your level of confidence is medium or lower, you MUST Ask the user: 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:
-
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?
-
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, Ask the user:
CRITICAL: More color ≠ better. Strategic color beats rainbow vomit every time. Every color should have a purpose.
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.
- 1mo ago First seen · 159 lines · 25 tokens per session scan A 5449b7f13450
colorize is a skill published in the GitHub repository FavioVazquez/learnship (62 stars, last pushed 5mo ago), licensed MIT. It adds 25 tokens to every session and 1,650 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to colorize, differing in 26 lines, and is treated as a copy.
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