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/resciencelab/tryskills/colorizenpx skills add ReScienceLab/TrySkills --skill colorizegit clone --depth 1 https://github.com/ReScienceLab/TrySkillsWhat 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 | $0.00053 | $0.01552 |
| Opus 5 | $0.00026 | $0.00776 |
| Sonnet 5 | $0.00011 | $0.00310 |
| Haiku 4.5 | $0.00005 | $0.00155 |
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.
This is a copy
78% identical to colorize — 27 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 — 143 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
Invoke /impeccable — it contains design principles, anti-patterns, and the Context Gathering Protocol. Follow the protocol before proceeding — if no design context exists yet, you MUST run /impeccable teach first. Additionally gather: existing brand colors.
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 directly to clarify what you cannot infer.
CRITICAL: More color ≠ better. Strategic color beats rainbow vomit every time. Every color should have a purpose.
Plan Color Strategy
Create a purposeful color introduction plan:
- Color palette: What colors match the brand/context? (Choose 2-4 colors max beyond neutrals)
- Dominant color: Which color owns 60% of colored elements?
- Accent colors: Which colors provide contrast and highlights? (30% and 10%)
- Application strategy: Where does each color appear and why?
IMPORTANT: Color should enhance hierarchy and meaning, not create chaos. Less is more when it matters more.
Introduce Color Strategically
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.
- 2d ago First seen · 143 lines · 53 tokens per session scan A 60b8240ad2e5
colorize is a skill published in the GitHub repository ReScienceLab/TrySkills (2 stars, last pushed 3mo ago), licensed MIT. It adds 53 tokens to every session and 1,552 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 78% identical to colorize, differing in 27 lines, and is treated as a copy.
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cpu-profile-analysis
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agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.