CCG is a command-line workflow engine that coordinates Claude, Codex, Gemini, and other models as specialized collaborators on coding tasks. It is used to analyze requests, choose a strategy, delegate work to model-specific roles, and combine their results. The catalogue entries provide the skills, commands, agents, and plugin that implement this workflow.
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 skills add fengshao1227/ccg-workflow --skill optimizegit clone --depth 1 https://github.com/fengshao1227/ccg-workflowWrote 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/fengshao1227/ccg-workflow/optimize)<a href="https://agentmods.dev/skills/fengshao1227/ccg-workflow/optimize"><img src="https://agentmods.dev/badge/skills/fengshao1227/ccg-workflow/optimize/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/fengshao1227/ccg-workflow/optimize"><img src="https://agentmods.dev/badge/skills/fengshao1227/ccg-workflow/optimize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00052 | $0.01877 |
| Opus 5.5 | $0.00021 | $0.00751 |
| Sonnet 5.5 | $0.00010 | $0.00375 |
| Haiku 4.5 | $0.00005 | $0.00188 |
Grade A, and why
optimize 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- optimize — 98% identical, 2 lines differ
- optimize — 98% identical, 2 lines differ
- optimize — 94% identical, 12 lines differ
- optimize — 92% identical, 6 lines differ
- optimize — 92% identical, 6 lines differ
- optimize — 92% identical, 99 lines differ
- optimize — 92% identical, 7 lines differ
- optimize — 92% identical, 7 lines differ
How it starts
The opening of the file, as written. The whole thing — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Identify and fix performance issues to create faster, smoother user experiences.
Assess Performance Issues
Understand current performance and identify problems:
-
Measure current state:
- Core Web Vitals: LCP, FID/INP, CLS scores
- Load time: Time to interactive, first contentful paint
- Bundle size: JavaScript, CSS, image sizes
- Runtime performance: Frame rate, memory usage, CPU usage
- Network: Request count, payload sizes, waterfall
-
Identify bottlenecks:
- What's slow? (Initial load? Interactions? Animations?)
- What's causing it? (Large images? Expensive JavaScript? Layout thrashing?)
- How bad is it? (Perceivable? Annoying? Blocking?)
- Who's affected? (All users? Mobile only? Slow connections?)
CRITICAL: Measure before and after. Premature optimization wastes time. Optimize what actually matters.
Optimization Strategy
Create systematic improvement plan:
Loading Performance
Optimize Images:
- Use modern formats (WebP, AVIF)
- Proper sizing (don't load 3000px image for 300px display)
- Lazy loading for below-fold images
- Responsive images (
srcset,pictureelement) - Compress images (80-85% quality is usually imperceptible)
- Use CDN for faster delivery
<img
src="hero.webp"
srcset="hero-400.webp 400w, hero-800.webp 800w, hero-1200.webp 1200w"
sizes="(max-width: 400px) 400px, (max-width: 800px) 800px, 1200px"
loading="lazy"
alt="Hero image"
/>
Reduce JavaScript Bundle:
- Code splitting (route-based, component-based)
- Tree shaking (remove unused code)
- Remove unused dependencies
- Lazy load non-critical code
- Use dynamic imports for large components
// Lazy load heavy component
const HeavyChart = lazy(() => import('./HeavyChart'));
Optimize CSS:
- Remove unused CSS
- Critical CSS inline, rest async
- Minimize CSS files
- Use CSS containment for independent regions
Optimize Fonts:
- Use
font-display: swaporoptional - Subset fonts (only characters you need)
- Preload critical fonts
- Use system fonts when appropriate
- Limit font weights loaded
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 · 267 lines · 52 tokens per session scan A 09e7ee25fe09
optimize is a skill published in the GitHub repository fengshao1227/ccg-workflow (5,943 stars, last pushed yesterday), licensed MIT. It adds 52 tokens to every session and 1,877 once invoked, about $0.0002 per session on Opus 5.5. 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.
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