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 agentmods add skills/fengshao1227/ccg-workflow/optimizenpx 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.svg" alt="Measured on agentmods" 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 | $0.00052 | $0.01877 |
| Opus 5 | $0.00026 | $0.00938 |
| Sonnet 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 today.
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, 7 lines differ
- optimize — 92% identical, 99 lines differ
- optimize — 92% identical, 6 lines differ
- optimize — 92% identical, 6 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.
- today First seen · 267 lines · 52 tokens per session scan A 09e7ee25fe09
optimize is a skill published in the GitHub repository fengshao1227/ccg-workflow (5,872 stars, last pushed yesterday), licensed MIT. It adds 52 tokens to every session and 1,877 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 2026-09-03.
Other skills, from other repositories
absolute-simplify
Use when the user wants to simplify, clean up, refactor, tidy, or refine code — their staged/unstaged git changes or a target file/path. Reduces complexity, flattens nesting, removes redundancy and dead code, scores each change by value (holding low-value churn), then runs tests to prove nothing broke. Invoke on…
absolute-ui
Build polished, intentional UIs with concrete CSS/Tailwind values — typography, color, layout, spacing, dark mode, accessibility, animations, components. Encodes specific, opinionated rules with exact values, not vague advice. Covers buttons, cards, forms, tables, navigation, dashboards, landing pages, onboarding, and…
absolute-work
End-to-end, phase-gated SDLC for AI coding agents: relentless design interview → reviewed spec → dependency-graphed task board → safe-wave TDD execution → verification → converge. Handles features, bugs, refactors, greenfield projects, planning breakdowns, and migrations. Triggers on "absolute work", "build this…
absolute-init
One-time setup for absolute: interview how you want it to behave (output style, autonomy, TDD strictness, spec dir, families) + detect the stack once, then write .absolute.config.json (project, committed) and /.absolute/config.json (user defaults + per-project overrides). Every other absolute- command reads it instead…
absolute-spec
Lightweight standalone design spec for AI coding agents: codebase scan → bounded clarify pass (3–5 questions, not a grill) → reviewed design doc written to docs/plans/ → independent scored review → stop. No task board, no build. Use when you want a spec to discuss, hand off, or review before committing to…
absolute-docs
Diátaxis-driven documentation for AI coding agents: write, improve, or audit tutorials, how-tos, reference, explanation, and developer docs (README, CONTRIBUTING, ADRs). Detects the docs stack; gates on the outline before writing prose; verifies every claim against the code before it ships. Triggers on "absolute…