ccg

ccg is a skill for Claude Code, Codex from zereight/gitlab-mcp. It costs 48 tokens per session (615 once invoked), scanned A, original, MIT.

A workflow that asks Codex and Gemini, two different AI coding assistants, for separate views of a task and then combines their responses. It can compare technical decisions with usability and documentation concerns.

In plain words
What is it for?
Use it for architecture advice, code reviews, backend and frontend planning, alternative approaches, edge-case checks, and polishing user-facing documentation.
Why use it?
It provides multiple perspectives when correctness, design choices, or edge cases need cross-checking. If one command-line tool is unavailable, it can continue with the other.

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/zereight/gitlab-mcp/ccg
Any agent
npx skills add zereight/gitlab-mcp --skill ccg
Clone the repo
git clone --depth 1 https://github.com/zereight/gitlab-mcp

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for ccg

README.md
[![agentmods](https://agentmods.dev/badge/skills/zereight/gitlab-mcp/ccg.svg)](https://agentmods.dev/skills/zereight/gitlab-mcp/ccg)
Your own site
<a href="https://agentmods.dev/skills/zereight/gitlab-mcp/ccg"><img src="https://agentmods.dev/badge/skills/zereight/gitlab-mcp/ccg.svg" alt="Measured on agentmods" height="20"></a>
Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 615 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 $0.00048 $0.00615
Opus 5 $0.00024 $0.00308
Sonnet 5 $0.00010 $0.00123
Haiku 4.5 $0.00005 $0.00061

Measured 4d ago against content hash 6439319f98d5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ccg 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 4d 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

2 near-identical copies found in the catalogue:

  • ccg — 100% identical, 0 lines differ
  • ccg — 100% identical, 0 lines differ
.github/skills/ccg/SKILL.md · 101 lines

How it starts

The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CCG - Claude-Codex-Gemini Tri-Model Orchestration

Route a task through three AI models in parallel, then synthesize their outputs into one unified answer.

When to Use

  • Backend/analysis + frontend/UI work in one request
  • Code review from multiple perspectives
  • Cross-validation where models may disagree
  • Fast parallel input without full team orchestration

When NOT to Use

  • Simple, straightforward tasks → execute directly
  • Already clear on approach → use /omg-autopilot
  • Need coordinated multi-agent work → use /team

Requirements

  • Codex CLI: npm install -g @openai/codex
  • Gemini CLI: npm install -g @google/gemini-cli
  • If either CLI is unavailable, continue with whichever provider works

Execution Protocol

1. Decompose Request

Split the user request into:

  • Codex prompt: architecture, correctness, backend, risks, test strategy
  • Gemini prompt: UX/content clarity, alternatives, edge-case usability, docs polish
  • Synthesis plan: how to reconcile conflicts

2. Invoke Advisors

Run both advisors via CLI in parallel:

# Run in terminal
codex "<codex prompt>"
gemini "<gemini prompt>"

Or via VS Code's selectChatModels() API if available:

Promise.all([
  model_openai.sendRequest(codex_prompt),
  model_google.sendRequest(gemini_prompt)
])

3. Collect Results

Gather outputs from both advisors.

4. Synthesize

Return one unified answer with:

  • Agreed recommendations
  • Conflicting recommendations (explicitly called out)
  • Chosen final direction + rationale
  • Action checklist

Fallbacks

Scenario Action
One provider unavailable Continue with available + Claude synthesis
Both unavailable Fall back to Claude-only answer

Example

/ccg Review this PR - architecture/security via Codex and UX/readability via Gemini

Output:

=== CCG Synthesis ===

## Agreed
- Authentication middleware needs rate limiting
- Error messages should be more user-friendly

## Conflicting
- Codex: Use middleware pattern for validation
- Gemini: Use inline validation for simplicity
→ Chosen: Middleware pattern (consistency with existing codebase)

## Action Checklist
- [ ] Add rate limiting middleware
- [ ] Improve error messages in auth flow
- [ ] Extract validation to middleware layer

Read the full file on GitHub · 101 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. 4d ago First seen · 101 lines · 48 tokens per session scan A 6439319f98d5

Subscribe to this mod's changes

ccg is a skill published in the GitHub repository zereight/gitlab-mcp (1,939 stars, last pushed 2d ago), licensed MIT. It adds 48 tokens to every session and 615 once invoked, about $0.0002 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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