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 verify-qualitygit 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/verify-quality)<a href="https://agentmods.dev/skills/fengshao1227/ccg-workflow/verify-quality"><img src="https://agentmods.dev/badge/skills/fengshao1227/ccg-workflow/verify-quality/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/verify-quality"><img src="https://agentmods.dev/badge/skills/fengshao1227/ccg-workflow/verify-quality.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 | $0.00064 | $0.01096 |
| Opus 5 | $0.00032 | $0.00548 |
| Sonnet 5 | $0.00013 | $0.00219 |
| Haiku 4.5 | $0.00006 | $0.00110 |
Grade A, and why
verify-quality 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 9d 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
2 near-identical copies found in the catalogue:
- verify-quality — 100% identical, 0 lines differ
- verify-quality — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
⚖ 校验关卡 · 代码质量
核心原则
代码质量 = 可读性 + 可维护性 + 可测试性
劣质代码是技术债，技术债是道基裂痕
复杂度是 bug 的温床
自动检查
运行质量检查脚本（跨平台）：
# 在 skill 目录下运行
node scripts/quality_checker.js <扫描路径>
node scripts/quality_checker.js <扫描路径> -v # 详细模式
node scripts/quality_checker.js <扫描路径> --json # JSON 输出
检测指标
复杂度指标
| 指标 | 阈值 | 超标后果 |
|---|---|---|
| 圈复杂度 | ≤ 10 | 🟠 警告，建议拆分 |
| 函数长度 | ≤ 50 行 | 🟠 警告，建议拆分 |
| 文件长度 | ≤ 500 行 | 🟡 提示，考虑拆分 |
| 参数数量 | ≤ 5 | 🟠 警告，考虑封装 |
| 嵌套深度 | ≤ 4 | 🟠 警告，建议重构 |
| 行长度 | ≤ 120 | 🔵 提示 |
命名规范
| 类型 | 规范 | 示例 |
|---|---|---|
| 类名 | PascalCase | UserService, HttpClient |
| 函数名 | snake_case | get_user, process_data |
| 常量 | UPPER_SNAKE | MAX_RETRY, DEFAULT_TIMEOUT |
| 变量 | snake_case | user_id, total_count |
代码异味
| 异味 | 说明 | 严重度 |
|---|---|---|
| 重复代码 | 相似代码块 > 10 行 | 🟠 High |
| 过长参数列表 | 参数 > 5 个 | 🟡 Medium |
| 魔法数字 | 未命名的常量 | 🟡 Medium |
| 死代码 | 未使用的函数/变量 | 🔵 Low |
| 注释代码 | 被注释的代码块 | 🔵 Low |
自动触发时机
| 场景 | 触发条件 |
|---|---|
| 复杂模块 | 代码行数 > 200 |
| 重构完成 | 重构任务完成时 |
| 代码审查 | PR/MR 审查时 |
| 提交前 | 代码提交前检查 |
校验流程
1. 扫描代码文件
2. 计算复杂度指标
3. 检测代码异味
4. 验证命名规范
5. 输出质量校验报告
校验报告格式
## 代码质量校验报告
✓ 通过 | ✗ 未通过
### 复杂度指标
- 平均函数复杂度: N
- 超标函数数: N
- 最大文件行数: N
### 代码异味
- 🟠 High: N
- 🟡 Medium: N
- 🔵 Low: N
### 问题清单
| 文件 | 行号 | 类型 | 严重度 | 描述 |
|------|------|------|--------|------|
| ... | ... | ... | ... | ... |
### 结论
可交付 / 需重构后交付
重构建议
降低复杂度
# 🔴 高复杂度 - 道基不稳
def process(data):
if condition1:
if condition2:
if condition3:
# 深层嵌套
pass
# ✅ 低复杂度 - 道基稳固
def process(data):
if not condition1:
return
if not condition2:
return
if not condition3:
return
# 主逻辑
消除重复
# 🔴 重复代码 - 异端
def func1():
# 10行相同逻辑
pass
def func2():
# 10行相同逻辑
pass
# ✅ 提取公共函数 - 正道
def common_logic():
# 公共逻辑
pass
def func1():
common_logic()
def func2():
common_logic()
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 161 lines · 64 tokens per session scan A 58bc95a2fe0a
verify-quality is a skill published in the GitHub repository fengshao1227/ccg-workflow (5,879 stars, last pushed 6d ago), licensed MIT. It adds 64 tokens to every session and 1,096 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 2026-08-30.
Other skills, from other repositories
code-review-workflow
Review a change in a fixed order — context, correctness, security, then style — and write feedback that is actionable and ranked by severity. Use when the user asks for a code review, wants a pull request or diff reviewed before merge, asks whether a change is safe to ship, or when the task involves reviewing a patch…
refactoring-workflow
Improve the structure of existing code without changing its behaviour, in small verified steps under a green test suite. Use when the user asks to refactor, clean up, restructure or simplify code, wants to reduce duplication or coupling, is preparing a codebase for a feature it cannot currently accommodate, or when…
plan-eng-review
Eng manager-mode plan review. Lock in the execution plan — architecture, data flow, diagrams, edge cases, test coverage, performance. Walks through issues interactively with opinionated recommendations. Use when asked to "review the architecture", "engineering review", or "lock in the plan". Proactively suggest when…
autoplan
Auto-review pipeline — reads the full CEO, design, eng, and DX review skills from disk and runs them sequentially with auto-decisions using 6 decision principles. Surfaces taste decisions (close approaches, borderline scope, codex disagreements) at a final approval gate. One command, fully reviewed plan out. Use when…
pre-landing-review
Pre-landing PR review. Analyzes diff against the base branch for SQL safety, LLM trust boundary violations, conditional side effects, and other structural issues. Use when explicitly asked for the specialized pre-landing workflow. Product /review requests are handled by OpenBitFun's unified Review mechanism instead.…
pr-review-canvas
Create a OpenBitFun Canvas for reviewing a pull request, branch diff, or change set with Cursor-style diff cards, review maps, risk callouts, and focused reviewer flow. Use when the user asks for a PR review canvas, diff walkthrough, change-set overview, or visual review summary.