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📊 公开数据一览
| 📦 榜单安装量 | 100 |
| ⭐ GitHub Stars | 28(fork 13) |
| 🗓️ 最近推送 | 2026-06-29 |
| 🌱 项目创建 | 2025-10-17 |
| 💻 语言 / License | Python · MIT |
| 🐛 开放Issue | 2 |
📝 工具简介
Claude Cortex安全编码实践技能。
📖 怎么用
安装方式二选一:macOS 用 Homebrew 跑 `brew tap NickCrew/cortex && brew install cortex`,或者用 pipx 跑 `pipx install claude-cortex`。装好后用 `uvx --from claude-cortex cortex-minimal --help` 查看帮助。核心机制是让 Codex 写代码、Claude 审查、Codex 修复、Claude 复审,最多循环 3 轮;测试和 lint 也有类似的多模型交叉验证流程,确保没有代理给自己打分。
📋 迷你测评
Claude Cortex的安全编码实践技能。亮点是聚焦安全,针对性强。但具体覆盖哪些漏洞类型或检查项,简介没说,适合安全敏感项目参考。
📄 README 要点
这是个叫Cortex的开发编排框架,专门协调Claude Code、Codex和Gemini这些AI代理一起干活。它的核心原则是“写代码的代理绝不审查自己的代码”——比如Codex写完功能,就交给Claude审,再换另一个模型家族审,同模型审查只能当最后手段。每次审查都会生成带严重级别和通过/失败结论的结构化报告。这样搞的好处是强制质量关卡,有独立的代码审查、测试覆盖审计和lint检查,整个开发流程可审计、有结构,不让AI自己给自己打分。
查看英文原文
Multi model development orchestration for Claude Code, Codex, and Gemini. Documentation · Install · Quick Start Cortex is a development orchestration framework that coordinates AI agents across model providers. It enforces quality gates — independent code review, test coverage audits, and lint checks — so that no agent grades its own homework. The result is a structured, auditable development workflow where Claude, Codex, and Gemini collaborate with built in verification at every step. How It Works Multi model review with no self review Cortex's core principle: the agent that writes the code never reviews it. When Codex implements a feature, the review is routed to Claude first, then to a different model family, with same model review as a last resort. Every review produces a structured artifact with severity levels and a pass/fail verdict. [安装/使用命令见下方] Agent loops: progressive quality gates Every code change flows through three sequential loops, each with circuit breakers and escalation rules: [安装/使用命令见下方] P0/P1 findings must be resolved before the loop exits. P2/P3 findings are filed as issues automatically. If circuit breakers trigger, the agent stops and escalates to a human — no infinite remediation loops. Skill recommendations Skills are suggested automatically as you work via a two layer pipeline: fast keyword matching on every prompt ( 50ms), with optional semantic matching for deeper recommendations. The TUI runs a background watch daemon for continuous suggestions. What's Inside Path Purpose agents/ Agent definitions (specialized reviewers, implementers) skills/ Reusable skill modules — workflow guidance, review prompts, quality standards rules/ Behavioral guardrails and coding conventions hooks/ Automation hooks (skill suggestions, validation gates) claude ctx py/ Python CLI and TUI implementation Key skills agent loops — The core workflow: structured implementation with independent review, test audit, and lint gates. Includes provider aware
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