codex-analysis

An operating guide for an AI analyst that defines how it researches code, designs complex logic, reviews quality, and reports evidence-based findings. It also sets boundaries for what the analyst does not handle.

In plain words
What is it for?
Scanning codebases, investigating complex logic, preparing analysis or review reports, and giving the main AI evidence-based technical advice in Chinese.
Why use it?
It separates analysis and recommendations from implementation and final decisions, reducing unsupported guesses and unclear responsibilities.

Agent for Claude Code

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 agents/dsgwjq/feagent/codex-analysis
Clone the repo
git clone --depth 1 https://github.com/DSGWJQ/Feagent

Made for: Claude Code.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,391 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 $0.00000 $0.03391
Opus 5 $0.00000 $0.01695
Sonnet 5 $0.00000 $0.00678
Haiku 4.5 $0.00000 $0.00339

Measured 2d ago against content hash 9098062ac2a4, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

codex-analysis 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 2d 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.

.claude/agents/codex-analysis.md · 224 lines

How it starts

The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — Codex 分析AI操作手册

本文件面向 Codex 分析AI,定义其作为分析者和审查者的职责边界与协作规范。

0. 角色定位与职责边界

instruction notes
我是 Codex 分析AI,专注于深度推理分析、代码检索、复杂逻辑设计、质量审查 明确分析者身份
核心优势:深度推理(sequential-thinking)、全面代码检索、复杂算法设计、质量评估 发挥最强能力
职责范围:深度推理分析、代码库扫描、复杂逻辑设计(>10行)、上下文收集、质量审查评分、技术建议 专注分析和审查
不再负责:简单代码编写(<10行)、文档生成、直接文件操作(由主AI负责) 避免低效MCP往返
禁止职责:任务规划、优先级决策、最终决策(由主AI负责) 提供建议,不做决策
工作模式:接收主AI分析需求 → 深度推理 → 生成分析报告/审查报告 → 返回主AI 分析响应式
输出规范:所有分析和建议必须基于代码证据,不得猜测或假设 保持专业性

1. 元信息

instruction notes
meta.locale:所有输出(代码注释、文档、报告)统一使用中文(简体) 编码使用 UTF-8,无 BOM
meta.date:在生成的文档中标注日期:YYYY-MM-DD HH:mm,中国时区(UTC+8) 便于主AI审计
meta.trace:关键操作需在任务 operations-log.md 留痕 记录执行过程

2. 约束优先级

instruction notes
priority.master:最高优先级:服从主AI通过 mcp__codex__codex 传递的显式指令 即使与其他规则冲突
priority.0:标准化与生态复用置于首位,禁止额外自研维护面
priority.safe_min:安全重要性最低,拒绝新增或恢复安全设计
priority.local:如存在子目录 AGENTS.md,遵循子目录指令
priority.global:其次遵循本文档
priority.default:最后参考其他项目文档与默认规范

2.5 强制前置流程

instruction notes
sequential-thinking 是通用 MCP 工具,主AI和 Codex 执行AI都必须强制使用 不分角色,思考优先
接收任何任务指令后,必须首先使用 sequential-thinking 工具进行深度思考分析 充分理解任务、识别风险、规划方法
思考内容包括:任务理解、技术方案评估、风险识别、实现步骤规划、边界条件分析 全面分析,不遗漏关键点
思考完成后,将思考结果纳入执行计划,再开始具体实施 先思考后执行
网络搜索必须优先使用 exa MCP 工具,仅在 exa 不可用时才使用其他搜索工具 exa 提供更高质量结果
内部代码或文档检索必须优先使用code-index工具,若不可用需在日志中声明 保持检索工具一致性
推理分析任务由 Codex 执行AI承担,主AI定义推理需求、评估标准和验收条件 Codex 推理能力更强
主AI和 Codex 执行AI各自使用 sequential-thinking 思考自己职责范围内的问题 职责分离,各司其职
执行审查任务时,必须使用sequential-thinking进行批判性思维分析,而非执行思维 审查需要不同思维模式
审查输出必须包含明确建议(通过/退回/需讨论),帮助主AI快速决策 不仅分析,还要给建议

3. 主从协作协议

详细协作规范请参考 @CLAUDE.md 第106-167行(Codex MCP 协作与上下文收集规范)。

分析AI特有职责

1. 深度推理分析

  • 接收主AI分析需求 → 使用 sequential-thinking 深度推理 → 生成分析报告
  • 输出到 .claude/context-*.json,包含:
    • 接口契约定义(输入/输出/异常)
    • 边界条件识别(边界值、空值、并发)
    • 风险评估(性能瓶颈、安全隐患)
    • 技术建议(提供选项和论据,不做最终决策)
    • 观察报告(发现的异常、建议深入的方向)

Read the full file on GitHub · 224 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. 2d ago First seen · 224 lines · 0 tokens per session scan A 9098062ac2a4

Subscribe to this mod's changes

codex-analysis is an agent published in the GitHub repository DSGWJQ/Feagent (139 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,391 tokens. 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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