generate-agent-instructions

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Analyze this codebase to generate or update

AGENTS.md

for guiding AI coding agents.

Important: You can completely ignore the CLAUDE.md file, if it exists, as it's a duplicate of AGENTS.md.

Do a full deep dive into the codebase so AI agents always have enough context to prevent them making assumptions and mistakes.

Focus on discovering the essential knowledge that would help an AI agent be immediately productive in this codebase. Consider aspects like:

The "big picture" architecture that requires reading multiple files to understand - major components, service boundaries, data flows, and the "why" behind structural decisions
Critical developer workflows (builds, tests, debugging) especially commands that aren't obvious from file inspection alone
Project-specific conventions and patterns that differ from common practices
Integration points, external dependencies, and cross-component communication patterns

Source existing AI conventions from

AGENTS.md

Guidelines:

If
```
AGENTS.md
```
exists, merge intelligently - preserve valuable content while updating outdated sections
Write concise, actionable instructions (~20-50 lines) using markdown structure
Include specific examples from the codebase when describing patterns
Avoid generic advice ("write tests", "handle errors") - focus on THIS project's specific approaches
Document only discoverable patterns, not aspirational practices
Reference key files/directories that exemplify important patterns

Update

AGENTS.md

for the user, then ask for feedback on any unclear or incomplete sections to iterate.

分析当前代码库，生成或更新用于指导AI编码Agent的

AGENTS.md

文件。

注意：如果存在CLAUDE.md文件，你可以完全忽略它，因为它是AGENTS.md的副本。

请深入全面地调研代码库，确保AI Agent总能获得足够的上下文，避免它们做出错误假设和操作失误。

重点挖掘能帮助AI Agent快速上手该代码库开展工作的核心知识，可参考以下维度：

从现有

AGENTS.md

中提取已有的AI相关规范。

编写规范：

为用户更新

AGENTS.md

后，可针对任何不明确或不完整的部分询问用户反馈，以便迭代优化。