feishu-cursor-claw AGENTS.md

feishu-cursor-claw AGENTS.md is an instructions file for Codex, OpenCode from nongjun/feishu-cursor-claw. It costs 1,840 tokens per session, scanned A, original, MIT.

Repository instructions for feishu-cursor-claw, a service that sends Feishu messages to a local Cursor coding agent and returns the results.

In plain words
What is it for?
Use them when modifying message handling, memory search, voice input, scheduling, synchronization, deployment, or the bridge between Feishu and the coding agent.
Why use it?
They explain the system's purpose, technology choices, directory structure, and responsibilities of its main modules.

Instructions file for CodexOpenCode

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 instructions/nongjun/feishu-cursor-claw/agents-md
Clone the repo
git clone --depth 1 https://github.com/nongjun/feishu-cursor-claw

Made for: Codex, OpenCode.

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 feishu-cursor-claw AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/nongjun/feishu-cursor-claw/agents-md.svg)](https://agentmods.dev/instructions/nongjun/feishu-cursor-claw/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/nongjun/feishu-cursor-claw/agents-md"><img src="https://agentmods.dev/badge/instructions/nongjun/feishu-cursor-claw/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,840 This file is loaded in full into every session.
When invoked 1,840 The same file — it is already loaded in full.
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 $0.01840 $0.01840
Opus 5 $0.00920 $0.00920
Sonnet 5 $0.00368 $0.00368
Haiku 4.5 $0.00184 $0.00184

Measured 5d ago against content hash 48f9639ccdce, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

feishu-cursor-claw AGENTS.md 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 5d 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.

AGENTS.md · 150 lines

How it starts

The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — feishu-cursor-claw(虾群平台版)

本文件是 AI 编码助手理解本项目的入口。所有信息矛盾时以 文档/ 目录为准。


项目定位

飞书 → Cursor AI 远程遥控桥接服务。用户在飞书发消息,server 自动转发给本地 Cursor Agent CLI 执行,执行结果通过飞书卡片回传。灵感来自 OpenClaw。


技术栈

技术
运行时 Bun 1.x + TypeScript(直接运行,无需编译)
飞书 SDK @larksuiteoapi/node-sdk(WebSocket 长连接)
数据库 SQLite(Bun 内置,记忆向量索引 + FTS5)
语音 火山引擎豆包 STT → 本地 whisper-cpp 兜底
向量 火山引擎豆包 Embedding API
部署 macOS launchd(service.sh 管理)

目录结构

虾群平台版/
├── server.ts              # 主服务入口:飞书 WebSocket → Cursor Agent CLI
├── bridge.ts              # OpenAI API 桥接(供 OpenClaw 调用)
├── memory.ts              # 记忆管理器 v2(SQLite + 向量 + FTS5)
├── memory-tool.ts         # 记忆 CLI(Cursor Agent 通过 shell 调用)
├── scheduler.ts           # 定时任务调度器(cron-jobs.json 驱动)
├── heartbeat.ts           # 心跳系统(定期触发 HEARTBEAT.md 检查)
├── sync-apple-notes.ts    # Apple Notes 同步
├── backfill-embeddings.ts # 向量嵌入回填工具
├── feishu/                # 飞书集成(17 个 .ts 文件)
│   ├── client.ts          # 飞书 SDK 客户端
│   ├── send.ts            # 消息发送
│   ├── streaming-card.ts  # 流式卡片更新
│   ├── mention.ts         # @提及处理
│   └── types.ts           # 类型定义
├── templates/             # 工作区初始化模板
├── plugins/               # 插件系统
│   └── turix-cua/         #   桌面操控代理(AI 视觉 + 鼠标键盘操控)
├── 瑞小美-harness/        # AI 编程辅助配置工具包
├── .cursor/               # 本项目 Cursor 配置
├── 参考代码/              # 参考项目集合(不参与构建)
├── 文档/                  # 结构化知识库(唯一真相源)
├── 架构.md                # 系统架构鸟瞰图
├── .env / .env.example    # 环境变量
├── package.json           # 项目依赖
└── service.sh / setup.sh  # 部署脚本

模块职责与依赖

进程模型

单进程架构,server.ts 是唯一的进程入口。所有模块在同一进程内运行。

模块关系

  • server.ts — 主进程,实例化 memory.ts、scheduler.ts、heartbeat.ts,导入 feishu/ 模块
  • memory.ts — 被 server.ts 实例化,提供记忆读写能力
  • memory-tool.ts — 独立 CLI 进程,供 Cursor Agent 通过 shell 调用记忆系统
  • scheduler.ts — 被 server.ts 实例化,读取 cron-jobs.json 驱动定时任务
  • heartbeat.ts — 被 server.ts 实例化,定期触发 HEARTBEAT.md 检查
  • bridge.ts — 独立服务,提供 OpenAI 兼容 API(供 OpenClaw 调用)
  • feishu/ — 飞书功能集合,被 server.ts 通过 SDK 导入
  • plugins/turix-cua/ — 独立 Python 进程,通过 turix.sh 启动,AI 截屏→理解→操控鼠标键盘完成桌面任务

Read the full file on GitHub · 150 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. 5d ago First seen · 150 lines · 1,840 tokens per session scan A 48f9639ccdce

Subscribe to this mod's changes

feishu-cursor-claw AGENTS.md is an instructions file published in the GitHub repository nongjun/feishu-cursor-claw (14 stars, last pushed 1mo ago), licensed MIT. It adds 1,840 tokens to every session, about $0.0092 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.