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FengChaoSkills 蜂巢

CI PyPI License: MIT Python 3.9+

Agent 无关的项目业务事实账本:让 AI 会话在真实开发交付后自动沉淀"业务真相 + 落地证据",在新会话开始时按最小必要集合路由回这些记忆,并严格区分"当前事实"与"历史参考"。

FengChao is an agent-agnostic, Markdown + Git based business fact ledger for AI coding sessions: it captures business truth with evidence after real delivery, routes the minimal memory set into fresh sessions, and never confuses "current fact" with "historical reference".

零第三方依赖 · 零遥测 · 零网络请求 · 纯 Markdown + Git · 记忆数据永远属于你

它解决什么问题

AI 编程会话是无状态的。代码在 git 里,但业务语义只存在于对话中:为什么审核要分两级?"主管"指什么岗位?用户上个月否定过哪个方案?会话关闭,知识就死了。更危险的是记忆污染:把"讨论过"当"已实现"、把"随口一提"当"业务规则"、把"已废弃"当"当前行为"。

FengChao 用两个别人基本没做的设计解决这两个问题:

  1. 记忆的认识论分层:五级可信度 + 冲突优先级(business-context 当前真相 > task-records/changelog 落地证据 > implemented plan > conversation-records > proposed plan)。
  2. 否定记忆:用户明确拒绝过的方案会被记录,防止 AI 把被否掉的方案再提一遍。

与 Spec 工具(OpenSpec / Spec Kit)不冲突:它们管"接下来做什么"(事前),FengChao 管"业务认知为什么是现在这样"(事后),可共存。

60 秒 Quick Start

cd your-project

# 方式一(推荐):免安装一次性运行
uvx fengchao-skills init     # 或 pipx run fengchao-skills init
# 没有 uv?一次性安装:brew install uv(或直接用方式二,零前置依赖)

# 方式二(当前可用):git clone 后直接跑,零依赖
git clone https://github.com/HappyLeoYang/FengChaoSkills.git ~/FengChaoSkills
python3 ~/FengChaoSkills/skills/fengchao-business-memory/scripts/fengchao.py init

init 交互选择 agent(或 --agents claude,cursor,会自动探测已有的 .claude/、.cursor/ 等目录),然后立刻验证:

uvx fengchao-skills status    # 全绿即可(源码方式则用 python3 .../fengchao.py status)

init 写入了什么(全部可见、可 diff、可干净移除)

写入 内容
.fengchao/ 唯一工具安装点:config.yaml + skill 完整副本(可整体删除)
fengchao/ 唯一记忆根:FENGWANG.md 路由入口 + 六层记忆目录(属于你,建议入 git)
.claude/ .cursor/ 等 薄入口 + 三个斜杠命令(每个文件 ≤ 10 行,只指向 .fengchao/skill/)
CLAUDE.md / AGENTS.md 一个 marker 块(≤ 15 行,disable 精确摘除,原内容一字不动)
.claude/settings.json SessionStart / Stop 两个 hook(可 --no-hooks 关闭)

日常使用:你什么都不用做

正常开发即可。路由和维护由 skill 规则 + hooks 驱动:

  • 新会话自动从 fengchao/FENGWANG.md 路由回业务记忆(SessionStart hook);
  • 真实开发交付后自动沉淀 task-record + changelog(Stop hook 门禁:remind / strict / off 三档);
  • 纯修复/重构走 lite 档只记一条 changelog,不制造记忆噪音。

想主动用,三个动词(Claude Code 中为 /fengchao:route 等):

命令 作用
/fengchao:route <关键词> 找回相关业务记忆
/fengchao:remember 把刚才的业务解释记入记忆
/fengchao:status 看看记忆系统状态

停用与卸载(三级分离,随时反悔)

uvx fengchao-skills disable     # 暂停:摘除全部注入,记忆和工具本体全保留;enable 逐字节还原
uvx fengchao-skills uninstall   # 移除工具:删 .fengchao/,记忆文档保留(它属于你)
uvx fengchao-skills uninstall --purge-memory   # 连记忆一起删,需要二次确认

disable 后 git diff 干净可读;每一个写入你项目的字节都有对应的干净摘除路径。即使卸载,记忆仍是一套完好的、人类可读的 Markdown 文档库。

六层记忆模型

目录 语义 写入时机
business-context/ 当前业务真相(每条规则一个现行条目,带证据链) 仅稳定业务事实落地后,经语义合并写入
task-records/ 已交付任务的业务意图、方案、证据(不可变) 仅真实开发交付后(full 档)
changelog/ 已落地变更历史(不可变) 任何真实交付(lite/full 档)
plan-records/ 最终计划(proposed → implemented 状态流转) Plan 产出最终计划后
conversation-records/ 用户业务解释、术语、偏好、否定项 用户给出长期有价值的解释后
FENGWANG.md + memory-map.md 路由入口 所有写入命令自动追加

隐私默认:只保存萃取摘要,永不保存完整对话。

支持的 Agent Surface

Claude Code(薄入口 + 斜杠命令 + hooks 硬门禁)· Cursor(rule + 命令)· OpenCode(命令 + opencode.json)· Codex / 通用 Agents(AGENTS.md marker 块)。不用 Claude Code 也能用:五个 surface + 可选 git pre-commit 钩子兜底(fengchao-skills install-git-hook)。任何读 AGENTS.md 的工具(Pi / Kimi Code / 智谱 ZCode 等)经通用 agents surface 开箱即用。

文档

信任声明

  • 运行时零第三方依赖:fengchao.py 只用 Python 标准库,目标项目无需安装任何东西。
  • 零遥测、零网络请求:没有任何数据离开你的机器。
  • 记忆数据神圣:任何命令(uninstall/upgrade/migrate/compact)都不会在无显式确认下删除或改写记忆内容。
  • token 开销可量化:每会话固定注入 ≤ 约 260 tokens,路由输出有 4KB 硬预算——实测数据见 FAQ。

License

MIT

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