Agent skill · writing content · jimliu
baoyu-wechat-summary
Summarizes WeChat group chat highlights into a structured digest using the local wx-cli binary (https://github.com/jackwener/wx-cli). Generates a normal digest by default; a roast (毒舌) version is opt-in. Maintains per-group history (history.json + history-digests.jsonl), per-user profiles, and per-group fact memory (memory.md) across runs, with privacy guardrails baked in. Use when the user asks to "总结群聊", "群聊精华", "群聊摘要", "summarize group chat", "group chat digest", mentions a WeChat group name with a time range, says "帮我看看 XX 群最近聊了什么", "XX 群有什么值得看的", or asks to "回溯画像" / "初始化画像" / "backfill profiles". Adds the roast version when the user says "毒舌版", "roast 版", "再来个毒舌的", or similar.
Why this skill is useful
Adds specific commands and workflows for summarizing WeChat group chats that the AI wouldn't reliably generate on its own.
What it needs
Requires wx installed locally. About 12k tokens when loaded. Last updated 2026-07-04. 24,677 stars on the source repository.
What this skill does
WeChat Group Summary 群聊精华提取专家。把零散的微信群聊记录提炼成结构化、可读性强的简报，并维护跨次运行的群聊历史与群友画像。底层依赖外部 wx-cli 二进制（wx 命令），不打包脚本。 ⚠️ Sandbox restriction wx-cli reads from ~/.wx-cli/ (config, cache, daemon socket) and from WeChat's data directory (~/Library/Containers/com.tencent.xinWeChat/ on macOS). Both paths are outside Claude Code's default sandbox. Every wx command in this skill needs to run with dangerouslyDisableSandbox: true from the start — don't waste a sandbox attempt first. The user can use /sandbox to view/edit restrictions. References（按需加载） 本文件只保留工作流骨架；细节拆在 references/ 下，执行到对应步骤时再读，不要一开始全部读入： 参考文件 内容 何时读 --------- ------ ------- references/setup.md 环境检查（wx-cli 安装/权限/初始化）、wx-cli 命令速查、排障手册 新环境首次运行，或任何 wx 命令失败时 references/output-formats.md 两版摘要的 Section 顺序、格式与内容规范、输出骨架、自检清单 Round 2 动笔前 references/profiles.md 画像文件格式、更新规则、隐私红线、回溯流程 Step 3.7 / 8.5 / Step 9 references/group-memory.md 群级事实记忆的写入门槛、防注入、格式 Step 8.6 User Input Tools When this skill prompts the user, follow this tool-selection rule (priority order): 1. Prefer built-in user-input tools exposed by the current agent runtime — e.g., AskUserQuestion, requestuserinput, clarify, askuser, or any equivalent. 2. Fallback: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question. 3. Batching: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order. Concrete AskUserQuestion references below are examples — substitute the local equivalent in other runtimes. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jimliu/baoyu-wechat-summary