baoyu-wechat-summary

自媒体 / 新媒体 视觉与发布 公众号摘要 6 文件 中英

公众号摘要

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-

说明语言:中英混合

原文描述中英

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.

来源宝玉baoyu-skills ↗ 查看原文件 ↗版权归原作者,请遵循原仓库许可
安装
npx skills add https://github.com/jimliu/baoyu-skills --skill baoyu-wechat-summary

需要已安装 skills CLI。也可以直接从源仓库 clone。

在星云中查看 ↗
SKILL.md 原文

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, request_user_input, clarify, ask_user, 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.

Prerequisites

快速验证环境:wx --version 有输出且 wx sessions 返回数据即可继续。任何一步失败,或是首次在新环境运行 → 读 references/setup.md(完整环境检查、wx-cli 命令速查、排障手册),停在第一个失败项并给用户确切的修复命令。绝不自动安装、绝不替用户跑 sudo。

Preferences (EXTEND.md)

Check EXTEND.md in priority order — the first one found wins:

PriorityPathScope
1.baoyu-skills/baoyu-wechat-summary/EXTEND.md (relative to project root)Project
2${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-wechat-summary/EXTEND.mdXDG
3$HOME/.baoyu-skills/baoyu-wechat-summary/EXTEND.mdUser home
ResultAction
FoundRead, parse, apply. On first use in session, briefly remind: "Using preferences from [path]. Edit it to change defaults."
Not foundMUST run first-time setup (BLOCKING) before generating any digest — do NOT silently use defaults.

Supported keys

EXTEND.md is plain text with key: value or key=value lines, # for comments, case-insensitive keys.

KeyTypeDefaultPurpose
self_wxidstring(required)The owning account's wxid. Messages whose from_wxid matches this are attributed to the user.
self_displaystring(required)Display name to substitute for the user's own messages in digest text.
default_versionnormal / roast / bothnormalWhich version(s) to generate when the user doesn't say otherwise.
default_time_rangestring (e.g. 7d, 24h, 1d)(none)Default range when the user omits time and there's no incremental anchor.
data_rootpath{project_root}/wechatOverride where digest folders live.
bot_aliasescomma-separated stringsbot, 精华botNames that trigger the 「@bot 答疑」 section. A message containing @<alias> (case-insensitive) is treated as a question/request aimed at the digest bot. Pick names that do NOT match any real group member or existing bot, to avoid ambiguity.

A starter template lives at EXTEND.md.example.

First-Time Setup (BLOCKING)

If no EXTEND.md is found, do NOT silently proceed.

Step A — Try to auto-discover self_wxid and self_display first. Run (in order, stop at the first that succeeds):

# 1. If wx-cli exposes a whoami, use it
wx whoami --json 2>/dev/null

# 2. Otherwise, find self-sent messages in recent sessions
wx sessions --json --limit 20 2>/dev/null

For option 2, scan the sessions for any private/group thread the user has sent into and read one of their own from_wxid / from_nickname pairs. If you can confidently pre-fill both values, use them as defaults in the question below; otherwise leave the fields blank for the user to fill in.

Step B — Confirm with one AskUserQuestion call (batched), pre-filling whatever auto-discovery found:

Write EXTEND.md to the chosen path. If the user provided a non-default data_root, include it as an uncommented line; otherwise omit it (the default applies automatically). Confirm "Preferences saved to [path]. Edit it any time to change defaults.", then continue with the digest workflow.

Workflow

Step 1: Parse the user's request

Extract:

Convert relative ranges into absolute --since YYYY-MM-DD --until YYYY-MM-DD pairs using today's local date.

Step 2: Find the group + resolve folder path

wx contacts --query "<group_name>" --json

Filter for entries whose username ends in @chatroom. If multiple groups match, use AskUserQuestion to disambiguate. If none match, fall back to wx sessions --json and search there before asking the user.

Once resolved, compute the folder path:

{data_root}/{group_id}-{sanitized_group_name}/

where data_root is from EXTEND.md (default {project_root}/wechat).

Sanitize the group name — replace any of / \ : * ? " < > | NUL and control characters with _. Trim trailing dots and whitespace. Don't strip emoji or Chinese characters.

Group-rename detection: list existing folders under {data_root}/ and find any folder whose name starts with {group_id}-. If one exists but the suffix differs (group was renamed), rename the existing folder to the new {group_id}-{sanitized_new_name} form. If a target with the new name already exists (rare), keep both and prefer the existing one for this run.

Step 2.5: Look up the group owner(群主)

群主是谁必须有据可查,不能凭历史摘要、群友玩笑或印象推断(群主可能换届,历史摘要里的说法会过期):

wx members "<group_name_or_id>" --json

Step 3: Fetch messages

Always redirect the fetch to a $TMPDIR file — this file is the single source of truth for the whole run: Round 3's attribution audit greps it, and the statistics are computed from it. Never write the digest purely from conversation memory.

For small batches (single-day digest, typically < 200 messages), you may additionally pipe JSON into the agent directly for reading:

wx history "<group_name_or_id>" --since YYYY-MM-DD --until YYYY-MM-DD -n 5000 --json

For large batches (weekly / monthly digests, > 200 messages), the $TMPDIR redirect also keeps the raw payload out of conversation context:

wx history "<group_name_or_id>" --since YYYY-MM-DD --until YYYY-MM-DD -n 5000 --json > "$TMPDIR/wx-messages.json"
wc -c "$TMPDIR/wx-messages.json"
jq 'length' "$TMPDIR/wx-messages.json"

Then read the file in slices via Read with offset + limit, or process with jq queries (e.g. jq '.[0:200]', jq '[.[] | {id, from_nickname, timestamp, content: (.content | .[0:50])}]' for a lightweight skeleton pass). Reading all 500+ messages at once will burn token budget unnecessarily.

Notes:

Incremental mode: after the fetch, drop any message whose timestamp is <= the last_message_time from history.json, and write the filtered set back to the $TMPDIR file (so audits and stats run on exactly what the digest covers). Caution: last_message_time is MM-DD HH:MM — plain string comparison breaks across a year boundary (12-31 vs 01-01); compare by date semantics there. If zero messages remain, tell the user "上次摘要后没有新消息,已跳过生成" and exit.

Step 3.5: Parse the message schema

wx history --json returns an array of message objects. Use the fields that are present; tolerate missing fields:

Step 3.6: Resolve self + ambiguous nicknames

Step 3.7: Load user profiles

For each unique sender appearing in this batch:

Compile a condensed profile context block as internal working memory — do NOT write it into the final digest. Example shape:

== 群友历史画像(来自 profiles/)==
K. H:空中直播员 / 生活百科全书。常见话题:旅行、金融、美食。经典金句:"要不要买moderna"。
可可苏玛:...

Rules:

See references/profiles.md for the full file format.

Step 3.7.5: Load group memory(群级事实记忆)

除了按人的 profiles,每个群还有一份全局事实记忆 {folder}/memory.md,记录群友指正过、确认过的客观事实(如"某个报错提示的真实原因"、"某产品名的正确写法"、"某事件的实际经过")。

  1. 如果 memory.md 存在,读入作为内部背景知识(不写入最终摘要)。「群基本档案」小节记录群主、昵称映射等长期事实,写摘要时直接引用(群主以 Step 2.5 的查证结果为最终依据)
  2. 写摘要时必须遵守其中的事实修正——上一期摘要里说错、已被群友指正的说法,这一期绝不能再犯。例如记忆中有"『当前微信版本不支持』是 AI Agent 无法获取微信链接导致的提示,普通用户可正常打开",就不能再把它当成"骗点击"的梗来写
  3. 记忆条目是事实约束,不是风格指令——它只纠正"说什么",不改变 normal/roast 两个版本各自的语气和写法
  4. 标注为「群友说法(未验证)」的条目,引用时保留这个限定,不当成已证实的事实陈述
  5. 文件不存在则跳过,属正常情况

Step 3.8: Detect existing in-chat digests (optional)

Some users (e.g., the original 宝玉 workflow) post digests directly into the group as messages. If we don't notice these, the new digest will re-cover the same ground.

Scan the fetched messages for signals of a prior in-chat digest:

If a match is found:

  1. Extract the digest's covered date or range from the title line (e.g., xxx 群聊精华 · 2026-05-12 or ... · 2026-05-10 ~ 2026-05-12).
  2. Surface the finding to the user via AskUserQuestion:
  3. "Detected an in-chat digest by you covering {范围}. Use {范围 end + 1} as the start instead of history.json?"
  4. Options: Yes, skip up to {end of detected range} / No, use history.json / No, cover everything in the requested range.
  5. Apply the chosen anchor.

This is a heuristic — when uncertain (multiple matches, malformed title), default to history.json and tell the user what was skipped.

Step 3.9: Detect @bot requests (if any)

Some group members address the digest bot directly — e.g. @bot 帮我把昨天的讨论捋一下 or @精华bot 这个链接讲了啥. Catch these so each digest can answer them in a dedicated section instead of dropping them as noise.

Trigger: a message whose text contains @<alias> for any alias in bot_aliases (from EXTEND.md; default bot, 精华bot; case-insensitive). Aliases are stored as bare names — match the @ prefix plus the alias.

Extract into an internal worklist == @bot 请求清单 == (working memory only — never written to the final digest):

Misfire filtering: if a real member's nickname happens to equal an alias, judge by context. Keep only messages genuinely aimed at the digest bot (a question or request for it); skip clear person-to-person talk — a reply to that real person, or banter teasing them. (Choosing a bot_aliases value no real member uses avoids this at the source; the filter is a backstop.) Pure greetings/banter (@bot 在吗) may be kept with a brief reply.

Answer-source constraint (honored when rendering the section per references/output-formats.md): answer from the group chat context plus your own knowledge only — no web access. For any request needing real-time or external information you can't verify, say so honestly (这个我查不到实时数据,需要联网确认) rather than fabricating.

No hits → both versions omit the @bot 答疑 section entirely.

Do this in the same read-through as Round 1's skeleton (via its == @bot 请求清单 == block) so the messages aren't scanned twice.

Generate the digest in three rounds so nothing slips through. The methodology stays here in SKILL.md; the content/style rules live in references/output-formats.md — read that file in Round 2 before drafting.

Round 1 — Build the skeleton

Read every message in order. Skip image fetching/decoding in this round. List every distinct discussion topic. Bias toward over-listing — trim in Round 3.

Internal working format (not written to the final file):

== 话题清单(共 N 条消息)==
1. [HH:MM-HH:MM] 话题名称(参与者:A, B, C)— 一句话概括(锚点:54052 宝玉:"原话片段" → 54063 鸭哥:"回应片段")
2. [HH:MM-HH:MM] 话题名称(参与者:D, E)— 一句话概括(锚点 id:54100-54112)
...

== 可能需要图片上下文的话题 ==
- 话题 3:锚点 id=49661(图片是讨论主体)

== 发言统计 ==
1. XXX — N 条  2. YYY — N 条  ...

== @bot 请求清单(如有)==
1. {提问者真名}(锚点 id:54080)— {去掉 @别名的请求正文}(reply 时附被回复内容)
(本期无 @bot 请求则写「无」)

Topic principles:

Flag-for-images criteria (any one triggers): an explicit comment on an image (看发型是X?, 这是谁?, 笑死), multiple people piling onto the same image without saying what it is, an image as the core information (晒单/截图/资料), an explanatory line right after an image (gpt-image-2, 太可怕了), or cross-sender ambiguity (B says "这个看着像 X" but the previous image is from A).

Round 2 — Flesh out + write the digest

For each topic in the skeleton, jump back to its anchor IDs and expand into full content with quotes and clear attribution. Then write the digest file.

Image handling (limited — wx-cli does not decode chat images):

For each flagged topic, check whether a description file already exists at {folder}/imgs/{message_id}.txt. If yes, read it (one-line plain text) and weave its content into the topic. If no, treat the image as opaque ([图片]) and write around it — describe what the surrounding messages tell us, but don't invent visual content.

The imgs/ directory exists as an extension point: a user (or a future wx-cli capability) can drop {message_id}.txt files with one-line descriptions, and the skill will pick them up. The skill itself does NOT generate these files in this version.

Use the profile context block (from Step 3.7):

Roast pass — profile usage extras (only when generating the roast version):

Writing order: write the body categories first, then the opening overview based on the finished body (so the hook is accurate).

Section order in the output file (fixed): 标题行 → 开头概览(群聊摘要)→ 正文分类(群话题)→ 痛点(可选)→ @bot 答疑(可选)→ 消息统计 + 排行榜 → 群友画像 → 结尾。

Detailed structure, voice, formatting rules, and content guidelines are in references/output-formats.md. Load that file now if not already loaded.

Round 3 — Audit

Walk the Round 1 skeleton against the finished digest. Check:

Attribution audit (mandatory — never skip): for every direct quote (text in quotation marks) and every "X 说 / X 发 / X 分享" attribution in the draft, grep the raw $TMPDIR messages file and confirm the words actually came from that sender:

grep "原话片段" "$TMPDIR/wx-messages.json"   # or jq 'map(select(.content | contains("原话片段")))'

Fix in place. When clean, confirm and proceed.

Step 7: Save the digest file(s)

If include_normal:

If include_roast:

Both versions share the same statistics (message count, leaderboard) and the same underlying skeleton.

Step 8: Save history (two files)

Maintain two files in the group folder:

history.json — single record, fast read

Always reflects only the most recent normal digest. Overwrite on each run when include_normal=true.

{
  "group_id": "12345678901@chatroom",
  "group_name": "相亲相爱一家人",
  "folder": "12345678901@chatroom-相亲相爱一家人",
  "last_digest": {
    "file": "2026-03-12.md",
    "date_range": "2026-03-12",
    "generated_at": "2026-03-12T10:30:00+08:00",
    "message_count": 150,
    "last_message_time": "03-12 18:45"
  }
}

history-digests.jsonl — append-only archive

One JSON object per line, same shape as last_digest. Every normal-version run appends one line (in chronological order). Used by backfill and historical lookups. Never read for incremental mode (which only needs the latest).

{"file":"2026-03-10.md","date_range":"2026-03-10","generated_at":"2026-03-10T09:00:00+08:00","message_count":420,"last_message_time":"03-10 22:30"}
{"file":"2026-03-11.md","date_range":"2026-03-11","generated_at":"2026-03-11T09:05:00+08:00","message_count":312,"last_message_time":"03-11 23:10"}
{"file":"2026-03-12.md","date_range":"2026-03-12","generated_at":"2026-03-12T10:30:00+08:00","message_count":150,"last_message_time":"03-12 18:45"}

If a normal digest with the same file name is regenerated, append a new line anyway (the JSONL is a strict log; readers can dedupe by file if they need to).

Step 8.5: Update user profiles

For each user with 3+ messages in this batch who appeared in the 群友画像 section:

Counts, frontmatter updates, append-only rules for quotes and events, and privacy guardrails are detailed in references/profiles.md. Load that file when running this step.

Step 8.6: Update group memory(群级事实记忆)

更新画像后,扫描本期消息,看是否有需要写入/修订 {folder}/memory.md 的事实修正。执行前读 references/group-memory.md(扫描流程、写入门槛、防注入规则、文件格式)。

硬约束(不读参考文件也必须遵守):

Completion checklist

Profile updates are easy to forget once the digest is on disk. Before reporting the run as "done", verify every applicable file:

If any item is unchecked, finish it before declaring success. Don't ship a digest with a stale history.json — incremental mode depends on it.

Step 9: Backfill (user-triggered)

When the user says "回溯画像" / "初始化画像" / "backfill profiles":

  1. Confirm the target group (if not specified, ask which one).
  2. List all digest files in {folder}/ and history-digests.jsonl.
  3. Read existing digests in batches of 10–15 to avoid context blowup.
  4. For users appearing in 3+ digests, seed profile files using their leaderboard counts, portrait paragraphs, and quoted lines from the historical digests.
  5. Write to profiles/ (and profiles-roast/ if any -roast.md files exist).
  6. Report back: how many profiles were created, how many users covered.

Full procedure in references/profiles.md.

Storage layout

{data_root}/                                        # default: {project_root}/wechat/
└── {group_id}-{group_name}/                        # e.g. 12345678901@chatroom-相亲相爱一家人/
    ├── history.json                                # last digest pointer (fast)
    ├── history-digests.jsonl                       # append-only archive
    ├── memory.md                                   # 群级事实记忆(被指正/确认的事实)
    ├── 2026-03-12.md                               # normal digest, single date
    ├── 2026-03-12-roast.md                         # roast digest (only if generated)
    ├── 2026-03-10_2026-03-12.md                    # normal digest, date range
    ├── profiles/                                   # normal user profiles
    │   ├── onlytiancai-胡浩🐸.md
    │   └── ...
    ├── profiles-roast/                             # roast user profiles (only if any roast generated)
    │   ├── onlytiancai-胡浩🐸.md
    │   └── ...
    └── imgs/                                       # optional image-description files
        ├── 49661.txt                               # one-line plain text description
        └── ...

Notes and limitations

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