飞书会话浏览与管理

通过 feishu-cli 浏览飞书单聊/群聊消息历史、搜索会话、管理群聊信息和成员。

前置条件

• feishu-cli：如尚未安装，请前往 riba2534/feishu-cli 获取安装方式

本技能的核心命令必须使用 User Token，使用前需先登录。chat create、chat link、msg read-users 使用 App Token，属于 feishu-cli-toolkit 技能。

feishu-cli auth login

未登录时命令会直接报错并提示登录方式。登录后 token 自动加载，无需手动传参。

身份说明

身份	使用场景
User Token（必须）	本技能所有读取/管理命令：chat get/update/delete、member list/add/remove、msg get/history/list/pins/reaction/search-chats、search messages
App Token	仅 chat create、chat link、msg read-users（这三个命令不属于本技能核心流程）

User Token 能力：

• 查看 bot 不在的群聊消息
• 查看私聊（p2p）消息
• 搜索用户有权限的所有会话

自动降级机制

当使用 User Token 调用 msg history / msg list 时，如果 bot 不在目标群中，API 会返回空结果。CLI 会自动检测这种情况并降级为 search + get 方式获取消息：

list API 返回空 + has_more=true → 自动切换到搜索模式 → 逐条获取消息内容

这个过程对用户透明，无需手动干预。

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场景一：查看群聊历史消息

这是最常见的场景——用户想看某个群最近在聊什么。

步骤 1：找到群聊

如果用户给了群名而不是 chat_id，先搜索：

feishu-cli msg search-chats --query "群名关键词" -o json

输出中的 chat_id（形如 oc_xxx）就是后续命令需要的标识。

步骤 2：获取消息

# 获取最近 50 条消息（API 单次上限 50）
feishu-cli msg history \
  --container-id oc_xxx \
  --container-id-type chat \
  --page-size 50 \
  --sort-type ByCreateTimeDesc \
  -o json

# 按时间范围获取（--start-time 为秒级时间戳，仅返回该时间之后的消息）
# 获取"今天 00:00 至今"的消息示例：
START_TS=$(python3 -c "from datetime import datetime,timezone,timedelta; tz=timezone(timedelta(hours=8)); print(int(datetime.now(tz).replace(hour=0,minute=0,second=0,microsecond=0).timestamp()))")
feishu-cli msg history \
  --container-id oc_xxx \
  --container-id-type chat \
  --page-size 50 \
  --start-time $START_TS \
  --sort-type ByCreateTimeAsc \
  -o json

# 获取更早的消息（使用上一次返回的 page_token 翻页）
feishu-cli msg history \
  --container-id oc_xxx \
  --container-id-type chat \
  --page-size 50 \
  --page-token "上一页返回的token" \
  -o json

步骤 2.5：判断群类型并获取线程回复

飞书群聊分为普通群和话题群两种，消息结构和获取策略完全不同。

如何判断群类型

观察 msg history 返回的消息字段：

群类型	特征	示例
话题群	每条消息都有 thread_id（形如 omt_xxx），主消息流仅包含每个话题的首条消息	泰国华商群
普通群	独立消息无 thread_id，仅被回复的消息和回复消息才有 thread_id	Claude Code闲聊群

消息中的线程相关字段

字段	说明	出现条件
thread_id	线程/话题 ID（形如 omt_xxx）	话题群所有消息 / 普通群中参与线程的消息
root_id	线程根消息 ID（即话题首条消息）	线程回复消息
parent_id	直接上级消息 ID（被回复的那条消息）	线程回复消息

普通群：一次获取全部消息

普通群的 msg history 返回所有消息（独立消息 + 线程回复），平铺在同一列表中。通过 root_id/parent_id 可重建回复关系，不需要额外获取线程。

独立消息:       无 thread_id、无 root_id
被回复的消息:   有 thread_id（被回复后自动产生）
线程回复:       有 thread_id + root_id + parent_id

话题群：需要逐个话题获取回复（重要）

话题群的 msg history --container-id-type chat 仅返回每个话题的首条消息，线程回复不在主消息流中。必须按 thread_id 逐个获取：

# 获取单个话题的所有回复（按时间正序，方便阅读）
feishu-cli msg history \
  --container-id omt_xxx \
  --container-id-type thread \
  --page-size 50 \
  --sort-type ByCreateTimeAsc \
  -o json

完整的话题群获取流程：

# 1. 获取主消息流（每个话题的首条消息）
feishu-cli msg history \
  --container-id oc_xxx \
  --container-id-type chat \
  --page-size 50 \
  --sort-type ByCreateTimeDesc \
  -o json

# 2. 从返回结果中提取所有 thread_id

# 3. 对每个 thread_id 获取回复（可并发执行，提高效率）
feishu-cli msg history --container-id omt_xxx --container-id-type thread --page-size 50 --sort-type ByCreateTimeAsc -o json
feishu-cli msg history --container-id omt_yyy --container-id-type thread --page-size 50 --sort-type ByCreateTimeAsc -o json
# ... 多个话题可并行获取

性能提示：话题群中活跃话题可能有 10-20 个，建议并发获取多个话题的回复。飞书 API 对 msg history 无严格 QPS 限制（不同于搜索 API），可以安全并发。

步骤 3：解析消息内容

API 返回的消息 body.content 是 JSON 字符串，常见格式：

msg_type	content 格式	说明
text	{"text":"消息内容"}	纯文本，@_user_1 是 at 占位符
post	富文本 JSON	包含标题和段落结构
image	{"image_key":"xxx"}	图片
interactive	卡片 JSON	交互式卡片
share_calendar_event	{"summary":"会议名","start_time":"ms","end_time":"ms",...}	日历事件分享
sticker	{"sticker_key":"xxx"}	表情包
file	{"file_key":"xxx","file_name":"..."}	文件

用 Python 提取文本内容的常用方式：

import json
content = json.loads(msg['body']['content'])
text = content.get('text', '')

完整示例：获取并总结群聊最近 N 条消息

# 1. 搜索群聊
feishu-cli msg search-chats --query "Go讨论区" -o json

# 2. 获取消息（循环翻页直到够数）
feishu-cli msg history \
  --container-id oc_xxx \
  --container-id-type chat \
  --page-size 50 \
  --sort-type ByCreateTimeDesc \
  -o json > /tmp/chat_page1.json

# 3. 提取 page_token 获取下一页
# ... 循环直到获取足够消息

注意：Search API 的 page_size 与 List API 不同，降级模式下每页实际返回数量可能少于请求值。建议循环翻页直到 has_more=false 或达到目标数量。

---

场景二：查看和某人的私聊记录

飞书 Open API 不支持直接按用户查询 p2p 聊天记录。需要通过搜索 API 间接实现。

方法：搜索 + 筛选

# 搜索私聊消息
feishu-cli search messages "关键词" \
  --chat-type p2p_chat \
  -o json

# 如果知道对方的 open_id，可以按发送者筛选
feishu-cli search messages "关键词" \
  --chat-type p2p_chat \
  --from-ids ou_xxx \
  -o json

# 获取单条消息详情
feishu-cli msg get om_xxx -o json

查找用户 ID

如果用户只给了邮箱或手机号，可以查找对应的 open_id：

# 通过邮箱查找用户
feishu-cli user search --email [email protected] -o json

# 通过手机号查找用户
feishu-cli user search --mobile 13800138000 -o json

注意：user search 仅支持 --email 和 --mobile 精确查找，不支持按姓名模糊搜索。

限制说明

• 搜索 API 的 query 参数不能为空，至少需要一个空格 " "
• p2p 聊天无法通过 msg search-chats 搜索（该 API 只搜索群聊）
• 搜索结果返回的是消息 ID 列表，需要逐条 msg get 获取完整内容
• msg get 对私聊消息可能返回 230001 错误（API 限制：部分私聊消息不支持通过 Get API 获取详情），此时只能依赖搜索结果中的摘要信息

---

场景三：搜索群聊

搜索群聊列表

# 按关键词搜索群聊
feishu-cli msg search-chats --query "关键词" -o json

# 分页获取所有群
feishu-cli msg search-chats --page-size 100 -o json

在群内搜索消息

# 在指定群中搜索消息
feishu-cli search messages "关键词" --chat-ids oc_xxx -o json

更多搜索功能（按时间范围、消息类型、发送者、跨模块搜索文档/应用等）请使用 feishu-cli-search 技能，提供完整的筛选参数和 Token 排错指南。

---

场景四：群聊信息管理

查看群信息

feishu-cli chat get oc_xxx

默认输出 JSON 格式，包含群名、描述、群主、群类型、成员数量等。

查看群成员

# 获取成员列表
feishu-cli chat member list oc_xxx

# 指定 ID 类型
feishu-cli chat member list oc_xxx --member-id-type user_id

# 分页获取（大群）
feishu-cli chat member list oc_xxx --page-size 100 --page-token "xxx"

Scope 要求：使用 User Token 时需要 im:chat:read 或 im:chat.members:read scope。若报 99991679 错误，需通过 auth login --scopes "... im:chat:read" 重新授权。

修改群信息

# 改群名
feishu-cli chat update oc_xxx --name "新群名"

# 改群描述
feishu-cli chat update oc_xxx --description "新的群描述"

# 转让群主
feishu-cli chat update oc_xxx --owner-id ou_xxx

群成员管理

# 添加成员
feishu-cli chat member add oc_xxx --id-list ou_xxx,ou_yyy

# 移除成员
feishu-cli chat member remove oc_xxx --id-list ou_xxx

# 使用 user_id 类型
feishu-cli chat member add oc_xxx --id-list user_xxx --member-id-type user_id

创建群聊

feishu-cli chat create --name "新群聊" --user-ids ou_xxx,ou_yyy

注意：chat create 和 chat link（获取分享链接）仅支持 App Token（租户身份），不支持 User Token。

解散群聊

feishu-cli chat delete oc_xxx
# 会要求确认，不可逆操作

---

场景五：消息详情与互动

获取单条消息详情

feishu-cli msg get om_xxx -o json

查看消息已读情况

feishu-cli msg read-users om_xxx -o json

限制：仅支持查询 bot 自己发送的、7 天内的消息，且 bot 必须在会话内。此命令仅使用 App Token。

查看群内置顶消息

feishu-cli msg pins --chat-id oc_xxx -o json

置顶/取消置顶消息

# 置顶消息
feishu-cli msg pin <message_id>

# 取消置顶
feishu-cli msg unpin <message_id>

Reaction 表情回应

# 添加表情
feishu-cli msg reaction add <message_id> --emoji-type THUMBSUP

# 删除表情
feishu-cli msg reaction remove <message_id> --reaction-id <REACTION_ID>

# 查询表情列表
feishu-cli msg reaction list <message_id> [--emoji-type THUMBSUP] [--page-size 20]

常用 emoji-type：THUMBSUP（点赞）、SMILE（微笑）、LAUGH（大笑）、HEART（爱心）、JIAYI（加一）、OK、FIRE

删除消息

仅能删除机器人自己发送的消息，不可恢复。

feishu-cli msg delete <message_id>

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常见操作速查表

用户意图	命令	Token
看某群最近消息	msg history --container-id oc_xxx --container-i List & Monetize Your Skill Submit your Claude Code skill and start earning Get started → Use Cases User Story & Requirements Generation Create detailed user stories, acceptance criteria, and feature specs Example Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios ✓ Reduce spec writing time by 50%, ensure comprehensive coverage Competitive Analysis Research competitors, compare features, identify gaps Example Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities ✓ Complete competitive research in 2 hours instead of 2 days Roadmap Prioritization Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs Example Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale ✓ Make data-driven prioritization decisions faster Stakeholder Communication Draft PRDs, status updates, and stakeholder presentations Example Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement ✓ Save 3-5 hours/week on communication overhead Implementation Guide Prerequisites ›Claude Desktop or compatible AI client ›Access to product documentation and roadmap tools (Jira, Notion, etc.) ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.) ›Stakeholder contact information and communication channels Time Estimate 30-60 minutes to see productivity improvements Steps 1Install product management skill 2Start with user story generation for known feature 3Progress to competitive analysis: research 2-3 competitors 4Use for roadmap prioritization: apply RICE/ICE scoring 5Draft stakeholder communications and refine based on feedback 6Build template library for recurring PM tasks 7Share effective prompts with product team Common Pitfalls ⚠Not validating competitive research—verify facts before sharing ⚠Accepting user stories without involving engineering team ⚠Over-relying on frameworks without qualitative judgment ⚠Not customizing outputs to company culture and communication style ⚠Skipping stakeholder validation of generated requirements Best Practices ✓ Do +Validate research and competitive analysis with real data +Collaborate with engineering when generating technical requirements +Customize frameworks and templates to your company context +Use skill for first drafts, refine with stakeholder input +Document successful prompt patterns for PM tasks +Combine AI efficiency with human judgment and intuition ✗ Don't −Don't publish competitive analysis without fact-checking −Don't finalize user stories without engineering review −Don't make prioritization decisions solely on AI scoring −Don't skip customer validation of generated requirements −Don't ignore company-specific context and culture 💡 Pro Tips ★Provide context: company goals, constraints, customer feedback ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap' ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec' ★Use skill for 70% generation + 30% customization to company needs When to Use This ✓ Use when Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work. ✗ Avoid when Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed. Learning Path 1Basic: user stories, feature specs, status updates 2Intermediate: competitive analysis, prioritization frameworks, PRDs 3Advanced: product strategy, go-to-market planning, OKR setting 4Expert: product vision, market positioning, business model innovation Related Skills grill-me 364 mattpocock/skills Productivitysame category premortem 196 parcadei/continuous-claude-v3 Productivitysame category deslop 114 cursor/plugins Productivitysame category framer-motion 97 pproenca/dot-skills Productivitysame category write-a-prd 88 mattpocock/skills Productivitysame category travel-planner 87 ailabs-393/ai-labs-claude-skills Productivitysame category Reviews 4.7★★★★★39 reviews X Xiao Martin★★★★★Dec 28, 2024 Registry listing for feishu-cli-chat matched our evaluation — installs cleanly and behaves as described in the markdown. D Diya Park★★★★★Dec 24, 2024 We added feishu-cli-chat from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront. S Shikha Mishra★★★★★Dec 16, 2024 feishu-cli-chat reduced setup friction for our internal harness; good balance of opinion and flexibility. X Xiao Harris★★★★★Dec 8, 2024 Keeps context tight: feishu-cli-chat is the kind of skill you can hand to a new teammate without a long onboarding doc. A Aisha Harris★★★★★Nov 27, 2024 I recommend feishu-cli-chat for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area. A Alexander Sethi★★★★★Nov 15, 2024 Solid pick for teams standardizing on skills: feishu-cli-chat is focused, and the summary matches what you get after install. H Hassan Anderson★★★★★Nov 7, 2024 feishu-cli-chat reduced setup friction for our internal harness; good balance of opinion and flexibility. A Amelia Iyer★★★★★Oct 26, 2024 Registry listing for feishu-cli-chat matched our evaluation — installs cleanly and behaves as described in the markdown. M Meera Zhang★★★★★Oct 18, 2024 Useful defaults in feishu-cli-chat — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows. C Charlotte Ramirez★★★★★Oct 6, 2024 feishu-cli-chat has been reliable in day-to-day use. Documentation quality is above average for community skills. showing 1-10 of 39 prev1 / 4next Discussion Comments — not star reviews Post comment No comments yet — start the thread. sharebookmark