feishu-cli-search▌
riba2534/feishu-cli · updated Apr 8, 2026
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搜索飞书云文档、消息和应用。所有搜索命令必须使用 User Access Token。
飞书搜索
搜索飞书云文档、消息和应用。所有搜索命令必须使用 User Access Token。
feishu-cli:如尚未安装,请前往 riba2534/feishu-cli 获取安装方式。
执行流程
每次执行搜索前,按以下流程操作:
1. 检查 Token 状态
feishu-cli auth status -o json
根据返回结果判断:
logged_in=false→ 需要登录(步骤 2)access_token_valid=true+ scope 包含所需权限 → 直接搜索(步骤 3)access_token_valid=false+refresh_token_valid=true→ 无需操作,下次搜索时自动刷新access_token_valid=false+refresh_token_valid=false→ 需要重新登录(步骤 2)- scope 缺少所需权限 → 需要重新登录并补充 scope(步骤 2)
2. 登录获取 Token(如需要)
使用两步式非交互登录,始终使用最大 scope 范围(覆盖搜索 + wiki + 日历 + 任务等全部功能):
# 步骤 A:生成授权 URL(最大 scope)
feishu-cli auth login --print-url --scopes \
"offline_access \
search:docs:read search:message drive:drive.search:readonly \
wiki:wiki:readonly \
calendar:calendar:read calendar:calendar.event:read \
calendar:calendar.event:create calendar:calendar.event:update \
calendar:calendar.event:reply calendar:calendar.free_busy:read \
task:task:read task:task:write \
task:tasklist:read task:tasklist:write \
im:message:readonly im:message.group_msg:get_as_user im:chat:read im:chat.members:read contact:user.base:readonly \
drive:drive.metadata:readonly"
scope 命名说明:飞书 OAuth scope 命名不完全统一,
search:docs:read带:read后缀,而search:message不带。这是飞书平台定义,非笔误。
将输出的 auth_url 展示给用户,请用户在浏览器中完成授权。授权后浏览器跳转到无法访问的页面,让用户复制地址栏完整 URL。
# 步骤 B:用回调 URL 换 Token
feishu-cli auth callback "<用户提供的回调URL>" --state "<步骤A输出的state>"
3. 执行搜索
登录后所有搜索命令自动从 ~/.feishu-cli/token.json 读取 Token,无需手动传递。
搜索云文档
搜索当前用户有权访问的飞书云文档和 Wiki。scope: search:docs:read
feishu-cli search docs "关键词" [选项]
选项
| 参数 | 类型 | 默认值 | 说明 |
|---|---|---|---|
--docs-types |
string | 全部 | 文档类型过滤(逗号分隔,小写) |
--count |
int | 20 | 返回数量(0-50) |
--offset |
int | 0 | 偏移量(offset + count < 200) |
--owner-ids |
string | — | 文件所有者 Open ID(逗号分隔) |
--chat-ids |
string | — | 文件所在群 ID(逗号分隔) |
-o json |
string | — | JSON 格式输出 |
文档类型(小写)
| 类型 | 说明 | 类型 | 说明 |
|---|---|---|---|
doc |
旧版文档 | docx |
新版文档 |
sheet |
电子表格 | slides |
幻灯片 |
bitable |
多维表格 | mindnote |
思维笔记 |
file |
文件 | wiki |
知识库文档 |
shortcut |
快捷方式 |
示例
# 基础搜索
feishu-cli search docs "产品需求"
# 只搜索新版文档和 Wiki
feishu-cli search docs "技术方案" --docs-types docx,wiki
# 搜索电子表格
feishu-cli search docs "数据报表" --docs-types sheet
# 分页获取更多
feishu-cli search docs "季度报告" --count 50
# 分页查询:获取第一页(20 条)
feishu-cli search docs "季度报告" --count 20 --offset 0
# 分页查询:获取第二页
feishu-cli search docs "季度报告" --count 20 --offset 20
# JSON 格式输出(适合程序解析)
feishu-cli search docs "产品需求" -o json
JSON 输出格式
{
"Total": 35367,
"HasMore": true,
"ResUnits": [
{
"DocsToken": "C29IdflghosjksxWKvNutR3UsXe",
"DocsType": "docx",
"Title": "产品需求文档 - Q2",
"OwnerID": "ou_46bb48e13f9ff5cfd4b60edae00678cd",
"URL": "https://feishu.cn/docx/C29IdflghosjksxWKvNutR3UsXe"
}
]
}
DocsToken 可以直接用于 feishu-cli doc get、doc export 等文档操作命令。
搜索消息
搜索飞书消息记录。scope: search:message
feishu-cli search messages "关键词" [选项]
选项
| 参数 | 类型 | 说明 |
|---|---|---|
--chat-ids |
string | 限定群聊范围(逗号分隔) |
--from-ids |
string | 限定发送者 ID(逗号分隔) |
--at-chatter-ids |
string | 限定被@的用户 ID(逗号分隔) |
--message-type |
string | 消息类型:file/image/media |
--chat-type |
string | 会话类型:group_chat/p2p_chat |
--from-type |
string | 发送者类型:bot/user |
--start-time |
string | 起始时间(Unix 秒级时间戳) |
--end-time |
string | 结束时间(Unix 秒级时间戳) |
--page-size |
int | 每页数量(默认 20) |
--page-token |
string | 分页 token(上一页返回) |
-o json |
string | JSON 格式输出 |
示例
# 搜索消息
feishu-cli search messages "上线"
# 搜索私聊消息(search-chats 无法搜到 p2p 会话,用此方式替代)
feishu-cli search messages "你好" --chat-type p2p_chat
# 搜索群聊中的文件消息
feishu-cli search messages "周报" --chat-type group_chat --message-type file
# 搜索机器人消息
feishu-cli search messages "告警" --from-type bot
# 限定时间范围
feishu-cli search messages "项目" --start-time 1704067200 --end-time 1704153600
# 限定特定群
feishu-cli search messages "会议" --chat-ids oc_xxx,oc_yyy
提示:搜索群聊 API(
search-chats)无法搜到 p2p 私聊会话。要查找私聊内容,使用search messages --chat-type p2p_chat。
JSON 输出格式
{
"MessageIDs": ["om_xxx", "om_yyy"],
"PageToken": "ea9dcb2f...",
"HasMore": true
}
返回的 MessageIDs 可用 feishu-cli msg get <message_id> 获取消息详情。
搜索应用
搜索飞书应用。注意:搜索应用的 scope 需在飞书开发者后台确认是否可用,部分应用可能未开通此权限。
feishu-cli search apps "关键词" [选项]
选项
| 参数 | 类型 | 说明 |
|---|---|---|
--page-size |
int | 每页数量(默认 20) |
--page-token |
string | 分页 token |
-o json |
string | JSON 格式输出 |
示例
feishu-cli search apps "审批"
feishu-cli search apps "OKR" --page-size 50
常见问题
| 问题 | 原因 | 解决 |
|---|---|---|
| "缺少 User Access Token" | 从未登录 | 执行两步式登录流程 |
| "User Access Token 已过期" | access + refresh token 都过期 | 重新登录 |
| 99991679 权限错误提到搜索应用 | 应用未开通搜索应用权限,或该 scope 在开发者后台不可用 | 在飞书开发者后台确认是否已开通对应权限 |
99991679 权限错误提到 search:docs:read |
登录时未包含 search:docs:read scope |
重新登录,scope 加上 search:docs:read |
| 搜索结果为空 | 关键词不匹配或无权限文档 | 尝试更宽泛的关键词,或检查文档权限 |
| offset + count 超过 200 | 飞书 API 限制 | 最多翻到第 200 条结果 |
完整的认证流程和 Token 管理请参考 feishu-cli-auth 技能。
与其他技能的分工
| 场景 | 使用技能 |
|---|---|
| 按关键词搜索文档/应用 | feishu-cli-search(本技能) |
| 按关键词搜索消息(含高级筛选) | feishu-cli-search(本技能) |
| 浏览群聊历史消息、搜索群聊列表 | feishu-cli-chat |
| Reaction/Pin/删除/获取消息详情 | feishu-cli-chat |
| 群聊信息管理、成员管理 | feishu-cli-chat |
搜索消息与浏览聊天记录的区别:搜索(search messages)用关键词跨会话检索,返回消息 ID 列表;浏览(msg history)获取指定会话的连续消息流。如果用户的意图是"找到包含某关键词的消息"用搜索,"看看某个群最近在聊什么"用浏览。
How to use feishu-cli-search on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add feishu-cli-search
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches feishu-cli-search from GitHub repository riba2534/feishu-cli and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate feishu-cli-search. Access the skill through slash commands (e.g., /feishu-cli-search) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
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
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share 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
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★50 reviews- ★★★★★Sakura Bansal· Dec 20, 2024
feishu-cli-search has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Amina Verma· Dec 16, 2024
feishu-cli-search fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Fatima Rao· Dec 12, 2024
feishu-cli-search is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Fatima Jain· Dec 12, 2024
Useful defaults in feishu-cli-search — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Dhruvi Jain· Dec 4, 2024
Keeps context tight: feishu-cli-search is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Oshnikdeep· Nov 23, 2024
feishu-cli-search has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Olivia Abbas· Nov 15, 2024
I recommend feishu-cli-search for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Michael Abebe· Nov 11, 2024
Keeps context tight: feishu-cli-search is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Yusuf Rahman· Nov 7, 2024
Registry listing for feishu-cli-search matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Fatima Gill· Nov 3, 2024
Solid pick for teams standardizing on skills: feishu-cli-search is focused, and the summary matches what you get after install.
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