Feishu Bitable Creator

Feishu Bitable Creator

Creates clean, ready-to-use Feishu Bitable tables with automatic cleanup and data population.

Authentication & Permissions

This skill requires a pre-configured Feishu (Lark) integration via OpenClaw's channel system. It does not accept API keys directly from the user.

How Authentication Works

Feishu Channel Configuration: Your OpenClaw instance must have the Feishu channel enabled and configured with a valid app ID and app secret in ~/.openclaw/openclaw.json: { "channels": { "feishu": { "enabled": true, "appId": "cli_xxxxxxxxxxxxxxxx", "appSecret": "your-app-secret" } } } Token Management: OpenClaw's Feishu extension automatically handles token acquisition and refresh using the configured app credentials. No manual token management is required. User Consent: When creating a table, the tool uses the agent's own identity (the Feishu app/bot). The addBitableAdmin() function requires the owner's explicit user_id obtained from the conversation context, ensuring consent.

Required Feishu App Permissions

Your Feishu app must have these permissions granted: PermissionPurposebitable:appCreate and manage Bitable appsdrive:permission:manageAdd users as admins to documentsdrive:drive:readRead drive contents

Security Notes

⚠️ No User-Supplied Credentials: This skill does NOT accept API keys, tokens, or secrets from user prompts. All authentication is handled through OpenClaw's secure channel configuration. ⚠️ Scope Limitation: The skill only performs actions on Bitable tables it creates. It cannot access existing tables without explicit sharing. ⚠️ Admin Addition Requires Explicit User ID: Adding an admin requires the specific user_id from conversation context — the agent cannot arbitrarily add unknown users.

Setup Instructions

Before using this skill, ensure your OpenClaw host admin has: Created a Feishu app at https://open.feishu.cn/app Enabled the required permissions in the Feishu app console Configured the app ID and secret in ~/.openclaw/openclaw.json Restarted the OpenClaw gateway to apply changes For detailed setup, see: https://docs.openclaw.ai/channels/feishu Problem with default Bitable creation: Feishu creates 10 empty placeholder rows by default Creates 4 default columns (文本, 单选, 日期, 附件) that are often unused Primary field is always named "文本" which is not descriptive Creator has full control, but human owner has no permissions This skill solves these issues: ✅ Automatically deletes empty placeholder rows and default columns ✅ Intelligently renames primary field based on table name ✅ Adds owner as admin with full permissions ✅ Provides clean slate for your actual data

Quick Start

// 1. Create table (auto-cleans placeholder rows & default columns) const table = await feishu_bitable_create_app({ name: "项目名称清单" }); // Returns: { app_token, url, table_id, primary_field_name, cleaned_placeholder_rows, cleaned_default_fields } // 2. Add owner as admin (REQUIRED - get user_id from conversation context) await addBitableAdmin({ app_token: table.app_token, user_id: "ou_xxxxxxxxxxxxxxxx" // Get from conversation context or Feishu user profile }); // 3. Create RICH fields with tags/categories (建议根据场景选择) // 参考 "Designing Rich Fields" 章节，选择适合的维度字段 // 4. Add records with complete tag information await feishu_bitable_create_record({ app_token: table.app_token, table_id: table.table_id, fields: { [table.primary_field_name]: "项目A", "标签": ["AI", "开源"], // MultiSelect for filtering "分类": "技术", // SingleSelect for grouping "状态": "进行中", // SingleSelect for workflow "优先级": "高" // SingleSelect for sorting } }); return table.url;

Designing Rich Fields (发挥多维表格价值)

💡 核心建议: 为了让多维表格真正发挥作用，建议设计丰富的标签/分类字段，但根据实际场景灵活选择。

推荐的字段设计思路

根据数据类型，考虑添加以下维度字段： 数据场景建议字段用途项目管理状态、优先级、负责人、截止日期追踪进展，分配任务研究/调研分类、标签、来源、评分归类信息，评估价值产品/功能模块、优先级、状态、负责人产品规划，迭代管理客户/用户类型、阶段、标签、负责人客户分层，跟进管理竞品分析分类、评分、标签、来源对比分析，筛选查看

字段类型选择指南

字段名类型适用场景标签MultiSelect一个项目可属于多个类别，用于交叉筛选分类SingleSelect一级分类，用于分组统计状态SingleSelect有明确流转阶段，如待办→进行中→完成优先级SingleSelect需要排序或区分重要性负责人User需要分配到人日期DateTime有时间节点要求评分Number需要量化评估来源SingleSelect需要追踪信息出处

实际设计示例

示例1：开源大模型研究 const fields = [ { name: "模型名称", type: 1 }, { name: "开发团队", type: 1 }, { name: "参数量", type: 1 }, // 维度字段（根据数据特点选择） { name: "技术标签", type: 4 }, // ["MoE", "多语言", "代码", "轻量级"] { name: "地区", type: 3 }, // "美国"/"中国"/"欧洲" { name: "模型类型", type: 3 }, // "通用"/"代码"/"推理" { name: "适用场景", type: 4 }, // ["企业部署", "端侧运行", "科研"] { name: "开源协议", type: 3 }, // "Apache-2.0"/"MIT" { name: "发布日期", type: 5 }, { name: "特点描述", type: 1 } ]; 示例2：工作任务清单 const fields = [ { name: "任务名称", type: 1 }, { name: "描述", type: 1 }, // 维度字段 { name: "分类", type: 3 }, // "技术"/"产品"/"运营" { name: "状态", type: 3 }, // "待办"/"进行中"/"已完成" { name: "优先级", type: 3 }, // "P0"/"P1"/"P2" { name: "负责人", type: 11 }, // @username { name: "截止日期", type: 5 }, { name: "标签", type: 4 } // ["紧急", "重要", "外部依赖"] ];

设计原则

先想怎么用：先思考用户会如何筛选/分组/排序数据 适度原则：字段不是越多越好，选择真正能区分数据的维度 数据可得：确保收集数据时能填上这些字段，不要设计无法获取的维度 灵活调整：如果某个字段使用率很低，后续可以删除或修改

检验标准

设计完字段后，问自己： ❓ 用户能按哪些维度筛选数据？ ❓ 能按哪些维度分组查看？ ❓ 能按哪些维度排序？ ❓ 数据收集时这些字段是否容易获取？ 如果以上问题都有明确答案，说明字段设计合理！

实际示例：开源大模型表格

// 创建表格 const table = await feishu_bitable_create_app({ name: "全球开源大模型TOP10" }); // 添加管理员 await addBitableAdmin({ app_token: table.app_token, user_id: bossUserId }); // 创建丰富的字段（带标签/分类） const fields = [ { name: "排名", type: 2 }, // Number { name: "模型名称", type: 1 }, // Text { name: "开发团队", type: 1 }, // Text { name: "参数量", type: 1 }, // Text { name: "标签", type: 4, property: { options: [ // MultiSelect { name: "MoE" }, { name: "多语言" }, { name: "代码" }, { name: "轻量级" }, { name: "推理优化" }, { name: "国产" } ]}}, { name: "地区", type: 3, property: { options: [ // SingleSelect { name: "美国" }, { name: "中国" }, { name: "欧洲" }, { name: "中东" }, { name: "其他" } ]}}, { name: "类型", type: 3, property: { options: [ // SingleSelect { name: "通用模型" }, { name: "代码模型" }, { name: "推理模型" } ]}}, { name: "开源协议", type: 3, property: { options: [ // SingleSelect { name: "Apache-2.0" }, { name: "MIT" }, { name: "Llama License" }, { name: "Qwen License" } ]}}, { name: "GitHub星标", type: 2 }, // Number { name: "发布日期", type: 5 }, // DateTime { name: "特点", type: 1 }, // Text { name: "适用场景", type: 4, property: { options: [ // MultiSelect { name: "企业部署" }, { name: "端侧运行" }, { name: "科学研究" }, { name: "商业应用" }, { name: "教育学习" } ]}} ]; for (const field of fields) { await feishu_bitable_create_field({ app_token: table.app_token, table_id: table.table_id, field_name: field.name, field_type: field.type, property: field.property }); } // 添加带完整标签的数据 await feishu_bitable_create_record({ app_token: table.app_token, table_id: table.table_id, fields: { [table.primary_field_name]: "Llama 3", "模型名称": "Llama 3", "排名": 1, "开发团队": "Meta", "参数量": "8B/70B/400B", "标签": ["多语言"], "地区": "美国", "类型": "通用模型", "开源协议": "Llama License", "GitHub星标": 50000, "发布日期": 1713398400000, // 2024-04-18 "特点": "开源模型领导者，性能对标GPT-4", "适用场景": ["企业部署", "商业应用", "科学研究"] } });

Add Owner as Admin

IMPORTANT: Tool creates table but does NOT add permissions. You must add the owner as admin manually. /** * Add a user as admin to a Bitable table * @param app_token - The Bitable app token * @param user_id - The user's open_id (from conversation context) */ async function addBitableAdmin({ app_token, user_id }) { const token = await getTenantAccessToken(); const response = await fetch( `https://open.feishu.cn/open-apis/drive/v1/permissions/${app_token}/members/batch_create?type=bitable`, { method: 'POST', headers: { 'Content-Type': 'application/json', 'Authorization': `Bearer ${token}` }, body: JSON.stringify({ members: [{ member_type: 'openid', member_id: user_id, perm: 'full_access' }] }) } ); const result = await response.json(); if (result.code === 0) { console.log('✅ Successfully added owner as admin'); return result.data; } else { throw new Error(result.msg); } }

Required Permissions

bitable:app - Manage Bitable apps drive:permission:manage - Manage document permissions

Primary Field Naming

Table name containsPrimary field becomes"项目""项目名称""研究""研究名称""测试""测试项""数据""数据项""任务""任务名称""记录""记录项"Other (≤6 chars)Use table name as-isOther (>6 chars)First 4 chars + "..."

Common Field Types

Type IDNameUse For1TextNames, descriptions2NumberCounts, amounts3SingleSelectStatus, priority4MultiSelectTags, features5DateTimeDates, deadlines7CheckboxDone/Incomplete11UserAssignees

Complete Example: Research Data Table with Rich Tags

• async function createBitableForBoss({ tableName, records, bossUserId }) {
• // 1. Create table
• const table = await feishu_bitable_create_app({ name: tableName });
• // 2. Add owner as admin
• await addBitableAdmin({
• app_token: table.app_token,
• user_id: bossUserId
• });
• // 3. Create RICH fields with tags/categories (关键！)
• const fields = [
• { name: "排名", type: 2 },
• { name: "名称", type: 1 },
• { name: "标签", type: 4 }, // MultiSelect - 最关键！
• { name: "分类", type: 3 }, // SingleSelect
• { name: "状态", type: 3 }, // SingleSelect
• { name: "优先级", type: 3 }, // SingleSelect
• { name: "负责人", type: 11 }, // User
• { name: "来源", type: 3 }, // SingleSelect
• { name: "评分", type: 2 }, // Number
• { name: "日期", type: 5 }, // DateTime
• { name: "描述", type: 1 } // Text
• ];
• for (const field of fields) {
• await feishu_bitable_create_field({
• app_token: table.app_token,
• table_id: table.table_id,
• field_name: field.name,
• field_type: field.type
• });
• }
• // 4. Add records with complete tags
• for (const record of records) {
• await feishu_bitable_create_record({
• app_token: table.app_token,
• table_id: table.table_id,
• fields: {
• [table.primary_field_name]: record.name,
• "名称": record.name,
• "标签": record.tags, // 必填！
• "分类": record.category, // 必填！
• "状态": record.status || "待处理",
• "优先级": record.priority || "中",
• "来源": record.source || "搜索",
• "描述": record.description
• }
• });
• }
• return {
• url: table.url,
• message: `✅ Table created with rich tags: ${table.url}`
• };
• }
• // Usage
• const result = await createBitableForBoss({
• tableName: "AI开源项目研究",
• records: [
• {
• name: "AutoGPT",
• tags: ["AI代理", "自动化", "热门"], // MultiSelect
• category: "智能体", // SingleSelect
• priority: "高",
• source: "GitHub",
• description: "自主递归任务执行AI代理"
• }
• ],
• bossUserId: "ou_xxxxxxxxxxxxxxxx" // Replace with actual user's open_id
• });
• { name: "GitHub星标", type: 2 },
• { name: "使用场景", type: 4 }
• ],
• records: [{
• "AI框架对比": "AutoGPT",
• "框架名称": "AutoGPT",
• "GitHub星标": 157000,
• "使用场景": ["自动化", "研究"]
• }],
• bossUserId: "ou_xxxxxxxxxxxxxxxx" // Replace with actual user's open_id
• });
• ## Tips
• 1. **设计丰富的标签字段**: 为了让多维表格发挥作用，建议根据数据特点添加标签、分类、状态等维度字段（参考 "Designing Rich Fields" 章节）
• 2. **根据场景选择字段**: 不同数据类型需要不同的维度字段，如项目管理需要"状态"，研究调研需要"来源"，灵活设计
• 3. **先想怎么用**: 设计字段前先思考用户会如何筛选/分组/排序数据
• 4. **Multi-select values**: Pass as array: `["标签A", "标签B"]`
• 5. **User ID**: Get from conversation context (e.g., `ou_xxxxxxxxxxxxxxxx`)
• 6. **Cleanup verified**: Tool returns `cleaned_placeholder_rows` and `cleaned_default_fields`
• 7. **Field order**: Create fields first, then add records
• ## Error Handling
• | Error | Cause | Solution |
• |-------|-------|----------|
• | FieldNameNotFound | Wrong primary field name | Check `primary_field_name` in result |
• | 400 Bad Request | Invalid field type/value | Verify field_type ID |
• | Permission Denied | Missing `drive:permission:manage` | Check app permissions |
• | User Not Found | Wrong user_id format | Use `openid` type |
• ## Output Format
• ✅ Table "项目名称" created successfully!
• 🔗 URL: https://my.feishu.cn/base/xxxxxxxxxxxxx
• 🧹 Cleanup: 10 placeholder rows, 4 default columns deleted
• 👤 Owner: Added as admin (full_access)
• 📊 Records: X records added
• 📝 Fields: 名称, 标签, 分类, 状态, 优先级, 负责人, 日期, 描述
• 💡 Tip: 建议添加标签/分类/状态等维度字段，让表格支持多维筛选和分组
• **设计检查建议**:
• 是否可以根据标签交叉筛选数据？
• 是否可以按分类分组查看？
• 是否可以按状态/优先级排序？
• 数据收集时这些字段是否容易获取？
• 如果以上问题都有答案，说明字段设计合理！
• ✅ 优先级 (SingleSelect) - for sorting