OpenClaw Lark/Feishu Plugin connects an OpenClaw agent to Lark or Feishu workspaces, allowing it to work with messages, documents, databases, spreadsheets, calendars, and tasks. It is for OpenClaw users who want their agent to read and update Lark/Feishu workspace data. The catalogue skills provide the agent workflows for operating those connected workspace features.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add larksuite/openclaw-lark --skill feishu-bitablegit clone --depth 1 https://github.com/larksuite/openclaw-larkWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/larksuite/openclaw-lark/feishu-bitable)<a href="https://agentmods.dev/skills/larksuite/openclaw-lark/feishu-bitable"><img src="https://agentmods.dev/badge/skills/larksuite/openclaw-lark/feishu-bitable/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/larksuite/openclaw-lark/feishu-bitable"><img src="https://agentmods.dev/badge/skills/larksuite/openclaw-lark/feishu-bitable.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk fail
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00159 | $0.03093 |
| Opus 5 | $0.00079 | $0.01546 |
| Sonnet 5 | $0.00032 | $0.00619 |
| Haiku 4.5 | $0.00016 | $0.00309 |
Grade A, and why
feishu-bitable scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
94% identical to feishu-bitable — 11 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 249 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feishu Bitable (多维表格) SKILL
🚨 执行前必读
- ✅ 创建数据表：支持两种模式 — ① 明确需求时，在
create时通过table.fields一次性定义字段（减少 API 调用）；② 探索式场景时，使用默认表 + 逐步修改字段（更稳定，易调整） - ⚠️ 默认表的空行坑：
app.create自带的默认表中会有空记录（空行）！插入数据前建议先调用feishu_bitable_app_table_record.list+batch_delete删除空行，避免数据污染 - ✅ 写记录前：先调用
feishu_bitable_app_table_field.list获取字段 type/ui_type - ✅ 人员字段：默认 open_id（ou_...），值必须是
[{id:"ou_xxx"}]（数组对象） - ✅ 日期字段：毫秒时间戳（例如
1674206443000），不是秒 - ✅ 单选字段：字符串（例如
"选项1"），不是数组 - ✅ 多选字段：字符串数组（例如
["选项1", "选项2"]） - ✅ 附件字段：必须先上传到当前多维表格，使用返回的 file_token
- ✅ 批量上限：单次 ≤ 500 条，超过需分批（批量操作是原子性的）
- ✅ 并发限制：同一数据表不支持并发写，需串行调用 + 延迟 0.5-1 秒
📋 快速索引：意图 → 工具 → 必填参数
| 用户意图 | 工具 | action | 必填参数 | 常用可选 |
|---|---|---|---|---|
| 查表有哪些字段 | feishu_bitable_app_table_field | list | app_token, table_id | - |
| 查记录 | feishu_bitable_app_table_record | list | app_token, table_id | filter, sort, field_names |
| 新增一行 | feishu_bitable_app_table_record | create | app_token, table_id, fields | - |
| 批量导入 | feishu_bitable_app_table_record | batch_create | app_token, table_id, records (≤500) | - |
| 更新一行 | feishu_bitable_app_table_record | update | app_token, table_id, record_id, fields | - |
| 批量更新 | feishu_bitable_app_table_record | batch_update | app_token, table_id, records (≤500) | - |
| 创建多维表格 | feishu_bitable_app | create | name | folder_token |
| 创建数据表 | feishu_bitable_app_table | create | app_token, name | fields |
| 创建字段 | feishu_bitable_app_table_field | create | app_token, table_id, field_name, type | property |
| 创建视图 | feishu_bitable_app_table_view | create | app_token, table_id, view_name, view_type | - |
🎯 核心约束（Schema 未透露的知识）
📚 详细参考文档
当遇到字段配置、记录值格式问题或需要完整示例时，查阅以下文档：
- 字段 Property 配置详解 - 每种字段类型创建/更新时需要的
property参数结构（单选的 options、进度的 min/max、关联的 table_id 等） - 记录值数据结构详解 - 每种字段类型在记录中对应的
fields值格式（人员字段只传 id、日期是毫秒时间戳、附件需先上传等） - 使用场景完整示例 - 8 个完整场景示例（创建表模式对比、批量导入、筛选查询、附件处理、关联字段等）
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 249 lines · 159 tokens per session scan A 33d864153124
feishu-bitable is a skill published in the GitHub repository larksuite/openclaw-lark (2,373 stars, last pushed 1mo ago), licensed MIT. It adds 159 tokens to every session and 3,093 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to feishu-bitable, differing in 11 lines, and is treated as a copy.
Other skills, from other repositories
smart-data-collection
A workflow for extracting structured information from images and documents such as PDFs, Word files, and spreadsheets, then storing it in a database.
lark-base
A guide for managing Lark Base, Feishu's spreadsheet-like database and workspace tool. It covers tables, fields, records, views, formulas, forms, dashboards, applications, workflows, and permissions.
feishu-bitable
A skill for managing Feishu Bitable, a database-like spreadsheet for organising structured records. It supports tables, fields, views, filters, and bulk changes.
mcp-sheet-cache-bridge
Keep Zapier Tables or another MCP-connected record store as the source of truth while Google Sheets-based tools read an event-driven cache tab.
airtable-cli
Lists bases, reads and writes records, manages tables and fields, filters and searches data in Airtable via the airtable-mcp CLI. Use when the task involves Airtable data or the user mentions airtable-mcp, bases, tables, records, or fields.
feishu-bitable
Feishu multi-dimensional table (Bitable) operations. Activate when user mentions tables, databases, or bitable links.