lark-im

A tool for using Feishu chat, including one-to-one and group conversations. It works with messages, replies, threads, emoji reactions, shared files and images, group members, and interactive message cards.

In plain words
What is it for?
Use it to send or reply to messages, search chats, download shared files, manage group members, create chats, add reactions, and handle card-button responses.
Why use it?
It removes the need to handle chat history, conversation identifiers, and attached resources manually. It also covers group and message actions in one place.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/larksuite/cli/lark-im
Any agent
npx skills add larksuite/cli --skill lark-im
Clone the repo
git clone --depth 1 https://github.com/larksuite/cli

Made for: Claude Code, Codex.

Per session 140 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,267 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00140 $0.06267
Opus 5 $0.00070 $0.03134
Sonnet 5 $0.00028 $0.01253
Haiku 4.5 $0.00014 $0.00627

Measured 3d ago against content hash 8d272993a64b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

lark-im 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 3d 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.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

  • lark-im — 88% identical, 52 lines differ
  • lark-im — 81% identical, 78 lines differ
skills/lark-im/SKILL.md · 275 lines

How it starts

The opening of the file, as written. The whole thing — 275 lines — stays where its author put it; the contents beside it link to each section on GitHub.

im (v1)

CRITICAL — 开始前 MUST 先用 Read 工具读取 ../lark-shared/SKILL.md,其中包含认证、权限处理

Core Concepts

  • Message: A single message in a chat, identified by message_id (om_xxx). Supports types: text, post, image, file, audio, video, sticker, interactive (card), share_chat, share_user, merge_forward, etc.
  • Chat: A group chat or P2P conversation, identified by chat_id (oc_xxx).
  • Thread: A reply thread under a message, identified by thread_id (om_xxx or omt_xxx).
  • Reaction: An emoji reaction on a message.
  • Flag: A bookmark on a message or thread.
  • Feed Shortcut: A chat pinned to the current user's feed sidebar, identified by feed_card_id (an oc_xxx open_chat_id for CHAT type).
  • Feed Group: A tag that groups feed cards in the feed list, identified by feed_group_id (ofg_xxx). Members are feed cards, each identified by feed_id + feed_type. Two types: normal (members managed explicitly) and rule (members auto-derived from rules).

Resource Relationships

Chat (oc_xxx)
├── Message (om_xxx)
│   ├── Thread (reply thread)
│   ├── Reaction (emoji)
│   └── Resource (image / file / video / audio)
└── Member (user / bot)

Important Notes

AppLink and Share Links

Prefer CLI-returned links: use chat_app_link to open joined conversations, message_app_link to open messages, and share_link to invite others to groups. If manually building a joined-conversation AppLink, use https://<applink_host>/client/chat/open?openChatId=<oc_xxx>, never chatId=<oc_xxx> or lark://...chat_id=<oc_xxx>.

Identity and Token Mapping

  • --as user means user identity and uses user_access_token. Calls run as the authorized end user, so permissions depend on both the app scopes and that user's own access to the target chat/message/resource.
  • --as bot means bot identity and uses tenant_access_token. Calls run as the app bot, so behavior depends on the bot's membership, app visibility, availability range, and bot-specific scopes.
  • If an IM API says it supports both user and bot, the token type changes who the operator is. The same API can succeed with one identity and fail with the other because owner/admin status, chat membership, tenant boundary, or app availability are checked against the current caller.

Read the full file on GitHub · 275 lines

Files

What ships with it

60 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.

Changes

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.

  1. 3d ago First seen · 275 lines · 140 tokens per session scan A 8d272993a64b

Subscribe to this mod's changes

lark-im is a skill published in the GitHub repository larksuite/cli (16,925 stars, last pushed yesterday), licensed MIT. It adds 140 tokens to every session and 6,267 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

hr-onboarding

A new-hire onboarding plan as a single page — first week schedule, buddy + manager intro, learning track, equipment checklist, and "you're set when…" outcomes. Use when the brief mentions "onboarding", "new hire", "first week plan", or "入职".

nexu-io/open-design · 62 tokens

feishu

Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.

Hmbown/CodeWhale · 33 tokens

reflect

Review recent work, find repeated workflow patterns, and suggest reusable skills, agents, commands, config changes, or playbooks. Use when the user asks to learn from past sessions, improve recurring workflows, or identify what should be turned into reusable agent instructions.

alvinunreal/oh-my-opencode-slim · 53 tokens

mochi-remind

Handle due reminders — notify the user with natural language and mark them done.

kirodotdev/KiroCrew · 20 tokens

organize-threads

猫猫辅助整理未分类 thread,分析标题和元数据,建议合适的标签。 Use when: 用户说"帮我整理"、"分类 thread"、点击整理按钮。 Not for: 删除/编辑标签本身。 Output: 按 thread 的标签建议列表。.

zts212653/clowder-ai · 65 tokens

change-keybinding

Customize Warp keyboard shortcuts (keybindings, keymappings) by editing the user's keybindings.yaml file. Use when the user asks to remap a key combination, rebind an action, change a shortcut, or remove a default keybinding (e.g. "change ctrl+space to ctrl+s", "rebind the command palette to cmd+p", "remove the…

warpdotdev/warp · 82 tokens