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Agent Skill · 开发

lark-event(云雀活动)

lark-event 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

lark-event 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 15。

总安装 1,968,624周安装 83,744GitHub Stars 9,004下载 689,688核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:lark-event(云雀活动)
来源仓库:https://github.com/larksuite/cli
仓库路径:skills/lark-event
安装命令:
npx skills add https://github.com/larksuite/cli --skill lark-event
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/larksuite/cli --skill lark-event

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

lark-event 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。

通过 npx skills add 命令从 larksuite/cli 仓库安装,需确认权限和维护状态。使用前应核实是否会触发联网、命令执行或文件读写操作。建议结合原始 README 核验具体用法和功能边界。

来源仓库内路径:skills/lark-event

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/larksuite/cli --skill lark-event;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

lark-event 怎么安装?

在终端执行 npx skills add https://github.com/larksuite/cli --skill lark-event。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

lark-event 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

lark-event 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/larksuite/cli --skill lark-event 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

lark-event 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

lark-event 用的人多吗?

公开数据是累计安装 1,968,624 次,近一周安装 83,744 次,下载 689,688 次,GitHub 9,004 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

lark-event 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 9,004 星,维护活跃度相对可查。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
lark-event

云雀活动 · 本页

1,968,6249,004执行命令未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Lark Events

Prerequisite: Read ../lark-shared/SKILL.md first for authentication, --as user/bot switching, Permission denied handling, and safety rules.

Core commands

CommandPurpose
lark-cli event list [--json]List all subscribable EventKeys
lark-cli event schema <EventKey> [--json]Show an EventKey's params and output schema
lark-cli event consume <EventKey> [flags]Blocking consume; events → stdout NDJSON
lark-cli event status [--json] [--fail-on-orphan]Inspect the local bus daemon status
lark-cli event stop [--all] [--force]Stop the bus daemon

Common flags

FlagDescription
--param key=value / -pBusiness params (repeatable; comma-separated for multi-value). Unknown keys fail with valid names listed inline
--jq <expr>jq expression to filter / transform each event; empty output skips the event
--max-events NExit after N events. Default 0 = unlimited
--timeout DExit after duration D (e.g. 30s, 2m). Default 0 = no timeout. Whichever of --max-events / --timeout fires first wins
--output-dir <dir>Write each event as a file (relative paths only; prevents traversal)
--quietSuppress stderr diagnostics. AI should not use this — it silences the ready marker
`--as user\bot\auto`Identity for the session (see lark-shared)

Examples

# Default: stream every event for the key (no filter, no projection)
lark-cli event consume im.message.receive_v1 --as bot

# Grab one sample event to inspect payload shape
lark-cli event consume im.message.receive_v1 --max-events 1 --timeout 30s --as bot

# Run for 10 minutes then auto-exit
lark-cli event consume im.message.receive_v1 --timeout 10m --as bot

# Consume multiple EventKeys concurrently (one shape per process, no dispatcher)
lark-cli event consume im.message.receive_v1          --as bot > receive.ndjson &
lark-cli event consume im.message.reaction.created_v1 --as bot > reaction.ndjson &
wait

Call flow

  1. lark-cli event list --json → pick a legal key
  2. lark-cli event schema <key> --json → read resolved_output_schema + jq_root_path to determine field paths
  3. lark-cli event consume <key> [--jq '<expr>'] → consume

Subprocess contract

Ready marker

event consume's stderr emits a fixed line [event] ready event_key=<key>. Parent processes should block on stderr until this line appears, then start reading stdout. Do not fall back to sleep.

stdin EOF = graceful exit

event consume treats stdin close as a shutdown signal (wired for AI subprocess callers). < /dev/null / nohup / systemd's default StandardInput=null will cause an immediate graceful exit (stderr reason: signal). To keep running:

  • Feed stdin a source that never EOFs: < <(tail -f /dev/null)
  • Or run bounded: --max-events N / --timeout D

Exit codes & reason

On exit, the last stderr line is [event] exited — received N event(s) in Xs (reason:...).

exit codereasonTrigger
0reason: limit--max-events reached
0reason: timeout--timeout reached
0reason: signalCtrl+C / SIGTERM / stdin EOF
non-0Error:... (no exited line)Startup / runtime failure (permissions, network, params, config)

Orchestrators should treat reason: limit/timeout/signal (all exit 0) as "business completion" and non-zero as "failure".

Never kill -9

Avoid kill -9 on consume processes: for EventKeys with a PreConsume hook (those that register server-side subscriptions via OAPI), kill -9 skips the OAPI unsubscribe and leaks server-side subscriptions (symptoms: "subscription already exists" on restart, duplicate event delivery). Prefer SIGTERM or closing stdin.

One consume, one EventKey (multi-key = multi-shell)

The command takes exactly one positional argument; k1,k2 and wildcards are unsupported. Listening to N keys means N subprocesses — this is intentional:

  • One shape per process stdout; no dispatcher logic required in the AI
  • Fault isolation (one key failing doesn't affect others)
  • Independent --as / --jq / --max-events / --timeout per key

All N consumers share a single bus daemon (UDS local IPC), so the overhead is small

Writing jq via schema

event schema <key> --json is the source of truth for writing --jq. Four things to look at:

(1) Where fields start — see jq_root_path

  • Value "." → fields are at the top level, write .chat_id
  • Value ".event" → fields are inside a V2 envelope, write .event.chat_id

(2) Field list and types — see resolved_output_schema.properties.<name>

Each field carries type / description, and some also have format. Snippet (from event schema im.message.receive_v1 --json):

{
  "chat_id":     {"type":"string", "format":"chat_id",      "description":"Chat ID, prefixed with oc_"},
  "sender_id":   {"type":"string", "format":"open_id",      "description":"Sender open_id, prefixed with ou_"},
  "create_time": {"type":"string", "format":"timestamp_ms", "description":"Send time as ms-epoch string"}
}

(3) Field semantics — see the format tag

Lark-defined semantic tags (not JSON Schema's standard format). Common values: open_id / chat_id / message_id / timestamp_ms / email. Purpose: distinguish "same string type, different meanings" fields so you can reverse-lookup via API or convert formats.

(4) Decoded state — read the field's description

event consume runs Process hooks that may pre-decode some payload fields (flattening V2 envelopes, rendering .content to plain text, etc.) — behavior differs from raw OAPI. Always read the field's description before writing jq, especially for generic field names like content / data / body / payload.

Why it matters: blindly applying fromjson to an already-decoded text field makes jq error on every event and silently drop it — the consumer looks alive but emits nothing, with only a single WARN line buried on stderr. (This is the general behavior: any jq runtime error skips the event with a one-line WARN; the loop does not abort.)

Don't shortcut the schema: when projecting event schema --json with jq, do not strip .description from properties — that's the field that tells you whether a field is already decoded. Dump the full property objects, not just keys.


Aside: --param's valid parameters also live in the schema — the params section lists name / type / required / enum / default / description; section missing = this key accepts no --param.

Topic index

TopicReferenceCoverage
IMreferences/lark-event-im.mdCatalog of 11 IM EventKeys + shape notes (flat vs V2 envelope) + im.message.receive_v1 field gotchas (sender_id is open_id only; .content is plain text except for interactive cards) + common jq recipes (filter by chat_type / message_type / sender)

平台分布

Codex

33.9%
按下载量换算233,804

Claude

29.58%
按下载量换算204,010

Cursor

19.23%
按下载量换算132,627

Gemini CLI

9.33%
按下载量换算64,348

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/larksuite/cli --skill lark-event 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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