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Agent Skill · 研究检索

openclaw-feishu-quota-guard(OpenClaw feishu quota guard 搜索)

openclaw-feishu-quota-guard 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

openclaw-feishu-quota-guard 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 19,633。

总安装 5,527周安装 235GitHub Stars 公开资料未说明下载 1,936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
MIT-0
版本
0.2.0

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:openclaw-feishu-quota-guard(OpenClaw feishu quota guard 搜索)
来源仓库:https://github.com/herbertwyt/openclaw-feishu-quota-guard
安装命令:
openclaw skills install openclaw-feishu-quota-guard
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install openclaw-feishu-quota-guard

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于诊断和修复 OpenClaw 中因心跳、健康检查或后台任务导致的飞书/Lark 配额异常消耗。适合需要监控 API 使用情况并优化配额管理的用户,尤其关注 webhook 探测和后台服务的影响。通过分析日志和运行状态提供修复建议,需配合 OpenClaw 环境使用,依赖本地配置和网络访问权限。

安装前请确认具备网关管理权限,注意操作可能涉及服务重启或配置修改,建议在非高峰时段执行。维护状态和具体修复步骤需参考官方仓库文档,部分场景可能需要手动干预或额外授权。

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 OpenClaw;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 openclaw skills install openclaw-feishu-quota-guard;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

openclaw-feishu-quota-guard 怎么安装?

在终端执行 openclaw skills install openclaw-feishu-quota-guard。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

openclaw-feishu-quota-guard 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

openclaw-feishu-quota-guard 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 openclaw skills install openclaw-feishu-quota-guard 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。

openclaw-feishu-quota-guard 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

openclaw-feishu-quota-guard 用的人多吗?

公开数据是累计安装 5,527 次,近一周安装 235 次,下载 1,936 次。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。

openclaw-feishu-quota-guard 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

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。
  • 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 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
openclaw-feishu-quota-guard

OpenClaw feishu quota guard 搜索 · 本页

5,527—执行命令MIT-0通过

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

name
openclaw-feishu-quota-guard
description
Use when a user wants OpenClaw itself to diagnose or fix Feishu/Lark quota burn caused by heartbeats, health checks, webhook probes, or overly expensive background runs. Start by running the bundled run-once fixer, then only do manual follow-up if custom gateway or webhook code is detected.

OpenClaw Feishu Quota Guard

Use this skill when OpenClaw is connected to Feishu/Lark and a user reports that free quota or paid API budget is draining unexpectedly.

This skill is based on a short Bilibili video about OpenClaw + Feishu quota burn and cross-checked against current OpenClaw docs. The likely failure mode is not "chat usage" itself, but background traffic:

  • OpenClaw heartbeat runs that still hit a cloud model
  • Feishu webhook or custom gateway health probes that accidentally trigger model work

Read references/source-notes.md only if you need the exact source-backed assumptions.

Quick Start

  1. Run the bundled fixer in the native shell for that machine:

- macOS/Linux: bash scripts/run-once.sh --dry-run - Windows PowerShell: powershell -ExecutionPolicy Bypass -File scripts/run-once.ps1 --dry-run - Any OS with Python: python scripts/apply_feishu_quota_fix.py --dry-run

  1. If the summary only reports official/current OpenClaw heartbeat settings, run the same command without --dry-run.
  2. If the summary reports custom webhook or gateway health routes, keep the automatic heartbeat fix and then inspect those files manually.
  3. Restart the relevant process and verify from logs that repeated probes no longer trigger expensive model calls.

Default behavior of the bundled fixer

The bundled fixer makes only safe automatic changes to standard OpenClaw config:

  • agents.defaults.heartbeat.every = "1h"
  • agents.defaults.heartbeat.lightContext = true
  • agents.defaults.heartbeat.isolatedSession = true
  • if target is missing, set target = "none"

If you want a full stop instead of throttling, run:

bash scripts/run-once.sh --mode disable

On Windows:

powershell -ExecutionPolicy Bypass -File scripts/run-once.ps1 --mode disable

That sets:

  • agents.defaults.heartbeat.every = "0m"

Workflow

1. Confirm the topology first

Do not patch blindly.

  • If the install uses the bundled/current Feishu plugin, treat this as a heartbeat-cost problem first.
  • If the install uses a webhook bridge or custom gateway, inspect the health route before touching heartbeat settings.

Useful search terms:

  • channels.feishu
  • @openclaw/feishu
  • heartbeat
  • HEARTBEAT.md
  • connectionMode
  • webhook
  • verificationToken
  • health
  • gateway

2. Fix path A: reduce or cheapen OpenClaw heartbeat work

Use this path for the official/current plugin, or anytime logs show scheduled heartbeat runs causing the spend.

Focus on:

  • ~/.openclaw/openclaw.json or the workspace config the user actually runs
  • agents.defaults.heartbeat
  • agents.list[].heartbeat
  • HEARTBEAT.md

Preferred order of fixes:

  1. First run the bundled fixer in throttle mode.

It applies the lowest-risk cost reduction settings supported by current OpenClaw heartbeat docs.

  1. If heartbeat is not needed, disable it or make the heartbeat prompt effectively empty.

OpenClaw docs say an effectively empty HEARTBEAT.md skips the heartbeat run and saves API calls.

  1. If heartbeat is needed, lower frequency first.

Safe first move: change every from a short interval to 1h or longer.

  1. Reduce token and context cost.

Prefer lightContext: true, isolatedSession: true when appropriate, and avoid sending heartbeat output anywhere unless the user really wants it.

  1. Route heartbeat away from an expensive cloud model.

If the install supports a separate heartbeat model, use a cheap or local model for heartbeat-only checks.

  1. Keep HEARTBEAT.md tiny.

A bloated checklist wastes tokens every run.

When editing configs manually, prefer minimal changes like:

{
  "agents": {
    "defaults": {
      "heartbeat": {
        "every": "1h",
        "lightContext": true,
        "target": "none"
      }
    }
  }
}

Only add a heartbeat-specific local model if the config format in that install already supports it.

3. Fix path B: stop Feishu/webhook health probes from touching the model

Use this path for older installs, custom bridges, or any codebase where /health, /ready, or webhook verification ends up invoking OpenClaw chat/model logic.

Goal: liveness checks must return a cheap static success unless the user explicitly wants an end-to-end synthetic test.

Preferred order of fixes:

  1. Do not auto-patch arbitrary app code unless the relevant route is obvious and isolated.
  2. Separate liveness from end-to-end checks.

/health should usually return a static 200 OK plus lightweight process info.

  1. If a real downstream check is required, cache the successful result.

A 24-hour cache is a good default for "bot still works" validation when the alternative is paying every minute.

  1. Never let Feishu verification or heartbeat probes call the main chat pipeline.
  2. If a custom bridge currently pings the model every 60 seconds, patch that route first before changing user-facing chat behavior.

For route handlers, acceptable outcomes are:

  • static ok
  • cached status object
  • cheap local state check

Avoid:

  • calling the main message handler
  • creating a new OpenClaw chat turn
  • invoking the paid model just to answer a health probe

4. Verify after the patch

After editing:

  1. Restart the OpenClaw gateway, plugin host, or custom bridge.
  2. Watch logs for 3-5 minutes.
  3. Confirm one of these outcomes:

- heartbeat frequency dropped to the intended interval - /health still gets hit, but no model invocation follows - quota burn rate stops climbing abnormally

If the user is on Docker, check container logs rather than assuming host paths.

Guardrails

  • Do not change unrelated chat routing.
  • Do not remove webhook verification unless the user is intentionally leaving webhook mode.
  • Prefer the smallest patch that stops repeated paid calls.
  • If the system mixes official Feishu config with custom gateway code, patch the custom health route first and then review heartbeat settings.
  • If the bundled fixer already solved the standard heartbeat cost issue, say so clearly and stop there unless custom webhook code still appears in the scan.

平台分布

OpenClaw

81.43%
按下载量换算1,576

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install openclaw-feishu-quota-guard 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。目前只有一个公开来源,建议同时核对源仓库。

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