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Agent Skill · 研究检索

idleclaw(idleclaw 搜索)

idleclaw 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。

idleclaw 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,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 10,574。

总安装 12,408周安装 533GitHub Stars 1下载 4,349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
1.2.1

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:idleclaw(idleclaw 搜索)
来源仓库:https://github.com/futurejunk/idleclaw
安装命令:
openclaw skills install idleclaw
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 idleclaw

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。

idleclaw 允许共享本地 Ollama 推理资源或接入社区算力池。适合在 OpenClaw 中 API 额度不足时获取额外计算支持。通过 clawhub 安装,连接社区节点进行模型推理。需确认是否开放本地端口及联网权限,防止意外暴露服务。idleclaw 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

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 idleclaw;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

idleclaw 怎么安装?

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

idleclaw 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。

idleclaw 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 idleclaw 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。

idleclaw 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。

idleclaw 用的人多吗?

公开数据是累计安装 12,408 次,近一周安装 533 次,下载 4,349 次,GitHub 1 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。

idleclaw 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

  • 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。

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 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。

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
idleclaw

idleclaw 搜索 · 本页

12,4081执行命令MIT-0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

name
idleclaw
description
Share your idle Ollama inference with the community, or use community
tools
Bash, Read
metadata
{"clawdbot":{"emoji":"🦀","os":["darwin","linux"],"requires":{"bins":["python3","ollama"]}}}

IdleClaw

A distributed inference network for Ollama. Contributors share idle GPU/CPU capacity, consumers use community compute when their API credits run out.

Modes

Contribute — Share your idle inference

Start your machine as an inference node. Your local Ollama models become available to the community.

cd "$SKILL_DIR" && python scripts/contribute.py

This connects to the IdleClaw routing server, registers your available models, and begins accepting inference requests. Press Ctrl+C to stop.

Requirements: Ollama must be running with at least one model pulled.

Consume — Use community inference

Send a chat request to the community network instead of running locally.

cd "$SKILL_DIR" && python scripts/consume.py --model <model-name> --prompt "<your message>"

Streams the response to stdout as tokens arrive.

Status — Check network health

See how many nodes are online and what models are available.

cd "$SKILL_DIR" && python scripts/status.py

Configuration

VariableDefaultDescription
IDLECLAW_SERVERhttps://api.idleclaw.comRouting server URL
OLLAMA_HOSThttp://localhost:11434Local Ollama endpoint

Security

External Endpoints

This skill contacts the following external endpoints:

  1. IdleClaw Routing Server (IDLECLAW_SERVER, default https://api.idleclaw.com)

- Contribute mode: Opens a WebSocket connection to register as an inference node. Sends: node ID, available model names, and inference responses. Receives: inference requests (model name, chat messages, and optional tool schemas). - Consume mode: Sends HTTP POST to /api/chat with model name and chat messages. Receives: streaming token response via SSE. - Status mode: Sends HTTP GET to /health and /api/models. Receives: server health info and available model list.

  1. Local Ollama (OLLAMA_HOST, default http://localhost:11434)

- Contribute mode only: Calls Ollama's API to list models and run inference. All communication stays on localhost.

Data Handling

  • No user data is persisted locally or on the server beyond the active session.
  • No credentials or API keys are required or stored.
  • All communication is text — every message between the server, the node, and Ollama is JSON text over WebSocket or HTTP. No binary data, file uploads, images, or executable payloads are transmitted.
  • No local code execution — the contributor node is a relay. It forwards JSON inference parameters to Ollama and streams JSON responses back to the server. The node does not execute tools, run shell commands, or access the filesystem. Any tool execution is handled server-side after response validation.
  • Chat messages (text strings) are transmitted from consumer to server to contributor node for inference, then discarded.
  • No telemetry or analytics are collected.
  • In contribute mode, the routing server sends JSON inference requests to the node, which forwards them to your local Ollama instance. Ollama returns a JSON text response which the node relays back. Contributors can point IDLECLAW_SERVER to a self-hosted instance.
  • In consume mode, text prompts are sent to the routing server which routes them to an available contributor node.

Sanitization

Client-side:

  • Inference parameters are validated before passing to Ollama: only whitelisted keys are forwarded (model, messages, stream, think, keep_alive, options, tools, format). Unknown keys are stripped.
  • Requested model must match a model the node registered — requests for unregistered models are rejected.
  • Message limits enforced: max 50 messages per request, max 10,000 characters per message content.
  • Only known response fields are forwarded back to the server (role, content, thinking, tool_calls).
  • In consume mode, model names are validated against a strict pattern (alphanumeric, colons, periods, hyphens only). In contribute mode, requested models must match a model the node registered from Ollama.
  • Server URLs are validated as HTTP/HTTPS URLs before use.
  • No shell commands are constructed from user input — all execution is Python-only.
  • No local files are read or accessed — the skill only communicates with Ollama and the routing server.

Server-side (routing server):

  • IP-based rate limiting on all endpoints: chat (20 RPM), node registration (5 RPM), general (60 RPM).
  • Input validation: max 50 messages per request, 10,000 chars per message, 64-char model names, roles restricted to user and assistant.
  • Output sanitization: response content is stripped of markup tags before delivery to consumers.
  • Node registration limits: max 3 nodes per IP, max concurrent requests clamped to 1-10.
  • Tool execution safeguards: schema validation, argument type checking, 15-second timeout, per-node rate limiting (20 calls/min).
  • Server binds to localhost only, accessed through Caddy reverse proxy with auto-TLS.
  • Red team tested with documented findings and mitigations (security assessment on GitHub).

Installation

Run the installer to set up Python dependencies:

cd "$SKILL_DIR" && bash install.sh

平台分布

OpenClaw

73.71%
按下载量换算3,206

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

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 idleclaw 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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