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Agent Skill · 研究检索

kimi-agent-policy(Kimi Agent policy 搜索)

kimi-agent-policy 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。

kimi-agent-policy 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;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 10,935。

总安装 11,919周安装 512GitHub Stars 公开资料未说明下载 4,178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
1.1.0

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:kimi-agent-policy(Kimi Agent policy 搜索)
来源仓库:https://github.com/2233admin/kimi-agent-policy
安装命令:
openclaw skills install kimi-agent-policy
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 kimi-agent-policy

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。

移植 Kimi 代理工具的完整使用策略至 OpenClaw 运行环境。涵盖步数控制、网页/图像检索、ipython 内存管理等核心功能模块。自动适配 Kimi 平台的工具调用规范与参数传递格式要求。需导入 Moonshot AI 开发者密钥并绑定有效订阅计划额度。部分高级功能可能受地区政策影响存在服务可用性差异。

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 kimi-agent-policy;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

    它需要接触敏感数据,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

kimi-agent-policy 怎么安装?

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

kimi-agent-policy 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。

kimi-agent-policy 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

kimi-agent-policy 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。

kimi-agent-policy 用的人多吗?

公开数据是累计安装 11,919 次,近一周安装 512 次,下载 4,178 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。

kimi-agent-policy 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

  • 需要接触敏感数据,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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
kimi-agent-policy

Kimi Agent policy 搜索 · 本页

11,919—接触敏感数据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
kimi-agent-policy
version
1.1.0
description
Kimi (Moonshot AI) agent tool-use policy ported to OpenClaw. Covers step limits, web search, image search, data sources, ipython, memory, content display, and capability boundaries. All Kimi-specific tools are mapped to available OpenClaw skills.
author
curry-clan
keywords
[kimi, moonshot, agent-policy, tool-use, memory, web-search, image-search, openclaw]
metadata
openclaw
emoji
🌙

kimi-agent-policy

Kimi agent tool-use policy and behavior rules, adapted for OpenClaw. Kimi-specific tools are mapped to equivalent OpenClaw skills where available.

Trigger Conditions

  • Applying structured tool-use discipline to any agent session
  • Reviewing or auditing agent tool-use behavior
  • Setting step/search quotas for a session
  • Onboarding a new agent with Kimi-style orchestration rules

Tool Mapping (Kimi → OpenClaw)

Kimi ToolOpenClaw EquivalentSkillAPI Key?
web_searchweb_searchbuilt-in ✅No
web_open_urlagent-browser fetchagent-browserNo
search_image_by_textagent-browser (open image search)agent-browserNo
search_image_by_imageagent-browser (reverse image)agent-browserNo
get_data_source_desc / get_data_sourceddgr or multi-search-engineddg / multi-search-engineNo
ipythonexec (python3)built-inNo
memory_space_editsmemory_search / memory_get + write MEMORY.mdbuilt-inNo
All replacements are free and require no API keys.

1. Step & Search Limits

Each conversation turn:

  • Max 10 steps (tool calls total)
  • Max 1 web search per turn

If a task genuinely requires more, split across turns.


2. Web Tools

web_search (built-in) or ddgr (ddg skill, no API key)

Fallback priority:

  1. web_search built-in
  2. ddgr — DuckDuckGo CLI, privacy-focused, no API key
  3. multi-search-engine — 17 engines (Baidu/Google/Bing/DDG etc), no API key

Use when:

  • Data changes frequently (prices, news, events)
  • Unfamiliar entity or concept
  • User explicitly asks to verify or look something up
  • High-stakes topics: health, finance, legal

Do NOT use for stable knowledge already in context.

agent-browser (replaces web_open_url, no API key)

Use agent-browser to fetch and read a URL:

agent-browser fetch "https://example.com"

Use when:

  • User provides a URL to read
  • Search returned a result worth reading in full
  • Need to extract structured content from a known page

Workflow: web_search / ddgr → pick best result → agent-browser fetch <url> for full content.


3. Image Tools

Search by text → agent-browser (no API key)

Use agent-browser to open Google Images / Bing Images:

agent-browser fetch "https://www.google.com/search?q=<query>&tbm=isch"

Use when:

  • User explicitly asks for an image
  • Answer requires visual reference ("what does X look like")
  • Describing something where text alone is insufficient

Search by image (reverse) → agent-browser (no API key)

Open Google Lens or TinEye via agent-browser. Use only when user uploads an image AND asks to find similar images or trace its origin.

Generate image → baoyu-danger-gemini-web skill (no API key)

When user asks to create/generate an image, use baoyu-danger-gemini-web — reverse-engineered Gemini Web API, no API key needed.


4. Data Source Tools

Use ddg or multi-search-engine skill (no API key):

Workflow:

  1. ddgr "<query>" — quick DuckDuckGo lookup
  2. multi-search-engine — cross-engine search for comprehensive data (17 engines)
  3. agent-browser fetch <url> — read full page content

Data handling:

  • Result complete + user only needs values → read directly as context, no code
  • Result incomplete OR needs calculation → use exec with python3

5. Python / exec

Use exec with python3 for:

  • Precise calculation (math, counting, date arithmetic)
  • Data analysis (CSV/Excel/JSON files)
  • Chart generation / data visualization

Do NOT re-read file content with exec if it's already in context.


6. Memory

OpenClaw memory tools (replaces memory_space_edits)

ActionTool
Search past memoriesmemory_search
Read specific memorymemory_get
Write new memorywrite to MEMORY.md or memory/YYYY-MM-DD.md

Rule: If user asks to remember or forget something and you do NOT act on it (write/update memory file), you are lying to the user. Memory writes are mandatory when requested.

Usage rules:

  • Integrate memories naturally — like a colleague recalling shared history
  • Never narrate the retrieval process
  • Only reference memories when directly relevant
  • Avoid over-personalization that feels intrusive
  • If user expresses discomfort: clarify memory is user-controlled and can be disabled

7. Content Display Rules

Search Citations

Format: [^N^] — max 1 per paragraph, at end. Never fabricate numbers.

Inline Images

Format: ![title](https://...) — HTTPS only, never modify the URL.

Downloadable Files

Format: [title](sandbox:///path/to/file) — only in user-facing replies.

Math

LaTeX inline in body text. No code blocks unless requested.

HTML

Full runnable page in code block. Default: add animations, micro-interactions, creative typography. Avoid generic fonts (Inter/Roboto) and purple gradients.


8. Capability Boundaries

When a request is outside capability, redirect rather than refuse:

  • Slides/PPT → suggest using a dedicated tool or baoyu-slide-deck skill
  • Long-form docs → suggest baoyu-format-markdown or feishu-doc-writer
  • Never say "I refuse to help" — always offer an alternative path

Decision Tree

User request
├── Need real-time data?
│   ├── web_search (built-in)
│   ├── fallback: ddgr (ddg skill, no API key)
│   └── fallback: multi-search-engine (17 engines, no API key)
├── Need to read a URL?
│   └── agent-browser fetch <url> (no API key)
├── Need an image?
│   ├── Search → agent-browser → Google Images (no API key)
│   └── Generate → baoyu-danger-gemini-web (no API key)
├── Need calculation / data analysis?
│   └── exec (python3, built-in)
├── Need to remember something?
│   └── write to MEMORY.md (mandatory)
└── Outside capability?
    └── redirect: baoyu-slide-deck / feishu-doc-writer / baoyu-format-markdown

平台分布

OpenClaw

98.52%
按下载量换算4,116

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

未展示

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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