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Kimi Agent Policy

作者 2233admin · GitHub ↗ · v1.1.0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install kimi-agent-policy
功能描述
Kimi (Moonshot AI) agent tool-use policy ported to OpenClaw. Covers step limits, web search, image search, data sources, ipython, memory, content display, an...
使用说明 (SKILL.md)

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 Tool OpenClaw Equivalent Skill API Key?
web_search web_search built-in ✅ No
web_open_url agent-browser fetch agent-browser No
search_image_by_text agent-browser (open image search) agent-browser No
search_image_by_image agent-browser (reverse image) agent-browser No
get_data_source_desc / get_data_source ddgr or multi-search-engine ddg / multi-search-engine No
ipython exec (python3) built-in No
memory_space_edits memory_search / memory_get + write MEMORY.md built-in No

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 \x3Curl> 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=\x3Cquery>&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 "\x3Cquery>" — quick DuckDuckGo lookup
  2. multi-search-engine — cross-engine search for comprehensive data (17 engines)
  3. agent-browser fetch \x3Curl> — 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)

Action Tool
Search past memories memory_search
Read specific memory memory_get
Write new memory write 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 \x3Curl> (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
安全使用建议
This is primarily a behavior policy (no code or installs), so the main risks are operational: it requires the agent to always write user 'memories' on request and points the agent to several external skills (including a 'reverse‑engineered' Gemini Web skill) without advising verification. Before installing, consider: (1) Where are MEMORY.md and memory/ files stored and who can read them? (2) Add an explicit confirmation step before storing any user-supplied secret or sensitive data. (3) Audit the referenced skills (baoyu-danger-gemini-web, agent-browser, ddg, multi-search-engine) to see what network access or credentials they require and whether you trust them. (4) If you are uncomfortable with automatic persistence, disable autonomous invocation for agents using this skill or require explicit user consent for any memory write. Finally, because there is no code to inspect, verify the provenance (source/repository) of this policy and the other skills it recommends before trusting them.
功能分析
Type: OpenClaw Skill Name: kimi-agent-policy Version: 1.1.0 The skill defines a policy for an AI agent, instructing it on how to use various tools. It is classified as suspicious due to its explicit instructions for the agent to use powerful capabilities like `exec` (python3) and direct file writing (`MEMORY.md`). While these capabilities are often necessary for agents, they pose significant security risks (e.g., RCE, arbitrary file writes) if the agent's execution environment or input sanitization is not robust. The `SKILL.md` also contains strong directives, such as making memory writes 'mandatory', which is a form of prompt injection to enforce specific agent behavior. There is no evidence of intentional malicious activity like data exfiltration, persistence, or obfuscation within this skill, but the instructed capabilities are high-risk.
能力评估
Purpose & Capability
The SKILL.md is an agent policy and does not request credentials or installs, which is appropriate. However it explicitly recommends using third‑party skills such as 'baoyu-danger-gemini-web' (a described "reverse‑engineered Gemini Web API") and multi‑engine search tools; recommending an unvetted reverse‑engineered tool is a design choice that increases operational risk even if it technically fits the policy purpose.
Instruction Scope
The instructions require the agent to write persistent memory files (MEMORY.md or memory/YYYY-MM-DD.md) whenever a user asks to remember/forget — the policy states memory writes are mandatory and that failing to act is "lying to the user." There are no explicit safeguards or confirmation steps described for sensitive data, which could cause unintended persistence of secrets or private data. The doc also instructs fetching arbitrary URLs via agent-browser and invoking web searches; those are expected for a policy but expand the surface for exfiltration if combined with memory writes.
Install Mechanism
Instruction-only skill with no install spec and no code files. This has minimal direct install risk because nothing is fetched or written by an installer.
Credentials
The skill declares no env vars or credentials required, which matches a policy document. However it references and maps to many other skills (agent-browser, ddg, multi-search-engine, baoyu-danger-gemini-web). Those skills may themselves require credentials or network access; the policy provides no guidance to verify or restrict those skills, which could lead to unexpected external data flows.
Persistence & Privilege
Although always:false and the skill is user-invocable, the policy enforces mandatory memory writes and prescribes storage paths (MEMORY.md, memory/YYYY-MM-DD.md, sandbox:/// for downloadable files). That grants the skill rules that cause persistent data storage. With agent autonomy enabled, this raises privacy risk because data could be saved without strong user confirmation or redaction rules.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install kimi-agent-policy
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /kimi-agent-policy 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.1.0
Kimi tool-use policy ported to OpenClaw. All tools mapped to free no-API-key alternatives (ddg, agent-browser, multi-search-engine, baoyu-danger-gemini-web).
元数据
Slug kimi-agent-policy
版本 1.1.0
许可证
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Kimi Agent Policy 是什么?

Kimi (Moonshot AI) agent tool-use policy ported to OpenClaw. Covers step limits, web search, image search, data sources, ipython, memory, content display, an... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 406 次。

如何安装 Kimi Agent Policy?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install kimi-agent-policy」即可一键安装,无需额外配置。

Kimi Agent Policy 是免费的吗?

是的,Kimi Agent Policy 完全免费(开源免费),可自由下载、安装和使用。

Kimi Agent Policy 支持哪些平台?

Kimi Agent Policy 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Kimi Agent Policy?

由 2233admin(@2233admin)开发并维护,当前版本 v1.1.0。

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