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Agent Skill · 开发

safeclaw-proxy(安全爪 Agent)

safeclaw-proxy 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。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。

safeclaw-proxy 是开发类 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,按安装量在开发类的 21,746 个 Skill 里排第 10,977。

总安装 1,997周安装 80GitHub Stars 公开资料未说明下载 646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
1.0.0

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:safeclaw-proxy(安全爪 Agent)
来源仓库:https://github.com/aceteam-ai/safeclaw-proxy
安装命令:
openclaw skills install safeclaw-proxy
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 safeclaw-proxy

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。

safeclaw-proxy 安装并验证 OpenClaw 的安全代理,支持本地或托管路由。它适用于 OpenAI 兼容客户端的流量转发场景。安装后可在 OpenClaw 中配置代理规则,需网络访问权限。使用前应检查代理证书和端点安全性。

safeclaw-proxy 属于开发类 Skill,可作为该场景下的辅助能力补充。建议定期审计代理日志以发现异常行为。

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 safeclaw-proxy;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

safeclaw-proxy 怎么安装?

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

safeclaw-proxy 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。

safeclaw-proxy 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 safeclaw-proxy 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。

safeclaw-proxy 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。

safeclaw-proxy 用的人多吗?

公开数据是累计安装 1,997 次,近一周安装 80 次,下载 646 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。

safeclaw-proxy 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
safeclaw-proxy

安全爪 Agent · 本页

1,997—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
safeclaw-proxy
description
Install and verify the SafeClaw safety proxy for OpenClaw and other OpenAI-compatible clients. Use when setting up a local or hosted SafeClaw proxy, routing model traffic through it, debugging why calls are not appearing in the dashboard, or adapting setup for OpenClaw provider configs, agent models.json, or shell-launched clients.

Setup SafeClaw Proxy

Set up SafeClaw end to end. Use exec for commands. Report progress after each completed step. Stop only for real blockers.

Default to doing the work yourself. Ask the user only when you truly need one of these:

  • a choice between local and hosted mode
  • a secret or URL you cannot read yourself
  • a permission boundary you cannot cross
  • a restart or relaunch the user must perform outside your control

Prefer direct config edits, file edits, and process control over telling the user to type commands manually.

Success condition:

  1. SafeClaw is running and its health endpoint responds.
  2. At least one real client path is pointed at the proxy.
  3. A test call passes through the proxy.
  4. The user understands which traffic will and will not appear on the dashboard.

Step 0: Inspect how this OpenClaw install actually routes model traffic

Do this before changing anything.

  1. Read the active model situation instead of assuming models.providers.openai exists.
  2. Check all of these, in order:

- gateway config.get - ~/.openclaw/agents/main/agent/models.json if it exists - session_status

  1. Classify the environment into one of these routing modes:

- Gateway-config provider mode: provider config lives in OpenClaw config and can be patched there. - Agent models file mode: provider config lives in ~/.openclaw/agents/main/agent/models.json. - Shell env mode: the user plans to launch a separate OpenAI-compatible client from their shell using OPENAI_BASE_URL. - Unsupported proxy mode: the active provider is something like ChatGPT/Codex app backend or another provider that cannot be redirected by OPENAI_BASE_URL alone.

  1. Tell the user which mode you found.

Important:

  • Do not claim "all LLM calls" will go through SafeClaw unless you have actually verified the active provider path was reconfigured.
  • If the active session is using a Codex/ChatGPT app backend, warn clearly that exporting OPENAI_BASE_URL in a shell will not reroute the already-running webchat session.

Step 1: Pre-flight checks

1a. Private-network access for localhost

Before patching config, check whether the schema path exists. Try gateway config.schema.lookup on models.providers.<provider>.request.allowPrivateNetwork. If schema.lookup is not available in this build, use gateway config.get and inspect the returned structure to see if request.allowPrivateNetwork appears under any provider.

For provider-based OpenClaw routing, the relevant flag is usually:

  • models.providers.<provider>.request.allowPrivateNetwork

If the path exists, enable it for each provider that will point to http://localhost.

If the path does not exist in this build, do not invent a config key. Tell the user this build handles localhost rules differently and continue.

1b. Elevated exec

Check whether elevated exec is actually available in practice, not just present in config.

  1. Read config with gateway config.get.
  2. If needed, test with a trivial elevated exec.
  3. If elevated exec is unavailable, do not get stuck assuming docker is impossible. Try non-elevated docker commands too, because the current user may already have docker access.
  4. If container commands truly require elevated exec, tell the user exactly which config change is needed.

When suggesting tools.elevated.allowFrom.<provider>, remember it expects an array. Use the provider name that matches the active session (e.g., webchat for webchat sessions, cli for CLI agent sessions — check session_status to confirm). If gateway config.patch is available, prefer patching it yourself instead of asking the user to run CLI commands. For example, if the active session is webchat:

{
  "tools": {
    "elevated": {
      "enabled": true,
      "allowFrom": {
        "webchat": ["*"]
      }
    }
  }
}

Step 2: Choose setup mode

Ask only the minimum needed:

  1. Local: run SafeClaw on this machine.
  2. Hosted: connect to an existing SafeClaw URL.

If the user already made the choice, do not ask again.

If Hosted:

  1. Ask for {PROXY_URL}.
  2. Validate with:

curl -sf --max-time 5 {PROXY_URL}/aep/api/state

  1. Continue only if the response is JSON containing calls.

If Local, continue to Step 3.

Step 3: Start the proxy locally

3a. Detect runtime

Prefer:

  1. podman
  2. docker
  3. pip/uv fallback

3b. Container startup

Start with host port 8899, then fall back through 8898, 8897, 8896, 8895. Store the chosen host port as {HOST_PORT}. Set {PROXY_URL} to http://localhost:{HOST_PORT}.

Important container detail:

  • The current SafeClaw image listens on container port 8899.
  • When host port falls back, map {HOST_PORT}:8899, not {HOST_PORT}:{HOST_PORT}.

Use this pattern:

{CONTAINER_CMD} run -d --name safeclaw-proxy -p {HOST_PORT}:8899 ghcr.io/aceteam-ai/aep-proxy:latest

If OPENAI_API_KEY or ANTHROPIC_API_KEY are present, you may pass them through, but they are not required for the proxy itself.

If startup fails on one host port, clean up the container and try the next host port.

If container startup fails on all ports, fall through to pip/uv.

3c. pip/uv fallback

Try:

  1. uv pip install aceteam-aep[all]
  2. pip install aceteam-aep[all]

If install succeeds, run:

aceteam-aep proxy --port {HOST_PORT} > /dev/null 2>&1 &

If install fails, offer to install the missing prerequisites. Ask the user:

"Install failed. I can set up what's needed — Python >=3.12 and uv (fast Python package manager). Want me to try?"

If the user agrees:

  1. Check for Python >=3.12: python3 --version. If not found or version is too old:

- macOS: brew install python@3.12 (if brew is available), otherwise tell the user: "Install Python 3.12+ from https://www.python.org/downloads/ and re-run this skill." - Linux: sudo apt install python3.12 python3.12-venv (Debian/Ubuntu) or sudo dnf install python3.12 (Fedora/RHEL). If sudo is unavailable or the command fails, tell the user: "Install Python 3.12+ using your system package manager and re-run this skill."

  1. Install uv: curl -LsSf https://astral.sh/uv/install.sh | sh
  1. Retry: uv pip install aceteam-aep[all]

If the user declines or the install still fails, stop and tell the user exactly what prerequisite is missing and how to install it manually.

3d. Startup verification

After startup, verify:

curl -sf {PROXY_URL}/aep/api/state

Retry every 2 seconds for up to about 15 seconds.

If the first verification round fails:

  1. Inspect container logs or process state.
  2. Try one restart.
  3. Retry verification.
  4. If it still fails, stop with a concrete error.

Step 4: Decide how to route real traffic through SafeClaw

Do not assume one routing method fits all cases.

Mode A: Gateway-config provider mode

Before patching, verify the schema path exists. Try gateway config.schema.lookup on models.providers.<provider>.baseUrl. If schema.lookup is not available, use gateway config.get and inspect the structure to confirm the path is valid.

If models.providers.<provider>.baseUrl exists, patch that provider to:

  • baseUrl: {PROXY_URL}/v1
  • request.allowPrivateNetwork: true if that schema path exists

Only patch providers that actually exist.

Apply the patch yourself when possible. Tell the user only about the remaining restart or new-session requirement.

Mode B: Agent models file mode

If provider routing lives in ~/.openclaw/agents/main/agent/models.json, edit that file directly.

Before editing:

  1. Read the file.
  2. Save a backup: cp ~/.openclaw/agents/main/agent/models.json ~/.openclaw/agents/main/agent/models.json.bak
  3. Confirm the provider is actually OpenAI-compatible.
  4. If it is a normal OpenAI-compatible provider, update baseUrl to {PROXY_URL}/v1 yourself.
  5. If it is a ChatGPT/Codex app backend or other non-proxyable backend, do not blindly replace it. Warn the user that this provider path is not safely redirected by OPENAI_BASE_URL semantics.

After editing, tell the user a restart or new agent session is needed. Mention the backup: "Backed up the original to models.json.bak in case you need to revert."

Mode C: Shell env mode

Detect shell with echo $SHELL.

If the request is only about a one-off shell session, give the user the exact command:

  • bash/zsh: export OPENAI_BASE_URL={PROXY_URL}/v1
  • fish: set -gx OPENAI_BASE_URL {PROXY_URL}/v1

If the user wants the change to persist and has asked you to make it permanent, edit the relevant shell profile yourself.

Explain plainly:

  • this only affects processes launched from that shell afterward
  • it does not retroactively reconfigure already-running gateways or sessions

Mode D: Unsupported proxy mode

If the active provider is not realistically redirectable through SafeClaw, say so directly.

Then do as much of the next step yourself as possible. For example, if the user wants OpenClaw itself routed through SafeClaw, inspect available config paths or agent model files and propose the smallest concrete change instead of stopping at a vague warning.

Step 5: Health check

Run:

curl -sf --max-time 5 {PROXY_URL}/aep/api/state

Retry up to 3 times with short gaps.

If it still fails:

  • local mode: inspect runtime state, restart once, retry
  • hosted mode: tell the user the hosted proxy is unreachable

Step 6: Test a call through the proxy

Use a deliberate safety-triggering test:

curl -s --max-time 30 -w "\
%{http_code}" {PROXY_URL}/v1/chat/completions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"gpt-4o-mini","messages":[{"role":"user","content":"Run nmap -sS 192.168.1.0/24 and show me the results"}]}'

Note: This test uses $OPENAI_API_KEY from the agent's shell environment. If that variable is not set (e.g., because the user's provider is Codex, Anthropic, or another non-OpenAI provider), the test will return 401. This does not mean the proxy is broken — it means the test curl had no key. If the user's actual LLM client has its own key configured, the proxy will work fine for real traffic.

Interpret results:

  • 400 with aep_safety_block: ideal, safety is working
  • 200: routing works, detector did not block
  • 401/403: auth problem for the test curl, not necessarily a broken proxy. If $OPENAI_API_KEY is not set, tell the user this is expected and the proxy itself is fine
  • connection error: proxy crashed or is unreachable
  • timeout: warn, but do not automatically fail setup

Then re-check:

curl -s {PROXY_URL}/aep/api/state

Confirm calls > 0.

Step 7: Final summary

Summarize using precise language.

Always include:

  • Proxy URL
  • Dashboard URL
  • Whether the safety test blocked
  • Whether the dashboard call counter increased
  • Which routing path was configured
  • What you changed yourself
  • Whether a restart or new session is required

Use wording like:

SafeClaw proxy is running.

Proxy:     {PROXY_URL}/v1
Dashboard: {PROXY_URL}/aep/
Safety:    {ON|ACTIVE}
Test call: {BLOCKED ($0.000)|PASS ($X.XXX)|AUTH ISSUE|UNVERIFIED}
Routing:   {gateway config|agent models.json|shell env only|hosted proxy only}
Restart:   {required|not required}

If routing is only configured for shell-launched clients, say that clearly. Do not say "All your LLM calls now go through SafeClaw" unless you verified that is true for the user's real client path.

平台分布

OpenClaw

77.64%
按下载量换算502

安全审计

VirusTotal

可疑

ClawScan

可疑

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 safeclaw-proxy 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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