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external-ki-integration-backup外部 ki 集成备份

Agent Skill

external-ki-integration-backup 用于处理浏览器自动化、网页检查和页面信息提取,适合在 OpenClaw 中需要让 Agent 打开页面、读取网页或验证前端流程时使用。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。

总安装

19,388

周安装

792

GitHub Stars

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下载量

6,209
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:external-ki-integration-backup(外部 ki 集成备份)
来源仓库:https://github.com/konscious0beast/external-ki-integration-backup
安装命令:
openclaw skills install external-ki-integration-backup
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 external-ki-integration-backup

简介

通过浏览器自动化 (Chrome Relay) 和 API 访问外部 AI 服务(ChatGPT、Claude、Hugging Face 等)以协助完成任务的技能。

SKILL.md

name
External KI Integration
description
Skill for accessing external AI services (ChatGPT, Claude, Hugging Face, etc.) via browser automation (Chrome Relay) and APIs to assist with tasks.

External KI Integration

Use external AI services via browser automation (ChatGPT, Claude, web‑based LLMs) and APIs (Hugging Face Inference, OpenAI‑compatible endpoints) to augment your capabilities.

When to use this skill

  • You need to consult an external AI model (ChatGPT, Claude, Gemini, etc.) for reasoning, analysis, or generation tasks.
  • The user has granted access to their chat interfaces (e.g., via Chrome Relay attached tab).
  • You want to use Hugging Face Inference API (if token provided) for model inference.
  • You need to interact with a free AI demo or Space via browser automation.
  • The task benefits from a second opinion or specialized model (coding, creative writing, summarization).

Requirements

  1. Browser automation – the browser tool with profile="chrome" (user must have attached a tab to OpenClaw Browser Relay).
  2. External AI accounts – user must be logged into the target service (ChatGPT, Claude, etc.) in the attached Chrome tab.
  3. Hugging Face token (optional) – for Inference API access, stored in ~/.openclaw/openclaw.json or provided as environment variable.
  4. Other API keys (optional) – e.g., OpenAI, Anthropic, if user provides them.

Setup

Chrome Relay Attachment

The user must click the OpenClaw Browser Relay toolbar icon on the desired tab (badge ON). Verify attachment:

openclaw browser status

Or via browser tool: browser(action=status, profile="chrome").

Hugging Face Token

If token already stored in config, it will be used automatically. Otherwise, ask user to provide it.

Environment Variables (optional)

For API‑based access, you may set:

export OPENAI_API_KEY="sk-..."
export ANTHROPIC_API_KEY="sk-ant-..."
export HF_TOKEN="hf_..."

Browser Automation for Web UIs

General Pattern

  1. Navigate to the service URL (e.g., https://chat.openai.com, https://claude.ai, https://gemini.google.com).
  2. Wait for page load, snapshot with refs="aria" to locate UI elements.
  3. Find input area (role="textbox", role="textbox" with name "Message", etc.).
  4. Type your query using act with ref or selector.
  5. Click send/submit button (role="button", name="Send").
  6. Wait for response (poll for new text elements, detect loading indicator disappearance).
  7. Extract response from the output container (role="article", class "markdown", etc.).
  8. Return the extracted text.

Example: ChatGPT via Chrome Relay

// 1. Navigate
browser(action="open", profile="chrome", targetUrl="https://chat.openai.com");

// 2. Snapshot after load
const snap = browser(action="snapshot", profile="chrome", refs="aria", interactive=true);

// 3. Find textbox (adapt ref based on snapshot)
browser(action="act", profile="chrome", request={ kind: "type", ref: "textbox:Message", text: "Your query here" });

// 4. Click send button
browser(action="act", profile="chrome", request={ kind: "click", ref: "button:Send" });

// 5. Wait for response (poll until new text appears)
// 6. Extract response

Adaptation Notes

  • UI changes frequently: Use refs="aria" for stable references (aria‑role, aria‑name). Fall back to selector with CSS classes if needed.
  • Rate limiting: Be gentle; wait 2–5 seconds between interactions.
  • Session persistence: The attached tab retains login state; you can continue conversation in same chat.

API Integration

Hugging Face Inference API

See the dedicated Hugging Face skill for detailed usage.

OpenAI‑compatible endpoints

If user provides an API key, you can call models via curl or exec:

curl -s -X POST https://api.openai.com/v1/chat/completions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

Anthropic Claude

curl -s -X POST https://api.anthropic.com/v1/messages \
  -H "x-api-key: $ANTHROPIC_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-3-opus-20240229",
    "max_tokens": 1024,
    "messages": [{"role": "user", "content": "Hello"}]
  }'

Cost & Safety

Browser Automation (free)

  • No direct cost, but uses user's existing subscription (if any).
  • Respect rate limits; do not spam requests.
  • Do not expose user credentials; rely on attached logged‑in session.

API Usage (paid)

  • Hugging Face Inference: Track estimated costs via system/logs/hf-costs.log. Stay within monthly budget (e.g., 33€). Notify user at 50% threshold.
  • OpenAI/Anthropic: If user provides API key, assume they accept associated costs. Still estimate token usage and log if possible.
  • General rule: Prefer browser automation for free services; use paid APIs only when explicitly authorized and task justifies cost.

Safety

  • No sensitive data: Avoid sending personal, financial, or confidential information to external services unless user explicitly approves.
  • Compliance: Follow external service terms of service.
  • Fallback: If external service fails, continue with internal reasoning; do not block task completion.

Integration with OpenClaw Skills

This skill complements:

  • Hugging Face skill – for dedicated Hugging Face API/Spaces.
  • Browser automation patterns – for generic web interaction.
  • Multi‑model orchestration – for delegating sub‑tasks to external models.

Add this skill to skills/index.md:

| External KI Integration | skills/external‑ki‑integration/SKILL.md |

Example Workflow

  1. Task: Need to generate a complex code snippet.
  2. Check: User has ChatGPT tab attached via Chrome Relay.
  3. Open ChatGPT, snapshot, locate input.
  4. Type: "Write a Python function that validates email addresses with regex and DNS MX check."
  5. Click Send.
  6. Wait for response, extract code.
  7. Return code to user, optionally refine via follow‑up.
  8. Log the interaction in memory (pattern learned).

Troubleshooting

  • Tab not attached: Ask user to click Browser Relay icon on the target tab.
  • UI changes: Update refs/selectors based on snapshot.
  • Rate limits: Wait longer between requests.
  • API errors: Check token permissions, budget, network.

References

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

93.96%
按下载量换算5,834

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

未展示

权限和风险

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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