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External Ki Integration Backup

作者 konscious0beast · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
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当前安装
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在 OpenClaw 中安装
/install external-ki-integration-backup
功能描述
Skill for accessing external AI services (ChatGPT, Claude, Hugging Face, etc.) via browser automation (Chrome Relay) and APIs to assist with tasks.
使用说明 (SKILL.md)

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

安全使用建议
Before installing or invoking this skill: (1) Verify the publisher/source — the registry metadata omits config/env references that appear in the runtime instructions. (2) Only attach Chrome tabs that you explicitly permit the agent to read; do not attach tabs containing private chats, passwords, or sensitive data. (3) Be cautious supplying API keys; prefer temporary or scoped keys and revoke them after use. (4) Inspect your ~/.openclaw/openclaw.json and any logs the agent might read/write; if you don't want the skill to read that file, do not grant it access and ask the publisher to remove that behavior. (5) Ask the publisher to update registry metadata to declare the optional env vars and config paths the skill uses; lack of declared requirements is a red flag. If you cannot confirm these points, treat the skill as risky and avoid providing credentials or attaching sensitive browser sessions.
功能分析
Type: OpenClaw Skill Name: external-ki-integration-backup Version: 1.0.0 The skill is classified as suspicious due to the broad capabilities it grants the AI agent, which, while necessary for its stated purpose, introduce significant vulnerabilities. Specifically, the `SKILL.md` instructs the agent to make arbitrary external network requests using `curl` (e.g., to `api.openai.com`, `api.anthropic.com`), access environment variables for API keys, and perform extensive browser automation via the `browser` tool. While the examples provided are for legitimate AI services, these capabilities could be exploited via prompt injection to exfiltrate sensitive data, interact with arbitrary web pages, or make unauthorized network calls to malicious endpoints, despite the skill's own safety instructions.
能力评估
Purpose & Capability
The skill claims to mediate external AI services via browser automation and APIs, and the SKILL.md contains concrete browser-relay and API call patterns that match that purpose. However, the manifest/registry metadata lists no required env vars or config paths while the SKILL.md explicitly references a local config (~/.openclaw/openclaw.json) and several optional API keys (OPENAI_API_KEY, ANTHROPIC_API_KEY, HF_TOKEN). The omission in metadata is an inconsistency the publisher should explain.
Instruction Scope
Instructions direct the agent to navigate user-attached Chrome tabs, interact with logged-in web UIs, extract chat responses, and read/write to local paths (e.g., ~/.openclaw/openclaw.json, system/logs/hf-costs.log) and update skills/index.md. Accessing browser sessions and local config/log files can expose sensitive data; while this is within the skill's stated function, the instructions also reference files and edits outside the immediate task without those paths being declared in metadata.
Install Mechanism
This is instruction-only (no install spec, no code files). That reduces supply-chain risk because nothing is downloaded or written at install time by the skill itself.
Credentials
The SKILL.md expects optional API keys (OPENAI_API_KEY, ANTHROPIC_API_KEY, HF_TOKEN) and may read a token from ~/.openclaw/openclaw.json, yet the registry metadata declares no required env vars or config paths. Optional credentials are reasonable for API calls, but the discrepancy and the ability to read an on-disk token (not declared) are proportionality concerns — the skill can access both web-session data and local stored tokens, increasing sensitive access surface.
Persistence & Privilege
The skill does not request always: true and has no install step, so it does not demand permanent elevated presence. It does suggest adding itself to skills/index.md (a local documentation/config file) which would modify agent state; editing its own index entry is plausible but should be explicit and limited to its own directory.
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 external-ki-integration-backup
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /external-ki-integration-backup 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
v1.0.0
External KI Integration v1.0.0 – Initial Release - Introduces a skill enabling access to external AI services (ChatGPT, Claude, Hugging Face, etc.) via both browser automation (through Chrome Relay) and APIs. - Supports reasoning, generation, coding, and summarization tasks by leveraging external models when authorized by the user. - Details setup, usage patterns, API integration (Hugging Face, OpenAI, Anthropic), and examples for both browser automation and API calls. - Clarifies safety, permissions, and cost considerations, emphasizing user control and best practices. - Offers troubleshooting tips and references for better integration with other skills.
元数据
Slug external-ki-integration-backup
版本 1.0.0
许可证
累计安装 2
当前安装数 2
历史版本数 1
常见问题

External Ki Integration Backup 是什么?

Skill for accessing external AI services (ChatGPT, Claude, Hugging Face, etc.) via browser automation (Chrome Relay) and APIs to assist with tasks. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 618 次。

如何安装 External Ki Integration Backup?

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

External Ki Integration Backup 是免费的吗?

是的,External Ki Integration Backup 完全免费(开源免费),可自由下载、安装和使用。

External Ki Integration Backup 支持哪些平台?

External Ki Integration Backup 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 External Ki Integration Backup?

由 konscious0beast(@konscious0beast)开发并维护,当前版本 v1.0.0。

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