/install autoglm-toolkit
AutoGLM Toolkit (智谱 AI 工具箱)
A comprehensive AI agent toolkit powered by Zhipu AI. Includes 6 capabilities:
- 🌐 Browser Automation — Autonomous browser agent for any web task
- 🔍 Deep Research — Multi-round search + deep reading for structured reports
- 🔎 Web Search — Quick web search with concise results
- 🎨 Image Generation — Text-to-image generation
- 🖼️ Image Search — Search for stock images by keywords
- 📄 Web Page Reader — Extract full-text content from web pages
Authentication
All API calls share the same authentication mechanism.
Token
Obtain via local AutoGLM service or manual configuration.
Signing Headers (required for all requests)
Every request must include these headers:
| Header | Value |
|---|---|
Authorization |
Bearer \x3Ctoken> |
X-Auth-Appid |
Your app ID |
X-Auth-TimeStamp |
Current Unix timestamp (seconds) |
X-Auth-Sign |
MD5(appid + "&" + timestamp + "&" + secret) |
import hashlib, time
def make_headers(token, app_id, secret):
ts = str(int(time.time()))
sign = hashlib.md5(f"{app_id}&{ts}&{secret}".encode()).hexdigest()
return {
'Authorization': f'Bearer {token}',
'X-Auth-Appid': app_id,
'X-Auth-TimeStamp': ts,
'X-Auth-Sign': sign,
'Content-Type': 'application/json'
}
1. Browser Automation Agent
Autonomous browser automation agent that can perform any web task.
Capabilities
- Open web pages, search engines (Baidu/Google/Bing)
- Browse social media (Weibo, Xiaohongshu, Zhihu, Douyin, Bilibili)
- Like, comment, repost, bookmark posts
- Login to websites, fill forms
- Take screenshots, scrape web content
- Online shopping comparisons
- Operate online documents (Feishu Docs, Tencent Docs)
Usage
# Delegate entire task to autonomous browser subagent
browser_subagent(task="\x3Ctask_description>", start_url="\x3Curl>")
Key Parameters
| Parameter | Required | Description |
|---|---|---|
task |
✅ | Task description (use user's exact words) |
start_url |
Optional | Starting URL for the task |
session_id |
Optional | Resume previous browser session |
auto_approve |
Optional | Auto-approve sensitive operations (default: false) |
Session Management
- Sessions persist in session pool with 12-hour TTL
- Same-site tasks reuse existing sessions
- Different-site tasks open new browser tabs
- Login/captcha always requires manual user interaction
Important Rules
- One task at a time (no concurrent browser tasks)
- Always show screenshots in results
- Default to 5 items when user doesn't specify quantity
- Separate browser operations from non-browser operations (like saving to Excel)
2. Deep Research (深度调研)
Conduct in-depth research on any topic with structured output.
Process
- Decompose: Break topic into 1-2 key search directions
- Search: 1-2 rounds of web search (controlled quantity)
- Deep Read: Open 1-3 important pages for full-text analysis
- Report: Generate structured research report
API Endpoints
# Web Search
POST https://autoglm-api.zhipuai.cn/agentdr/v1/assistant/skills/web-search
Body: {"queries": [{"query": "\x3Csearch_term>"}]}
# Returns: data.results[].webPages.value[] → name / url / snippet
# Open Link (Deep Read)
POST https://autoglm-api.zhipuai.cn/agentdr/v1/assistant/skills/open-link
Body: {"url": "\x3Cpage_url>"}
# Returns: data.text → full page content
Execution Constraints
web-searchmax 2 callsopen-linkmax 3 calls- Show intermediate results after each call
- Stop when sufficient information is gathered
Output Format
# [Topic] 深度调研报告
## 中间发现
## 概述
## 背景
## 现状分析
## 典型案例 / 代表性观点
## 发展趋势
## 总结
## 参考来源
3. Web Search (网络搜索)
Quick web search with structured results.
API
POST https://autoglm-api.zhipuai.cn/agentdr/v1/assistant/skills/web-search
Body: {"queries": [{"query": "\x3Csearch_term>"}]}
Response
{
"code": 0,
"data": {
"results": [{
"webPages": {
"value": [
{"name": "Page Title", "url": "URL", "snippet": "Summary"}
]
}
}]
}
}
Output Requirements
- Summarize search results based on snippets
- Append reference sources with links
4. Image Generation (AI 生图)
Generate images from text descriptions.
API
POST https://autoglm-api.zhipuai.cn/agentdr/v1/assistant/skills/generate-image
Body: {"text": "\x3Cimage_description>"}
Response
{
"code": 0,
"data": {"image_url": "https://..."}
}
Display result as: 
5. Image Search (搜图)
Search for images by keywords.
API
POST https://autoglm-api.zhipuai.cn/agentdr/v1/assistant/skills/search-image
Body: {"query": "\x3Csearch_keywords>"}
Response
{
"code": 0,
"data": {
"results": [{
"original_url": "image_url",
"caption": "description",
"source": "source",
"original_width": 1267,
"original_height": 845
}],
"count": 4
}
}
6. Web Page Reader (网页阅读)
Extract full-text content from a web page URL.
API
POST https://autoglm-api.zhipuai.cn/agentdr/v1/assistant/skills/open-link
Body: {"url": "\x3Cpage_url>"}
Response
{
"code": 0,
"data": {"text": "Full page content..."}
}
Output Requirements
- Extract
data.textas page content - Summarize or display based on user's goal
- Never fabricate content on API error
API Quick Reference
| Capability | Endpoint | Method |
|---|---|---|
| Web Search | /skills/web-search |
POST |
| Open Link | /skills/open-link |
POST |
| Generate Image | /skills/generate-image |
POST |
| Search Image | /skills/search-image |
POST |
Base URL: https://autoglm-api.zhipuai.cn/agentdr/v1/assistant
Notes
- All APIs use the same authentication signature mechanism
- Python 3 with standard library only (no extra dependencies)
- Particularly effective for Chinese internet content
- Browser agent requires Chromium-based browser with AutoClaw extension
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install autoglm-toolkit - 安装完成后,直接呼叫该 Skill 的名称或使用
/autoglm-toolkit触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
AutoGLM Toolkit 是什么?
AutoGLM AI agent toolkit powered by Zhipu AI. Includes browser automation, deep research, web search, image generation, image search, and web page content ex... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 511 次。
如何安装 AutoGLM Toolkit?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install autoglm-toolkit」即可一键安装,无需额外配置。
AutoGLM Toolkit 是免费的吗?
是的,AutoGLM Toolkit 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
AutoGLM Toolkit 支持哪些平台?
AutoGLM Toolkit 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 AutoGLM Toolkit?
由 ye4wzp(@ye4wzp)开发并维护,当前版本 v1.0.0。