Webfetch Skill

Web Fetch

Fetch and analyze web content by calling a specialized sub-agent that uses the webfetch script.

Use this as a clean single-page / few-page extraction tier:

• prefer native web_fetch for quick cooperative pages
• prefer this skill when you want cleaner markdown extraction, comparison across a few URLs, or extraction from article-like pages
• if the page is challenge-blocked or JS-only, recover that URL with camofox before escalating to any paid proxy path

Quick Start

To fetch and analyze web content, invoke the webfetch sub-agent:

Fetch a single URL:

Fetch and summarize: https://example.com

Fetch multiple URLs (max 5):

Fetch and compare: https://example.com and https://example2.com

Analyze specific content:

What are the main points on: https://example.com/article

Extract specific information:

Extract all email addresses from: https://example.com/contact

The sub-agent will:

1. Fetch the URL(s) using the webfetch script
2. Read the extracted markdown content
3. Provide AI analysis based on your prompt

Escalation contract

Keep the order narrow and cheap:

1. Try native web_fetch or this script workflow first.
2. If the target page is blocked by Cloudflare, challenge pages, or blank JS rendering, retry that URL with camofox.
3. If camofox also fails and the blocked URL is genuinely important, ask before using residential-proxy.

Do not automatically turn a small fetch task into a proxy-backed workflow.

Prerequisites

The webfetch script requires these Python packages:

pip install --break-system-packages trafilatura requests beautifulsoup4

trafilatura - Main content extraction and HTML→markdown conversion requests - HTTP client for fetching URLs beautifulsoup4 - Link and image extraction

How It Works

1. Skill triggers when you ask to fetch web content
2. Sub-agent invoked via Task tool
3. Script executes webfetch.py to fetch and extract content
4. Sub-agent analyzes the markdown output and provides intelligent response
5. Results returned with summaries, extractions, or answers

This approach avoids external APIs and local LLMs while providing intelligent analysis.

Sub-Agent Instructions (READ CAREFULLY)

CRITICAL: When you are the sub-agent for this skill, you MUST follow these instructions exactly:

TOOL RESTRICTIONS

• DO NOT USE ANY MCP TOOLS - Specifically: NO zai-web-reader, NO zai-vision tools, NO webfetch, NO webfetch_webReader
• DO NOT USE the webfetch function - Use the Python script instead
• ONLY USE THESE TOOLS: Bash tool (to run python3) and Read tool (to read markdown files)

EXACT STEPS TO FOLLOW

When asked to fetch web content, follow this EXACT process:

Step 1: Run the webfetch.py script

python3 ./skills/webfetch-skill/scripts/webfetch.py --url "URL_HERE" --output ./tmp/webfetch-skill/FILENAME.md

For multiple URLs (max 5), run separately for each URL or use --url multiple times:

python3 ./skills/webfetch-skill/scripts/webfetch.py --url "URL1" --url "URL2" --url "URL3" --output ./tmp/webfetch-skill/output.md

Step 2: Read the generated markdown file(s)

Use the Read tool to read: ./tmp/webfetch-skill/FILENAME.md

Step 3: Analyze the content

• Read and understand the markdown content
• Provide analysis, summary, or extraction based on the user's request
• Answer any questions about the fetched content

Step 4: Return results

• Provide your analysis to the main agent
• Do NOT include tool execution details unless asked

SCRIPT LOCATION

• Full path: ./skills/webfetch-skill/scripts/webfetch.py
• This script uses trafilatura for HTML→markdown conversion
• Cache is stored in: ./tmp/webfetch-skill/

ERROR HANDLING

• If the script fails, run it again with --no-cache flag
• If timeout occurs, add --timeout 30 or --timeout 60
• Report errors to the user with the exact error message

TEMPLATE PROMPT FOR MAIN AGENT

When invoking this sub-agent, use a prompt like:

Fetch and analyze content from these URLs using the webfetch script:
- https://example.com/page1
- https://example.com/page2

DO NOT use MCP tools. Use ONLY the python3 script at ./skills/webfetch-skill/scripts/webfetch.py.
Save output to ./tmp/webfetch-skill/ and read the files.

Using the Script Directly

You can also run the webfetch script directly without the sub-agent:

# Basic fetch
python3 scripts/webfetch.py --url "https://example.com"

# Multiple URLs
python3 scripts/webfetch.py --url "https://example.com" --url "https://example2.com"

# Disable cache
python3 scripts/webfetch.py --url "https://example.com" --no-cache

# Set timeout
python3 scripts/webfetch.py --url "https://example.com" --timeout 30

# Save to file
python3 scripts/webfetch.py --url "https://example.com" --output content.md

Script Parameters

Features

Main Content Extraction

Trafilatura automatically identifies the main article body and removes boilerplate (navigation, ads, footers).

Image Handling

Extracts up to 10 images with:

• Alt text (when available)
• Absolute URLs
• Markdown format: ![alt text](url)

Link Summary

Extracts up to 20 links with:

• Link text
• Absolute URLs
• Markdown format: [text](url)

Caching

15-minute file-based cache in ./tmp/webfetch-skill/:

• Cache key based on URL hash
• Automatic cache invalidation
• Improves performance for repeated requests

URL Handling

• HTTP→HTTPS: Automatically upgrades HTTP URLs
• Redirects: Follows redirects automatically
• User-Agent: Uses realistic browser headers

Output Format

When running the script directly, output is in markdown:

# https://example.com
_(from cache)_

## Content

Main content extracted from the page...

## Images
- **Image Alt**: https://example.com/image.jpg

## Links
- [Link Text](https://example.com/page)

When using the sub-agent, you get AI analysis instead of raw content.

Limitations

Cannot access:

• Authenticated/private URLs (Google Docs, Confluence, Jira, etc.)
• Sites requiring JavaScript rendering
• Sites with CAPTCHAs
• Rate-limited or blocked sites

Potential issues:

• Sites with anti-scraping measures
• Paywalled content
• Dynamic content loaded after page load
• Very large pages (may truncate)

Error Handling

The script handles common errors gracefully:

• 404 Not Found: Returns error message
• 500 Server Error: Returns error message
• Timeout: Returns timeout error
• Connection Error: Returns connection error
• Invalid URL: Returns invalid URL error

Errors are included in markdown output so sub-agent can inform you.

Best Practices

For optimal results:

1. Use sub-agent for intelligent analysis instead of reading raw content
2. Provide specific prompts rather than generic "fetch" requests
3. Enable cache (default) for performance on repeated requests
4. Use --no-cache when you need fresh content
5. Set longer timeout for slow-loading sites (e.g., --timeout 30)
6. Limit URLs when fetching multiple sites (max 5 enforced)

Example effective prompts:

• "Summarize the key takeaways from: https://example.com/article"
• "Extract all pricing information from: https://example.com/pricing"
• "What are the main sections in: https://example.com/docs"
• "Compare the content of these two pages: [url1] [url2]"

Resources

This skill includes:

scripts/webfetch.py - Main fetch script with content extraction