| name | reverse-engineering-api |
| description | Reverse engineer web APIs by capturing browser traffic (HAR files) and generating production-ready Python API clients. Use when the user wants to create an API client for a website, automate web interactions, or understand undocumented APIs. Activate on tasks mentioning "reverse engineer", "API client", "HAR file", "capture traffic", or "automate website". |
| compatibility | Requires Playwright MCP for browser control. HAR files saved to ~/.reverse-api/runs/har/{run_id} |
| metadata | [object Object] |
| allowed-tools | Bash(python:*) Bash(uv:*) Read Write Edit |
Reverse Engineering API Skill
This skill enables you to reverse engineer web APIs by:
- Controlling a browser with HAR recording enabled
- Analyzing captured network traffic
- Generating production-ready Python API clients
Prerequisites
- Playwright MCP: You must have access to Playwright MCP tools for browser control
- HAR Recording: The browser must be configured to record HAR files
- Python: For running analysis scripts and generated clients
Workflow Overview
[User Task] -> [Browser Capture] -> [HAR Analysis] -> [API Client Generation] -> [Testing & Refinement]
Phase 1: Browser Capture with HAR Recording
Starting the Browser
When starting a browser session for API capture:
- Launch browser with HAR recording enabled via Playwright MCP
- Generate a unique run ID:
{run_id} - Configure HAR output path:
~/.reverse-api/runs/har/{run_id}/recording.har
During Capture
Navigate autonomously to trigger the API calls needed:
- Login flows (capture authentication)
- Data fetching (capture GET endpoints)
- Form submissions (capture POST/PUT endpoints)
- Pagination (capture query parameter patterns)
On Browser Close
When the browser closes, note the HAR file location:
HAR file saved to: ~/.reverse-api/runs/har/{run_id}/recording.har
Phase 2: HAR Analysis
Reading the HAR File
HAR files are JSON with this structure:
{
"log": {
"entries": [
{
"request": {
"method": "GET|POST|PUT|DELETE",
"url": "https://api.example.com/endpoint",
"headers": [...],
"postData": {...}
},
"response": {
"status": 200,
"headers": [...],
"content": {...}
}
}
]
}
}
Filtering Relevant Entries
Filter out noise by excluding:
- Static assets:
.js,.css,.png,.jpg,.svg,.woff,.ico - Analytics:
google-analytics,segment,mixpanel,hotjar - Ads:
doubleclick,adsense,facebook.com/tr - CDN resources:
cloudflare,cdn.,static.
Focus on:
- API endpoints:
/api/,/v1/,/v2/,/graphql - XHR/Fetch requests with JSON responses
- Requests with authentication headers
Extracting Patterns
For each relevant endpoint, extract:
- URL Pattern: Base URL, path, query parameters
- Method: GET, POST, PUT, DELETE, PATCH
- Headers:
- Required headers (Authorization, Content-Type, custom headers)
- Optional headers (User-Agent, Accept)
- Request Body: JSON schema, form data structure
- Response Schema: JSON structure, status codes
- Authentication: See references/AUTH_PATTERNS.md
Phase 3: API Client Generation
Code Structure
Generate a Python module with:
{output_dir}/
api_client.py # Main API client class
README.md # Usage documentation
api_client.py Template
"""
Auto-generated API client for {domain}
Generated from HAR capture on {date}
"""
import requests
from typing import Optional, Dict, Any, List
import logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
class {ClassName}Client:
"""API client for {domain}."""
def __init__(
self,
base_url: str = "{base_url}",
session: Optional[requests.Session] = None,
):
self.base_url = base_url.rstrip("/")
self.session = session or requests.Session()
self._setup_session()
def _setup_session(self):
"""Configure session with default headers."""
self.session.headers.update({
"User-Agent": "Mozilla/5.0 (compatible)",
"Accept": "application/json",
# Add other required headers
})
def _request(
self,
method: str,
endpoint: str,
**kwargs,
) -> requests.Response:
"""Make an HTTP request with error handling."""
url = f"{self.base_url}{endpoint}"
try:
response = self.session.request(method, url, **kwargs)
response.raise_for_status()
return response
except requests.exceptions.RequestException as e:
logger.error(f"Request failed: {e}")
raise
# Generated endpoint methods go here
def get_example(self, param: str) -> Dict[str, Any]:
"""
Fetch example data.
Args:
param: Description of parameter
Returns:
JSON response data
"""
response = self._request("GET", f"/api/example/{param}")
return response.json()
# Example usage
if __name__ == "__main__":
client = {ClassName}Client()
# Example calls
Code Quality Requirements
All generated code must include:
- Type hints for all parameters and return values
- Docstrings for all public methods
- Error handling with try-except blocks
- Logging for debugging
- Session management for connection reuse
- Authentication handling based on detected patterns
Phase 4: Testing & Refinement
Testing the Generated Client
After generating the client:
- Run the example usage section
- Verify responses match expected structure
- Handle any errors encountered
Iteration Protocol
You have up to 5 attempts to fix issues:
Attempt 1: Initial implementation
- What was tried
- What failed (if anything)
- What was changed
Attempt 2: Refinement
...
Common Issues
| Issue | Solution |
|---|---|
| 403 Forbidden | Add missing headers, check authentication |
| Bot detection | Switch to Playwright with stealth mode |
| Rate limiting | Add delays, respect Retry-After headers |
| Session expiry | Implement token refresh logic |
| CORS errors | Use server-side requests (not applicable to Python) |
Domain Discovery (Optional)
Before capture, you may want to map the domain to understand its structure.
Using the Mapper Script
Run scripts/mapper.py to quickly discover:
- All pages on the domain or subdomains
- Subdomains
It is useful for generalizing your scripts on multitenants websites.
For example, for Ashby ATS or Workday it's useful to find other companies using this ATS when trying to generalize your script.
python scripts/mapper.py https://example.com
Using the Sitemap Parser
Run scripts/sitemap.py to extract URLs from sitemaps:
python scripts/sitemap.py https://example.com
Output Locations
- HAR files:
~/.reverse-api/runs/har/{run_id}/ - Generated scripts:
./{task_name}
Example Session
User: "Create an API client for the Apple Jobs website"
1. [Browser Capture]
Launch browser with HAR recording
Navigate to jobs.apple.com
Perform search, browse listings
Close browser
HAR saved to: ~/.reverse-api/runs/har/{run_id}/recording.har
Note: you can monitor browser requests with the Playwright MCP
2. [HAR Analysis]
Found endpoints:
- GET /api/role/search?query=...
- GET /api/role/{id}
Authentication: None required (public API)
3. [Generate Client]
Create : {task_name}/api_client.py
4. [Test]
Ran example usage - Success!
5. [Summary]
Generated Apple Jobs API client with:
- search_roles(query, location, page)
- get_role(role_id)
Files: ./{task_name}/