capture-analytics

To capture network traffic end-to-end, this skill uses mitmproxy for autonomous interception and Playwright for browser exploration. It automates collection and applies AI-assisted analysis to generate structured outputs like HAR files and NDJSON indexes.

Yes, Playwright drives browser exploration while mitmproxy captures traffic, and you can limit captures to selected hosts using scope control. This targeted approach prevents unrelated noise and focuses the analysis on specific domains.

Yes, mitmproxy is a required dependency to intercept and capture web traffic for analysis. You also need Python 3.8+ and Playwright MCP configured in your environment to orchestrate the autonomous workflow.

Analyzing network traffic generates HAR files, NDJSON indexes, and AI-friendly briefs for rapid triage. These multi-format outputs allow you to import data into other tools or quickly review the AI-assisted analysis summaries.

The best way to automate browser traffic capture for AI analysis is using an autonomous workflow that combines Playwright-driven exploration with mitmproxy interception. This approach reduces manual setup and produces structured, AI-friendly reports.

Yes, the network capture workflow includes secure cleanup options to remove sensitive data after analysis is complete. Scope control limits captures to selected hosts during operation, and cleanup ensures no residual traffic data remains.