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scarnyc / product-research-agent
Product Research Agent that automates the tedious parts of online shopping research using LangChain's DeepAgents framework.
Languages
- python77.4%
- markdown19.4%
- json3.2%
Explore scarnyc/product-research-agent
Code health
Full report- Code health88
- Dead code100
- Hotspot density100
- Bus factor42
How scarnyc/product-research-agent works
Product Research Agent that automates the tedious parts of online shopping research using LangChain's DeepAgents framework. This page is an auto-generated, always-fresh map of the scarnyc/product-research-agent repository, written primarily in Jupyter Notebook. Repowise indexes the source, parses every symbol, computes a dependency graph, scores per-file code health from complexity, duplication, test coverage and churn, mines git history for hotspots and ownership, and lifts the resulting architectural decisions into a wiki you can read or query through MCP.
The codebase has 31 source files, 409 symbols, and 3 languages. Git churn analysis flags 0 high-frequency files as hotspots — places where bugs, rewrites, and code review tend to concentrate. The dependency graph clusters into 12 tightly-coupled module communities.
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