adith92/ai-avatar-system
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adith92/ai-avatar-systemadith92/ai-avatar-system
Repowise · Codebase intelligence
Repowise ranks every file by predicted defect risk. Of the 20 files it flags as riskiest, 18 (90%) actually needed a bug fix in the last 6 months — 2.6× better than picking files at random.
frontend
frontend
backend/main.pyinfrastructure/main.tfstart.shThis page is an auto-generated, always-fresh map of the adith92/ai-avatar-system repository, written primarily in python. 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 73 source files, 306 symbols, and 9 languages. Git churn analysis flags 13 high-frequency files as hotspots — places where bugs, rewrites, and code review tend to concentrate. The dependency graph clusters into 34 tightly-coupled module communities.
Use the panels above to open the interactive dashboards, or connect this repo to your editor via the Repowise MCP server for grounded answers inside Claude, Cursor, or VS Code.
Files, symbols, languages, packages, git intelligence
Dependency graph, layered architecture, symbol index, and third-party dependencies
Per-file health scores, hotspots, test coverage, dead code, and refactoring targets
Module-by-module documentation generated from source
Change-risk ranked history with AI-agent provenance and hotspots
Bus-factor, per-file maintainer maps, and human/agent collaboration
Architectural decisions extracted from commits and PRs
Ask grounded questions over the indexed code