01 — AI · Infra
Dependency-aware AI code review that posts context-rich feedback directly on GitHub pull requests.
Stack
Tree-sitter · Gemini · Qdrant · Redis · Celery · AWS ECS · Docker
In one line
AST-scoped PR review
PRism is an event-driven developer tool that reviews GitHub pull requests with real codebase context instead of just the raw diff. When a PR event fires, it walks the repo's dependency graph to find every file and symbol impacted by the change, then assembles a tightly scoped prompt so the model reviews the change the way a senior engineer familiar with the codebase would.
Demo coming soon
AST parsing with Tree-sitter builds repo-wide dependency graphs, identifying impacted files and call sites per PR change.
Context-scoped prompting assembles diffs, impacted call sites, and internal engineering rules into tightly scoped Gemini prompts.
Scoped RAG via Qdrant enforces internal style guides, with per-commit-SHA caching of ASTs and symbol maps in Redis.
Deployed on AWS ECS with Celery and isolated Docker workers, webhook signature verification, and short-lived GitHub App tokens.
Precision/recall evaluation pipeline runs against known-bad PR test sets for continuous quality measurement.