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A multi-layered, agentic, context-aware, zero-cost code reviewer

Project description

Frankenreview v11.6.9

Version Python Cost Gemini Status

Lean, stateless, zero-cost code reviewer and research agent powered by Gemini via browser automation.

Architecture: Pull Model | Cost: $0.00 | Runtime: Playwright + Chrome

[!CAUTION] Data Privacy Notice: Google AI Studio may use submitted code for model training. Do NOT submit proprietary, confidential, or sensitive code.


Overview

Frankenreview packs a repository into structured XML context and submits it to Gemini via browser automation (no API key required).

Layer Module Function
Dumper engine/repo_dumper.py Repository to XML context
Browser engine/browser/client.py AI Studio automation
CLI cli.py Stateless command interface
Research agents/research.py Deep research agent

Installation

pip install frankenreview && playwright install chromium

Usage

frankenreview --start-chrome              # Start Chrome debugger
frankenreview -r                          # Review current directory
frankenreview -r --model gemini-3-pro     # Use specific model
frankenreview -r --json                   # JSON output for CI
frankenreview --research --prompt q.md    # Deep research

# Model Discovery
frankenreview --available-models           # Cached model list (instant)
frankenreview --fetch-models               # Live fetch from Google AI docs

# Session Management
frankenreview --open-chat                 # Open chat for manual use
frankenreview -r --continue               # Continue previous session
frankenreview --delete-chat               # Delete saved session

CLI Reference

Flag Description
-r, --review Run code review
--research Deep research mode
--start-chrome Launch Chrome debugger
--stop-chrome Stop Chrome instance
--path PATH Target project
--model ID Gemini model ID
--attach FILE Extra context files
--json JSON output
--continue Resume previous session
--open-chat Open chat without review
--delete-chat Delete saved session
--available-models Display cached model compatibility list
--fetch-models Actively fetch models from Google AI docs and update cache

Configuration

Edit config.yaml:

chat_url: "https://aistudio.google.com/prompts/new_chat?model=gemini-flash-latest"
delete_after_review: true
prune_dirs: [.git, node_modules, __pycache__]
model_failover: [gemini-3-flash-preview, gemini-2.5-pro, gemini-2.0-flash]

Documentation


License

MIT - See LICENSE

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