Which is more popular, git-lrc or goose?

goose has more GitHub stars (54,872 vs 1,468).

Which is more actively developed, git-lrc or goose?

goose had more commits in the last 90 days (804 vs 92).

Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.

Side-by-side comparison of two AI agent tools

goose is growing faster: +3,367 GitHub stars in the last 30 days vs +176 for git-lrc.
Pick git-lrc for: free, Unlimited AI Code Reviews That Run on Commit. Pick goose for: an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test.

From GitHub data refreshed daily.

Free, Unlimited AI Code Reviews That Run on Commit

gooseopen-source

an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM

+Completely free with unlimited AI code reviews, removing cost barriers for comprehensive code analysis
+Seamless Git integration that automatically reviews changes on commit without disrupting developer workflow
+Quick 60-second setup process that minimizes onboarding friction for immediate productivity gains

-Relatively modest GitHub star count (361) suggests smaller community and potentially less mature ecosystem
-Dependency on AI models may result in false positives or missed issues that human reviewers would catch

•Teams using AI coding assistants who need to validate automatically generated code for security vulnerabilities and logic errors
•Individual developers working on personal projects who want professional-level code review without subscription costs
•Organizations implementing security-first development practices that require automated scanning of all code changes before commit

Which is more popular, git-lrc or goose?: goose has more GitHub stars (54,872 vs 1,468).
Which is more actively developed, git-lrc or goose?: goose had more commits in the last 90 days (804 vs 92).
Should I use git-lrc or goose?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.