Which is more popular, git-lrc or Promptfoo?

Promptfoo has more GitHub stars (25,665 vs 1,468).

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

Promptfoo had more commits in the last 90 days (920 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

Promptfoo is growing faster: +1,110 GitHub stars in the last 30 days vs +175 for git-lrc.
Pick git-lrc for: free, Unlimited AI Code Reviews That Run on Commit. Pick Promptfoo for: open-source CLI and library for evaluating and red-teaming prompts, agents, RAG systems, and LLM apps.

From GitHub data refreshed daily.

Free, Unlimited AI Code Reviews That Run on Commit

Promptfooopen-source

Open-source CLI and library for evaluating and red-teaming prompts, agents, RAG systems, and LLM apps

+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

+Comprehensive testing suite covering both performance evaluation and security red teaming in a single tool
+Multi-provider support with easy comparison between OpenAI, Anthropic, Claude, Gemini, Llama and dozens of other models
+Strong CI/CD integration with automated pull request scanning and code review capabilities for production deployments

-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

-Requires API keys and credits for multiple LLM providers, which can become expensive for extensive testing
-Command-line focused interface may have a learning curve for teams preferring GUI-based tools
-Limited to evaluation and testing - does not provide actual LLM application development capabilities

•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

•Automated testing and evaluation of prompt performance across different models before production deployment
•Security vulnerability scanning and red teaming of LLM applications to identify potential risks and compliance issues
•Systematic comparison of model performance and cost-effectiveness to optimize AI application architecture

Which is more popular, git-lrc or Promptfoo?: Promptfoo has more GitHub stars (25,665 vs 1,468).
Which is more actively developed, git-lrc or Promptfoo?: Promptfoo had more commits in the last 90 days (920 vs 92).
Should I use git-lrc or Promptfoo?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.