Which is more popular, Langfuse or Skills?

Skills has more GitHub stars (179,472 vs 35,329).

Which is more actively developed, Langfuse or Skills?

Langfuse had more commits in the last 90 days (2,013 vs 14).

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

Skills is growing faster: +25,889 GitHub stars in the last 30 days vs +1,807 for Langfuse.
Pick Langfuse for: open-source LLM engineering platform for observability, evaluation, prompt and dataset management. Pick Skills for: public repository for Agent Skills.

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Langfuseopen-source

Open-source LLM engineering platform for observability, evaluation, prompt and dataset management

Public repository for Agent Skills

+Open source with MIT license allowing full customization and transparency, plus active community support
+Comprehensive feature set combining observability, prompt management, evaluations, and datasets in one platform
+Extensive integrations with major LLM frameworks and tools including OpenTelemetry, LangChain, and OpenAI SDK

+Official Anthropic implementation provides reliable, well-tested skill patterns and best practices for Claude AI development
+Extensive collection covering diverse domains from creative tasks to enterprise workflows, offering immediate practical value
+Self-contained modular design allows easy customization and extension of existing skills for specific organizational needs

-Skills are Claude-specific and may not be directly portable to other AI agents or platforms
-Some skills are source-available only (not open source), limiting modification rights for certain components
-Repository serves primarily as demonstration material, requiring thorough testing before production deployment

•Production LLM application monitoring to track performance, costs, and identify issues in real-time
•Prompt engineering and management for teams collaborating on optimizing model prompts and tracking versions
•LLM evaluation and testing to measure model performance across different datasets and use cases

•Enterprise teams standardizing AI workflows with consistent document creation, branding, and communication processes
•Developers building Claude-powered applications needing reference implementations for complex multi-step tasks
•Organizations creating custom AI skills who need proven architectural patterns from Anthropic's production implementations

Which is more popular, Langfuse or Skills?: Skills has more GitHub stars (179,472 vs 35,329).
Which is more actively developed, Langfuse or Skills?: Langfuse had more commits in the last 90 days (2,013 vs 14).
Should I use Langfuse or Skills?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.