Manages human annotations and manual scoring workflows for Langfuse LLM traces directly from Claude.
The Langfuse Annotation Manager skill empowers developers to streamline the human-in-the-loop evaluation process by managing scores and annotations within the Langfuse observability platform. It allows for creating, updating, and exporting human feedback on LLM traces, identifying pending reviews, and managing annotation configurations. This tool is essential for teams looking to improve model performance through high-quality ground-truth data and systematic manual evaluation workflows without leaving their development environment.
Key Features
01Create and update human scores and comments on specific traces
02Export annotations in CSV format for offline analysis
03Integrate review workflows and patterns for consistent evaluations
04Filter and identify pending traces requiring manual review
05List and manage score configurations and categories
060 GitHub stars
Use Cases
01Exporting human-labeled datasets for fine-tuning or benchmarking AI models
02Performing manual quality assurance on LLM responses to improve model alignment
03Managing annotation backlogs by identifying traces that haven't been reviewed yet
