haizelabs

Create flexible annotation workflows for AI applications. Contains common tools to explore raw ai agent logs/transcripts, extract out relevant evaluation data, and llm-as-a-judge creation.

Investigates agent behaviors and performance from any observability store — local logs, agent trajectory stores, and MCP servers from observability products. Covers how models reason, interact, handle pressure, mirror values, and coordinate. Guides tracing setup. Use when: (1) analyzing agent failures or slowness, (2) auditing reasoning quality, (3) comparing behavioral patterns across models, (4) understanding multi-agent dynamics, (5) setting up tracing, (6) debugging reports of model performance degradations. Triggers: "investigate traces", "analyze agent behavior", "debug the agent", "model behavior", "set up tracing".