Use RagaAI Catalyst to instrument agent runs, collect traces, manage evaluation datasets, inspect execution graphs, and review regressions before deployment.
Scanned 9/2/2026
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---
name: "Evaluate and trace agent workflows with RagaAI Catalyst"
slug: "evaluate-and-trace-agent-workflows-with-ragaai-catalyst"
description: "Use RagaAI Catalyst to instrument agent runs, collect traces, manage evaluation datasets, inspect execution graphs, and review regressions before deployment."
github_stars: 16167
verification: "security_reviewed"
source: "https://github.com/raga-ai-hub/RagaAI-Catalyst"
author: "raga-ai-hub"
publisher_type: "open_source"
category: "Monitoring & Alerts"
framework: "Multi-Framework"
tool_ecosystem:
github_repo: "raga-ai-hub/RagaAI-Catalyst"
github_stars: 16167
---
# Evaluate and trace agent workflows with RagaAI Catalyst
Use RagaAI Catalyst to instrument agent runs, collect traces, manage evaluation datasets, inspect execution graphs, and review regressions before deployment.
## Prerequisites
Python environment, ragaai-catalyst SDK, Catalyst project credentials, instrumented LLM or agent workflow, and evaluation datasets or trace samples.
## Installation
Use the upstream install or setup path that matches your environment:
- To install RagaAI Catalyst, you can use pip:
- pip install ragaai-catalyst
Requirements and caveats from upstream:
- python
Basic usage or getting-started notes:
- [Usage](#usage)
- Before using RagaAI Catalyst, you need to set up your credentials. You can do this by setting environment variables or passing them directly to the RagaAICatalyst class:
- from ragaai_catalyst import RagaAICatalyst
- Source: https://github.com/raga-ai-hub/RagaAI-Catalyst
- Extracted from upstream docs: https://raw.githubusercontent.com/raga-ai-hub/RagaAI-Catalyst/HEAD/README.md
## Documentation
- https://catalyst.raga.ai/
## Source
- [Agent Skill Exchange](https://agentskillexchange.com/skills/evaluate-and-trace-agent-workflows-with-ragaai-catalyst/)
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