RagaAI-Catalyst — security grade SAFE, quality 73/100

Security audit verdict: SAFE · quality 73/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by raga-ai-hub · Agent Tool · ★ 16.2k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is RagaAI-Catalyst safe to install? View the security audit →

About RagaAI-Catalyst

RagaAI Catalyst  RagaAI Catalyst is a comprehensive platform designed to enhance the management and optimization of LLM projects. It offers a wide range of features, including project management, dataset management, evaluation management, trace management, prompt management, synthetic data generation, and guardrail management. These functionalities enable you to efficiently evaluate, and safeguard your LLM applications. Table of Contents RagaAI Catalyst Installation Configuration Usage Project Management Dataset Management Evaluation Management Trace Management Agentic Tracing Prompt Management Synthetic Data Generation Guardrail Management Red-teaming Installation To install RagaAI Catalyst, you can use pip: Configuration Before using RagaAI Catalyst, you need to set up your credentials. You can do this by setting envir

agentic-aiagentic-ai-developmentagentneoagentsai-agent-monitoringai-application-debuggingai-evaluation-toolsai-performance-optimizationai-tool-interaction-monitoringllm-testing

Quick Facts

Stars16,162
Forks3,567
LanguagePython
CategoryAgent Tool
LicenseApache-2.0
Quality Score72.808264593832/100
Open Issues34
Last Updated2026-02-11
Created2024-08-26
Platformspython
Est. Tokens~3792k

Compatible Skills

These tools work well together with RagaAI-Catalyst for enhanced workflows:

  • autogen — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (53%)
  • solace-agent-mesh — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (51%)
  • nexent — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)
  • ag2 — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)
  • PPTAgent — semantic(0.15)+complementary+same_lang+similar_pop+shared_platform (50%)

RagaAI-Catalyst alternative? Top 6 similar tools

Looking for a RagaAI-Catalyst alternative? If you're comparing RagaAI-Catalyst with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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  • litellm by BerriAI · ⭐ 59.4k

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Frequently Asked Questions

What is RagaAI-Catalyst?

RagaAI-Catalyst is Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced anal. It is categorized as a Agent Tool with 16.2k GitHub stars.

What programming language is RagaAI-Catalyst written in?

RagaAI-Catalyst is primarily written in Python. It covers topics such as agentic-ai, agentic-ai-development, agentneo.

How do I install or use RagaAI-Catalyst?

You can find installation instructions and usage details in the RagaAI-Catalyst GitHub repository at github.com/raga-ai-hub/RagaAI-Catalyst. The project has 16.2k stars and 3567 forks, indicating an active community.

What license does RagaAI-Catalyst use?

RagaAI-Catalyst is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to RagaAI-Catalyst?

The top alternatives to RagaAI-Catalyst on Agent Skills Hub include composio, ruflo, valuecell. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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