Agent SDK and Runtime · Public

RagaAI-Catalyst

Agent SDK project for checking tool calls, state, handoffs, traces, evaluation, and permission boundaries.

Agent SDKTool callsHandoffsTracingEvaluation boundaries

Best fitDevelopers building observable, testable, multi-tool agent applications.

Check whether this project matches your task before installing it.

What it can doAgent runtime preflights, tool permissions, state/handoff boundaries, trace acceptance, and evaluation checks

Review the portable capability path.

Before continuingVerify in a sandbox

Do not treat a preview pack as a proven local install.

GitHub snapshot16k stars

3.6k forks · 28 contributors

Doramagic.ai Last verification date: 2026-06-23 Verification method: source evidence, semantic profile, public page gate, and static build acceptance.

Official first step Read manual preview Source repository

Publication status · 2026-06-23

What is RagaAI-Catalyst?

RagaAI-Catalyst is an Agent SDK or runtime for tool calls, state, handoffs, tracing, and evaluation boundaries.
Best fit: Developers building observable, testable, multi-tool agent applications.
Not for: Not for one prompt, simple API calls, or environments that cannot isolate tool permissions.
Capability added to an AI workflow: Agent runtime preflights, tool permissions, state/handoff boundaries, trace acceptance, and evaluation checks
First safe verification step: Verify one minimal agent loop with fake tools and temporary credentials first.
Verification state: source, Quick Start, and sandbox install checks are recorded as passed.
Top risk: May increase setup, validation, or first-run risk for the user.
Evidence base: https://github.com/raga-ai-hub/RagaAI-Catalyst, https://github.com/raga-ai-hub/RagaAI-Catalyst#readme, Human Manual, Pitfall Log

Quick decision

Use this section to decide whether the project is worth a deeper read.

Best forDevelopers building observable, testable, multi-tool agent applications.

Match the project to your task before installing it.

CapabilityAgent runtime preflights, tool permissions, state/handoff boundaries, trace acceptance, and evaluation checks

Agent SDK project for checking tool calls, state, handoffs, traces, evaluation, and permission boundaries.

Repositoryraga-ai-hub/RagaAI-Catalyst

16k stars · 3.6k forks

What it can do

Translate the upstream project into concrete capabilities the user can judge before installing.

Overview, Installation & Project Management

Related topics: Trace Management & Agentic Tracing, Dataset, Evaluation & Prompt Management

Sources: [README.md](https://github.com/raga-ai-hub/RagaAI-Catalyst/blob/main/README.md), [ragaai_catalyst/redteaming/utils/issue_description.py](https://github.com/raga-ai-hub/RagaAI-Catalyst/blob/main/ragaai_catalyst/redteaming/utils/issue_description.py)

Trace Management & Agentic Tracing

Related topics: Overview, Installation & Project Management, Dataset, Evaluation & Prompt Management

Source: https://github.com/raga-ai-hub/RagaAI-Catalyst / Human Manual

Dataset, Evaluation & Prompt Management

Related topics: Overview, Installation & Project Management, Guardrails, Red-Teaming & Synthetic Data Generation

Source: https://github.com/raga-ai-hub/RagaAI-Catalyst / Human Manual

Guardrails, Red-Teaming & Synthetic Data Generation

Related topics: Trace Management & Agentic Tracing, Dataset, Evaluation & Prompt Management

Source: https://github.com/raga-ai-hub/RagaAI-Catalyst / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

Sources: https://github.com/raga-ai-hub/RagaAI-Catalyst, Human Manual, Project Pack evidence, and downstream validation signals.

Community Discussion Evidence

Project-level external discussion stays visible on the detail page, not only inside the manual.

Stars16k stars

Forks3.6k forks

Contributors28 contributors

Licenseunknown

Community Discussion Evidence

12 source-linked items

Review these external discussions before using RagaAI-Catalyst with real data or production workflows. They are review inputs, not standalone proof that the project is production-ready.

01
Standardizing Agent Commerce: Merxex Integration Proposal
github / github_issue
02
Authorization receipts for agent traces — signed governance proof per tr
github / github_issue
03
Tamper-proof audit logs to complement observability traces
github / github_issue
04
🤖 Connect your agent to MEEET STATE — earn $MEEET on Solana
github / github_issue
05
Add Unit Tests
github / github_issue
06
Add Example Notebooks
github / github_issue
07
Integration: Agent-SRE Reliability Layer for AI Agent Monitoring
github / github_issue
08
Question / suggestion: using WFGY Problem Map as a 16-mode RAG failure t
github / github_issue
09
2.2.4
github / github_release
10
2.2.3
github / github_release
11
2.2.1
github / github_release
12
2.1.7.4
github / github_release

How to start

Only source-backed commands are shown here. Verify them in an isolated environment first.

Try the prompt first

Test the workflow without installing the upstream project.

preview

Read the Human Manual

Understand inputs, outputs, limits, and failure modes.

manual

Take context to your AI host

Use the compiled assets in your preferred AI environment.

context

Run sandbox verification

Confirm install commands and rollback before using a primary environment.

verify

pip install ragaai-catalyst

Official start command · https://github.com/raga-ai-hub/RagaAI-Catalyst#readme · verified: yes

Human Manual

The English page must expose the real manual, not a short placeholder.

8+ sections · Human Manual

RagaAI-Catalyst Manual

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 analytics with timeline and execution graph view

Open the full manual

https://github.com/raga-ai-hub/RagaAI-Catalyst Project Manual
Table of Contents
Overview, Installation & Project Management
Related Pages
1. What is RagaAI Catalyst
2. Installation
3. Authentication & Configuration
4. Project Management

Overview, Installation & Project Management

Related topics: Trace Management & Agentic Tracing, Dataset, Evaluation & Prompt Management

Sources: [README.md](https://github.com/raga-ai-hub/RagaAI-Catalyst/blob/main/README.md), [ragaai_catalyst/redteaming/utils/issue_description.py](https://github.com/raga-ai-hub/RagaAI-Catalyst/blob/main/ragaai_catalyst/redteaming/utils/issue_description.py)

Trace Management & Agentic Tracing

Related topics: Overview, Installation & Project Management, Dataset, Evaluation & Prompt Management

Source: https://github.com/raga-ai-hub/RagaAI-Catalyst / Human Manual

Dataset, Evaluation & Prompt Management

Related topics: Overview, Installation & Project Management, Guardrails, Red-Teaming & Synthetic Data Generation

Source: https://github.com/raga-ai-hub/RagaAI-Catalyst / Human Manual

Guardrails, Red-Teaming & Synthetic Data Generation

Related topics: Trace Management & Agentic Tracing, Dataset, Evaluation & Prompt Management

Source: https://github.com/raga-ai-hub/RagaAI-Catalyst / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

AI Context Pack and portable assets

After deciding to continue, take the project context into your own AI host.

Complete pack plus user-owned assets

These files are planning and verification assets for Claude Code, Codex, Gemini, Cursor, ChatGPT, and other AI hosts.

Download complete pack Read Human Manual

BundleComplete Project Pack AssetAI Context Pack AssetBoundary & Risk Card AssetHuman Manual AssetPitfall Log AssetPrompt Preview AssetQuick Start EvidenceREPO_INSPECTION.json

Preflight checks

Treat this page as a planning asset, not proof that your local environment is ready.

The manual is generated from source-linked project files and Doramagic validation signals.
Community evidence warnings stay visible instead of being converted into marketing claims.
This English page is indexable because the locale quality gate passed and explicit English index approval is enabled.
Use the upstream repository as the final authority for installation commands, license, and version-specific behavior.