How should CrewAI-Crash-Course be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this skill.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

Crawler Summary

CrewAI-Crash-Course answer-first brief

Comprehensive CrewAI tutorial with 7 modules covering basics to advanced topics. Learn multi-agent AI systems, LLM integration, observability, and production patterns. Perfect for AI agent development. CrewAI Crash Course 🚀 A comprehensive, hands-on tutorial and learning resource for **CrewAI** - the powerful framework for building multi-agent AI systems. This repository contains practical examples, step-by-step guides, and real-world implementations covering all aspects of CrewAI development. 📋 Overview **CrewAI Crash Course** is your complete guide to mastering CrewAI, featuring: - ✅ **7 comprehensive modules** Capability contract not published. No trust telemetry is available yet. 1 GitHub stars reported by the source. Last updated 4/16/2026.

Freshness

Last checked 4/16/2026

Best For

CrewAI-Crash-Course is best for crewai, multi-agent workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB OPENCLEW, runtime-metrics, public facts pack

Card Facts Snapshot Contract Trust

Claim this agent

Agent DossierGitHubSafety: 66/100

CrewAI-Crash-Course

OpenClawself-declared

Public facts

Change events

Artifacts

Freshness

Apr 16, 2026

Verifiededitorial-contentNo verified compatibility signals1 GitHub stars

Capability contract not published. No trust telemetry is available yet. 1 GitHub stars reported by the source. Last updated 4/16/2026.

1 GitHub starsTrust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Apr 16, 2026

Vendor

Bhanuchaddha

Artifacts

Benchmarks

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. 1 GitHub stars reported by the source. Last updated 4/16/2026.

View Source

Setup snapshot

git clone https://github.com/bhanuchaddha/CrewAI-Crash-Course.git

1
Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
2
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content

Vendor (1)

Vendor

Bhanuchaddha

profilemedium

Observed Apr 16, 2026Source link Provenance

Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium

Observed Apr 16, 2026Source link Provenance

Adoption (1)

Adoption signal

1 GitHub stars

profilemedium

Observed Apr 16, 2026Source link Provenance

Security (1)

Handshake status

UNKNOWN

trustmedium

Observed unknownSource link Provenance

Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium

Observed Apr 15, 2026Source link Provenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Docs Update

Docs refreshed: Sign in to GitHub · GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB OPENCLEW

Extracted files

Examples

Snippets

Languages

python

Executable Examples

text

CrewAI-Crash-Course/
├── knowledge/                      # Sample knowledge files
│   ├── customer.json
│   ├── products.txt
│   └── transactions.xlsx
├── src/
│   ├── 1_basics/                  # Basic crew creation
│   ├── 2_tasks/                   # Task management
│   ├── 3_crew/                    # Crew operations
│   ├── 4_tools/                   # Tool integration
│   ├── 5_knowledge/               # Knowledge management
│   ├── 6_llm/                     # LLM integrations
│   └── 7_observability/           # Monitoring & tracing
└── pyproject.toml

bash

git clone https://github.com/bhanuchaddha/CrewAI-Crash-Course.git
cd CrewAI-Crash-Course

bash

uv venv
# or
python -m venv venv

bash

source venv/bin/activate  # On macOS/Linux
# or
venv\Scripts\activate  # On Windows

bash

uv pip install -e .
# or
pip install -e .

python

from crewai import Agent, Crew, Task

# Create an agent
agent = Agent(
    name="Researcher",
    role="Research Analyst",
    goal="Provide accurate research",
    backstory="Expert researcher with attention to detail"
)

# Create a task
task = Task(
    description="Research the latest AI trends",
    expected_output="A comprehensive report on AI trends",
    agent=agent
)

# Create and run crew
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB OPENCLEW

Docs source

GITHUB OPENCLEW

Editorial quality

ready

Full README

CrewAI Crash Course 🚀

A comprehensive, hands-on tutorial and learning resource for CrewAI - the powerful framework for building multi-agent AI systems. This repository contains practical examples, step-by-step guides, and real-world implementations covering all aspects of CrewAI development.

📋 Overview

CrewAI Crash Course is your complete guide to mastering CrewAI, featuring:

✅ 7 comprehensive modules covering everything from basics to advanced topics
✅ Hands-on examples with real code you can run immediately
✅ Best practices and production-ready patterns
✅ Observability integration with LangTrace
✅ Knowledge management techniques
✅ LLM integration (OpenAI, Anthropic Claude, local LLMs with Ollama)

🎯 What is CrewAI?

CrewAI is a cutting-edge framework for orchestrating role-playing, autonomous AI agents. It enables you to build sophisticated multi-agent systems where agents collaborate to solve complex tasks.

✨ Features

📚 Module 1: Basics

Create crews programmatically
Configure crews using YAML
Agent and task management

📋 Module 2: Tasks

Access task outputs (Pydantic & JSON)
Task dependencies and chaining
Task callbacks
Guardrail validations

👥 Module 3: Crew Management

Access crew outputs
Crew orchestration patterns

🛠️ Module 4: Tools Integration

Using tools with tasks
Custom tool development

📖 Module 5: Knowledge Management

Reading files as knowledge
Knowledge base integration

🤖 Module 6: LLM Integration

Local LLM setup with Ollama
Anthropic Claude integration
Any LLM provider support

📊 Module 7: Observability

Tracing with LangTrace
Performance monitoring
Debugging and logging

🏗️ Project Structure

CrewAI-Crash-Course/
├── knowledge/                      # Sample knowledge files
│   ├── customer.json
│   ├── products.txt
│   └── transactions.xlsx
├── src/
│   ├── 1_basics/                  # Basic crew creation
│   ├── 2_tasks/                   # Task management
│   ├── 3_crew/                    # Crew operations
│   ├── 4_tools/                   # Tool integration
│   ├── 5_knowledge/               # Knowledge management
│   ├── 6_llm/                     # LLM integrations
│   └── 7_observability/           # Monitoring & tracing
└── pyproject.toml

🚀 Getting Started

Prerequisites

Python 3.8+
pip or uv package manager
(Optional) OpenAI API key or Anthropic API key for cloud LLMs
(Optional) Ollama for local LLM support

Installation

Clone the repository:

git clone https://github.com/bhanuchaddha/CrewAI-Crash-Course.git
cd CrewAI-Crash-Course

Create virtual environment:

uv venv
# or
python -m venv venv

Activate virtual environment:

source venv/bin/activate  # On macOS/Linux
# or
venv\Scripts\activate  # On Windows

Install dependencies:

uv pip install -e .
# or
pip install -e .

Quick Start Example

from crewai import Agent, Crew, Task

# Create an agent
agent = Agent(
    name="Researcher",
    role="Research Analyst",
    goal="Provide accurate research",
    backstory="Expert researcher with attention to detail"
)

# Create a task
task = Task(
    description="Research the latest AI trends",
    expected_output="A comprehensive report on AI trends",
    agent=agent
)

# Create and run crew
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

📖 Module Guide

Module 1: Basics

Learn how to create crews both programmatically and using YAML configuration files.

Module 2: Tasks

Master task management including dependencies, callbacks, and output handling.

Module 3: Crew Management

Understand crew orchestration and output management.

Module 4: Tools

Integrate custom tools and external APIs with your agents.

Module 5: Knowledge

Feed your agents with structured knowledge from files and databases.

Module 6: LLM Integration

Configure different LLM providers and optimize for cost and performance.

Module 7: Observability

Monitor, trace, and debug your AI agent systems.

🔧 Configuration

Environment Variables

Create a .env file for API keys:

OPENAI_API_KEY=your_key_here
ANTHROPIC_API_KEY=your_key_here

YAML Configuration

Example agents.yaml:

agents:
  - name: Researcher
    role: Research Analyst
    goal: Provide accurate research

📝 Examples

Each module contains multiple examples demonstrating different aspects of CrewAI. Navigate to the specific module directory and run the examples:

cd src/1_basics
python 1_create_crew_programmatically.py

🎓 Learning Path

Start with Module 1 - Understand the basics
Move to Module 2 - Learn task management
Explore Modules 3-4 - Advanced crew features
Integrate knowledge - Module 5
Configure LLMs - Module 6
Add observability - Module 7

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Fork the repository
Create your feature branch (git checkout -b feature/AmazingFeature)
Commit your changes (git commit -m 'Add some AmazingFeature')
Push to the branch (git push origin feature/AmazingFeature)
Open a Pull Request

📄 License

This project is open source and available for educational purposes.

🔗 Resources

🌟 Star History

If you find this repository helpful, please consider giving it a star! ⭐

Built with ❤️ for the AI agent community

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB OPENCLEW

Endpoints

Dossier API Snapshot API Contract API Trust API

Contract coverage

Status

missing

Auth

None

Streaming

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.

Invocation examples

curl -s "https://xpersona.co/api/v1/agents/crewai-bhanuchaddha-crewai-crash-course/snapshot"

curl -s "https://xpersona.co/api/v1/agents/crewai-bhanuchaddha-crewai-crash-course/contract"

curl -s "https://xpersona.co/api/v1/agents/crewai-bhanuchaddha-crewai-crash-course/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.

No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media

No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors

GITHUB_REPOSactivepieces

Rank

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

Traction

No public download signal

Freshness

Updated 2d ago

OPENCLAW

GITHUB_REPOScherry-studio

Rank

AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs

Traction

No public download signal

Freshness

Updated 5d ago

MCPOPENCLAW

GITHUB_REPOSAionUi

Rank

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW

GITHUB_REPOSCopilotKit

Rank

The Frontend for Agents & Generative UI. React + Angular

Traction

No public download signal

Freshness

Updated 23d ago

OPENCLAW

Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://xpersona.co/api/v1/agents/crewai-bhanuchaddha-crewai-crash-course/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/crewai-bhanuchaddha-crewai-crash-course/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/crewai-bhanuchaddha-crewai-crash-course/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-bhanuchaddha-crewai-crash-course/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-bhanuchaddha-crewai-crash-course/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-bhanuchaddha-crewai-crash-course/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-04-17T00:10:54.359Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "crewai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "multi-agent",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:crewai|supported|profile capability:multi-agent|supported|profile"
}

Facts JSON

[
  {
    "factKey": "vendor",
    "label": "Vendor",
    "value": "Bhanuchaddha",
    "category": "vendor",
    "href": "https://github.com/bhanuchaddha/CrewAI-Crash-Course",
    "sourceUrl": "https://github.com/bhanuchaddha/CrewAI-Crash-Course",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-16T06:46:55.715Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "protocols",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "category": "compatibility",
    "href": "https://xpersona.co/api/v1/agents/crewai-bhanuchaddha-crewai-crash-course/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-bhanuchaddha-crewai-crash-course/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-04-16T06:46:55.715Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "traction",
    "label": "Adoption signal",
    "value": "1 GitHub stars",
    "category": "adoption",
    "href": "https://github.com/bhanuchaddha/CrewAI-Crash-Course",
    "sourceUrl": "https://github.com/bhanuchaddha/CrewAI-Crash-Course",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-16T06:46:55.715Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "docs_crawl",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "category": "integration",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "handshake_status",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "category": "security",
    "href": "https://xpersona.co/api/v1/agents/crewai-bhanuchaddha-crewai-crash-course/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-bhanuchaddha-crewai-crash-course/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true,
    "metadata": {}
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true,
    "metadata": {}
  }
]