agents-crewai

Multi-agent orchestration framework for autonomous AI collaboration.

IndexedMIT★ 25

Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/vadimcomanescu-agents-crewai

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

About

Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast execution.

Use cases: agent-building

Reviews

Write a review

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools: No tools found
Secrets: None asked for
Install scripts: None found

Network hosts it talks to 1

codeload.github.com · found in install command

Files it touches

~/.claude/skills/agents-crewai

What's inside

Skill name: agents-crewai
Description: Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast execution.
License: MIT
Instructions: 39 lines in SKILL.md · view on GitHub

Files (6)

LICENSE.txt
SKILL.md
examples.md · references/
flows.md · references/
tools.md · references/
troubleshooting.md · references/

SKILL.md (first lines)

# CrewAI

Design and run role-based agent teams using CrewAI.

## Quick Start
1) Define agents with clear roles and goals.
2) Define tasks with explicit expected outputs.
3) Choose a process (sequential vs. hierarchical).
4) Run the crew and inspect outputs.

## Minimal Example
```python
from crewai import Agent, Task, Crew, Process

researcher = Agent(role="Researcher", goal="Find 5 key trends")
writer = Agent(role="Writer", goal="Summarize findings")

research = Task(description="Research AI agents", expected_output="5 bullets", agent=researcher)
write = Task(description="Write a summary", expected_output="Short memo", agent=writer, context=[research])

crew = Crew(agents=[researcher, writer], tasks=[research, write], process=Process.sequential)
result = crew.kickoff(inputs={"topic": "AI agents"})
print(result.raw)
```

## Design Guidance
- Keep roles narrow and outputs explicit.
- Use context chaining to pass outputs between tasks.
- Prefer sequential for reliability; hierarchical for delegation-heavy workflows.

## Use Alternatives When
- You need complex graph cycles → consider LangGraph.
- You’re focused on document retrieval → consider LlamaIndex.

## References
- Extended examples: `references/examples.md`

From vadimcomanescu/codex-skills, MIT.

Signals

Stars: 25
Forks: 8
Open issues: 2
Last commit (this folder): Jan 19, 2026 (9 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License: MIT
Repository: github.com/vadimcomanescu/codex-skills
First seen: Oct 24, 2026
Last checked: Oct 24, 2026
Source: GitHub github-graphql

More from vadimcomanescu

Cite this page

agents-crewai skill. Agent Mart. https://agentmart.dev/skills/vadimcomanescu-agents-crewai (last updated 2026-10-24)