Skip to content
TrustedSkillsbeta
Back to all skills

Crewai Multi Agent

Checked
davila7·vlatest·agents·MIT

Orchestrates complex tasks by dynamically assigning roles to multiple CrewAI agents for collaborative problem solving.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add davila7/claude-code-templates --skill crewai-multi-agent -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

davila7

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned davila7/claude-code-templates at 79182c51fb.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
79182c51fb
Manifest
cli-tool/components/skills/ai-research/agents-crewai/SKILL.md
Scanned
4 files, 1,665 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The crewai-multi-agent skill enables the creation and management of multi-agent systems, allowing AI agents to collaborate on complex tasks. It supports defining roles, assigning tasks, and facilitating communication between agents in a structured workflow.

When to use it

  • To automate workflows that require multiple specialized AI agents working together (e.g., research, content generation).
  • For projects requiring task delegation across different agent roles (e.g., data analysis, report writing, and decision-making).
  • When building scalable AI systems where individual agents can handle specific subtasks efficiently.

Key capabilities

  • Multi-agent collaboration framework
  • Role-based agent assignment
  • Task delegation and coordination
  • Structured communication between agents

Example prompts

  • "Create a multi-agent system with roles for researcher, writer, and editor to generate a detailed report."
  • "Assign the task of analyzing customer feedback to an AI agent and then delegate summarization to another."
  • "Set up a team of agents to handle data collection, analysis, and visualization in one workflow."

Tips & gotchas

  • Ensure all agents are properly configured with clear roles and responsibilities for optimal performance.
  • Monitor communication between agents to avoid conflicts or redundant processing.