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Agent Swarm Workflow

Checked
dicklesworthstone·vlatest·agents

Helps with AI agents, workflows as part of orchestrating AI agents and multi-step workflows workflows.

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 dicklesworthstone/agent_flywheel_clawdbot_skills_and_integrations --skill agent-swarm-workflow -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

dicklesworthstone

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 dicklesworthstone/agent_flywheel_clawdbot_skills_and_integrations at 4d332440c3.

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

Commit
4d332440c3
Manifest
skills/agent-swarm-workflow/SKILL.md
Scanned
1 file, 333 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

The agent-swarm-workflow skill enables the coordination of multiple AI agents to execute complex, multi-step tasks collaboratively. It facilitates a structured environment where individual agents can communicate and delegate sub-tasks to achieve a unified goal efficiently.

When to use it

  • Complex Data Analysis: Break down large datasets into smaller chunks for parallel processing by specialized agents before aggregating results.
  • Multi-Stage Workflows: Automate sequential processes like content creation, where one agent drafts text and another optimizes it for SEO.
  • Collaborative Problem Solving: Deploy a team of agents to brainstorm solutions from different perspectives before synthesizing a final recommendation.
  • Decentralized Task Management: Distribute routine monitoring or data entry tasks across multiple instances to increase throughput and reliability.

Key capabilities

  • Orchestrates interactions between multiple autonomous AI agents.
  • Manages task delegation and handoff between team members.
  • Supports parallel execution of independent sub-tasks.
  • Aggregates outputs from various agents into a cohesive final result.

Example prompts

  • "Create a swarm of three agents to analyze this financial report: one for trend identification, one for risk assessment, and one for summarizing key findings."
  • "Set up a workflow where an agent drafts a blog post, a second agent reviews it for tone, and a third publishes it to the CMS."
  • "Deploy a team of agents to monitor social media mentions of our brand across different platforms and generate a daily sentiment report."

Tips & gotchas

Ensure you define clear roles and communication protocols for each agent in the swarm to prevent redundant work or conflicting outputs. Limit the size of the swarm based on your system's resource constraints, as coordinating many agents simultaneously can increase latency.