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Agent Topology Optimizer

Checked
ruvnet·vlatest·agents·MIT

Optimizes network infrastructure layouts and resource allocation within virtual environments for peak performance using ruvnet's AI.

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 ruvnet/ruflo --skill agent-topology-optimizer --full-depth -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

ruvnet

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 ruvnet/claude-flow at 49da6ecc44.

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

Commit
49da6ecc44
Manifest
.agents/skills/agent-topology-optimizer/SKILL.md
Scanned
1 file, 791 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 agent-topology-optimizer skill analyzes and restructures agent workflows to improve efficiency. It identifies redundant or inefficient steps within a sequence of agents, suggesting optimizations like merging agents or reordering tasks. This results in faster execution times and reduced resource consumption for complex agent chains.

When to use it

  • Slow Agent Chains: When an existing chain of AI agents takes too long to complete a task.
  • High Resource Consumption: If running multiple agents is straining system resources (CPU, memory).
  • Complex Workflows: For intricate workflows involving numerous agents and dependencies where optimization potential exists.
  • Debugging Agent Sequences: To help understand the flow of data and identify bottlenecks in agent chains.

Key capabilities

  • Workflow analysis
  • Redundancy detection
  • Agent merging suggestions
  • Task reordering recommendations

Example prompts

  • "Analyze this agent chain: [paste agent chain description] and suggest optimizations."
  • "Can you simplify the following workflow to reduce execution time? [paste agent chain description]"
  • "I'm seeing high resource usage in my agent sequence. Suggest ways to make it more efficient."

Tips & gotchas

The quality of optimization suggestions depends heavily on a clear and detailed description of the existing agent topology. Providing context about the purpose of each agent will yield better results.