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Agent Performance Benchmarker

Checked
ruvnet·vlatest·agents·MIT

Automatically assesses ruvnet agent performance across key metrics, providing actionable insights for optimization and improvement.

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-performance-benchmarker --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/ruflo at b636802d8c.

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

Commit
b636802d8c
Manifest
.agents/skills/agent-performance-benchmarker/SKILL.md
Scanned
1 file, 842 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 ruvnet-agent-performance-benchmarker skill allows you to evaluate and compare the performance of AI agents. It provides a standardized benchmarking framework, enabling objective assessment of different agent configurations or models. This helps identify strengths and weaknesses in agent design and optimize for specific tasks.

When to use it

  • Comparing Agent Models: Evaluate which language model performs best on a given task within an agent setup.
  • Optimizing Agent Configurations: Test various prompt engineering techniques or tool integrations to see how they impact overall agent performance.
  • Identifying Bottlenecks: Pinpoint areas where an agent is struggling, such as slow response times or inaccurate results.
  • Regression Testing: Ensure that changes made to an agent don't negatively impact its performance over time.

Key capabilities

  • Standardized benchmarking framework
  • Performance evaluation of AI agents
  • Comparison of different agent configurations
  • Objective assessment of agent strengths and weaknesses

Example prompts

  • "Benchmark the 'agent_a' configuration against 'agent_b' using the provided task list."
  • "Run a performance test on my agent with prompt 'X' versus prompt 'Y'."
  • "Evaluate agent performance for this specific scenario: [scenario description]."

Tips & gotchas

The skill requires a defined set of tasks or scenarios to benchmark against. Ensure these are representative of the intended use case for accurate and meaningful results.