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Agent Performance Benchmarker

Checked
ruvnet·vlatest·agents·MIT

Ruvnet's agent-performance-benchmarker automatically assesses agent capabilities across diverse tasks, providing quantifiable performance metrics.

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/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-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 Agent Performance Benchmarker skill allows you to evaluate the performance of AI agents across various tasks. It provides structured testing and reporting, enabling comparisons between different agent configurations or models. This facilitates identifying strengths, weaknesses, and areas for improvement in your AI agents.

When to use it

  • Comparing Agent Models: Determine which language model (e.g., GPT-4 vs. Claude 3) performs best on a specific set of tasks within an agent.
  • Evaluating Prompt Engineering Changes: Measure the impact of prompt modifications on an agent's accuracy and efficiency.
  • Assessing Tool Integration: Quantify how effectively an agent utilizes external tools or APIs to complete complex workflows.
  • Regression Testing: Ensure that changes to an agent’s code or configuration don't negatively affect its performance over time.

Key capabilities

  • Structured task definition and execution
  • Automated result logging and reporting
  • Performance comparison across different agents
  • Task-specific evaluation metrics

Example prompts

  • "Run the 'website_scraping' benchmark with agent version 1.2."
  • "Compare the performance of Agent A and Agent B on the 'data_extraction' task."
  • "Generate a report showing the average completion time for each task in the 'customer_service' suite."

Tips & gotchas

The skill requires clear definitions of tasks and expected outputs to accurately measure agent performance. Ensure that the benchmark environment is consistent across different agents being compared to avoid skewed results.