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Agent Performance Analyzer

Checked
ruvnet·vlatest·agents·MIT

Analyzes agent interactions to identify performance bottlenecks, suggest improvements, and optimize ruvnet agent 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 ruvnet/ruflo --skill agent-performance-analyzer --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-analyzer/SKILL.md
Scanned
1 file, 196 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 Analyzer skill assesses and provides insights into the performance of AI agents. It analyzes agent interactions, identifies areas for improvement, and generates reports on key metrics like task completion rate and efficiency. This allows users to optimize agent workflows and enhance overall productivity.

When to use it

  • Troubleshooting slow or ineffective agents: Identify bottlenecks in an agent's process by analyzing its steps and decision-making.
  • Evaluating new agent configurations: Compare the performance of different agent setups before deploying them widely.
  • Optimizing complex workflows: Pinpoint inefficiencies within multi-step agent tasks to streamline operations.
  • Monitoring long-running agents: Track key metrics over time to ensure consistent and acceptable performance levels.

Key capabilities

  • Interaction analysis
  • Performance metric reporting
  • Workflow bottleneck identification
  • Task completion rate assessment
  • Efficiency evaluation

Example prompts

  • "Analyze the agent's interaction log from yesterday."
  • "Generate a report on task completion rates for the last week."
  • "Identify bottlenecks in the checkout process agent workflow."
  • "Compare the performance of Agent A and Agent B over the past month."

Tips & gotchas

The skill requires access to agent interaction logs or data streams. Ensure sufficient historical data is available for accurate analysis and meaningful insights.