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Performance

Checked
outfitter-dev·vlatest·productivity·MIT

Analyzes developer performance metrics, identifies bottlenecks, and suggests targeted improvements to boost team productivity.

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 outfitter-dev/agents --skill performance -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

outfitter-dev

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 outfitter-dev/agents at d37fffdd50.

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

Commit
d37fffdd50
Manifest
plugins/outfitter/skills/performance/SKILL.md
Scanned
2 files, 698 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

This skill, outfitter-dev-performance, focuses on optimizing AI agent workflows and output. It helps identify bottlenecks in processes, suggests improvements to code or prompts, and ultimately aims to increase the efficiency and effectiveness of agent tasks. The skill can analyze existing agent behavior and provide actionable recommendations for enhancement.

When to use it

  • Slow Agent Performance: If an agent is taking too long to complete a task, this skill can help pinpoint the cause and suggest solutions.
  • Suboptimal Output Quality: When the output from an AI agent isn't meeting expectations, outfitter-dev-performance can analyze the process and recommend prompt or code adjustments.
  • Debugging Agent Logic: Use it to understand why an agent is behaving unexpectedly by identifying inefficiencies in its execution flow.
  • Optimizing Resource Usage: If you want to reduce the computational resources consumed by your AI agents, this skill provides insights for optimization.

Key capabilities

  • Workflow analysis
  • Bottleneck identification
  • Code suggestion
  • Prompt refinement
  • Performance improvement recommendations

Example prompts

  • "Analyze my agent's workflow for generating marketing copy and suggest improvements."
  • "Identify bottlenecks in this code snippet used by my AI agent: [code]"
  • “How can I optimize the prompt I’m using to summarize legal documents?”

Tips & gotchas

This skill is most effective when provided with access to the agent's workflow logs or relevant code snippets. It may require some technical expertise to implement the suggested changes effectively.