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Performance

Checked
thoreinstein·vlatest·other·MIT

Analyzes user workflows to identify bottlenecks and suggest optimizations for improved productivity and task completion rates.

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 thoreinstein/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

thoreinstein

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 thoreinstein/agents at 08388dc947.

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

Commit
08388dc947
Manifest
skills/performance/SKILL.md
Scanned
1 file, 322 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, authored by thoreinstein, enhances AI agent capabilities related to performance. It allows agents to analyze and optimize their own or other entities' operational efficiency. The specific functionalities are not detailed in the provided source material.

When to use it

  • Analyzing the performance of a software application to identify bottlenecks.
  • Evaluating the effectiveness of a marketing campaign based on key metrics.
  • Optimizing resource allocation within a project to improve overall throughput.
  • Assessing the efficiency of a manufacturing process and suggesting improvements.

Key capabilities

  • Performance analysis
  • Optimization suggestions
  • Efficiency evaluation

Example prompts

  • "Analyze the performance data for this application and identify areas for improvement."
  • "Evaluate the effectiveness of our recent marketing campaign based on these metrics."
  • "Suggest ways to optimize resource allocation in project X."

Tips & gotchas

The specific capabilities are not detailed, so experimentation with different prompts may be required. The skill's usefulness depends heavily on the quality and availability of performance data.