Skip to content
TrustedSkillsbeta
Back to all skills

Profiling Performance

Checked
wesleysmits·vlatest·testing

Analyzes system resource usage to identify performance bottlenecks and suggest optimization strategies.

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 wesleysmits/agent-skills --skill profiling-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

wesleysmits

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 wesleysmits/agent-skills at 10274ee62f.

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

Commit
10274ee62f
Manifest
.agent/skills/performance-profiler/SKILL.md
Scanned
1 file, 310 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 allows AI agents to analyze and report on performance metrics. It can identify bottlenecks in code execution, memory usage, or other resource-intensive operations. The agent can then provide insights into how to optimize these areas for improved efficiency.

When to use it

  • Debugging slow application processes: Identify the specific functions or modules causing delays.
  • Optimizing resource utilization: Determine if an application is consuming excessive memory or CPU.
  • Analyzing code performance after refactoring: Confirm that changes have not introduced new bottlenecks.
  • Troubleshooting user-reported slowdowns: Pinpoint the root cause of perceived performance issues.

Key capabilities

  • Performance metric analysis
  • Bottleneck identification
  • Resource usage reporting
  • Optimization insights

Example prompts

  • "Analyze the performance of my Python script and identify any bottlenecks."
  • "Report on memory usage during this process."
  • "What is causing this function to take so long?"

Tips & gotchas

The skill's effectiveness depends on having access to relevant code or execution data. Ensure the agent has sufficient permissions and context to accurately assess performance.