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Performance Profiling

Checked
kentoshimizu·vlatest·testing·Apache-2.0

Analyzes code execution to identify performance bottlenecks and suggest optimizations based on Kentoshimizu's expertise.

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 kentoshimizu/sw-agent-skills --skill performance-profiling -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

kentoshimizu

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 kentoshimizu/sw-agent-skills at 5b7bafb626.

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

Commit
5b7bafb626
Manifest
skills/performance-profiling/SKILL.md
Scanned
3 files, 75 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 provides performance profiling capabilities for AI agents. It allows users to identify bottlenecks and areas of inefficiency within agent workflows, ultimately leading to improved response times and resource utilization. The tool analyzes execution traces and presents data visualizations to pinpoint problematic code segments or API calls.

When to use it

  • Slow Response Times: Investigate why an agent is taking longer than expected to complete tasks.
  • High Resource Consumption: Identify areas where the agent is using excessive CPU, memory, or network bandwidth.
  • Debugging Performance Issues: Pinpoint specific code blocks contributing to performance degradation after updates or modifications.
  • Optimizing API Usage: Analyze API call patterns to identify potential inefficiencies and opportunities for optimization.

Key capabilities

  • Execution trace analysis
  • Data visualization of performance metrics
  • Bottleneck identification
  • API call pattern analysis

Example prompts

  • "Profile the execution time of my agent's 'summarize_article' function."
  • "Show me a graph of API calls made during the last hour, sorted by latency."
  • "Identify the most resource-intensive parts of my agent’s workflow."

Tips & gotchas

The skill requires access to execution traces from the AI agent. Ensure proper logging and tracing is enabled within your agent's environment for accurate profiling data.