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Performance Profiler

Checked
curiouslearner·vlatest·testing·MIT

Analyzes AI performance, identifies bottlenecks, and suggests improvements via detailed profiling reports and actionable insights.

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 curiouslearner/devkit --skill performance-profiler -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

curiouslearner

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 curiouslearner/devkit at 3fa45b7ab3.

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

Commit
3fa45b7ab3
Manifest
skills/performance-profiler/SKILL.md
Scanned
1 file, 275 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 CuriousLearner Performance Profiler skill allows AI agents to analyze and report on their own execution time. It identifies bottlenecks in code or processes, providing insights into areas for optimization. This helps improve agent efficiency and reduce resource consumption by pinpointing slow operations.

When to use it

  • Debugging Slow Agents: Use when an agent is performing tasks significantly slower than expected.
  • Optimizing Resource Usage: Employ the profiler to identify code sections consuming excessive computational resources.
  • Analyzing Complex Workflows: Apply it to break down and understand the performance of multi-step processes within an AI agent.
  • Identifying Bottlenecks in API Calls: Pinpoint slow or inefficient external API interactions impacting overall agent speed.

Key capabilities

  • Execution time analysis
  • Bottleneck identification
  • Performance reporting

Example prompts

  • "Profile the execution of my process_image function."
  • "Show me a breakdown of how long each step in my workflow takes."
  • "Analyze the performance of my API calls to the external weather service."

Tips & gotchas

The skill requires access to the agent's internal execution environment. Ensure appropriate permissions are granted for accurate profiling and reporting.