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Agent skill

Profiling Application Performance

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Execute this skill enables AI assistant to profile application performance, analyzing cpu usage, memory consumption, and execution time.

MITAuto-check passedDevelopment

Install Profiling Application Performance

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill profiling-application-performance -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace profiling-application-performance --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/profiling-application-performance .claude/skills/profiling-application-performance && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
profiling-application-performance
GitHub stars
2.8k
Token cost
~894 tokens
SKILL.md length
362 words
Files
6 (incl. scripts, references, assets)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Execute this skill enables AI assistant to profile application performance, analyzing cpu usage, memory consumption, and execution time.

  • Works in 4 steps: Identify Application Stack: Determines… → Locate Entry Points: Identifies main… → Analyze Performance Metrics: Examines… → …
  • Requests performance analysis
  • SKILL.md covers Overview, How It Works, When to Use This Skill and Examples, plus 7 more sections
  • Runs Python scripts from its folder

What it does

Profiling Application Performance is an agent skill from jeremylongshore/tons-of-skills-marketplace. Execute this skill enables AI assistant to profile application performance, analyzing cpu usage, memory consumption, and execution time. it is triggered when the user requests performance analysis, bottleneck identification, or optimization recommendations. the... Use when optimizing performance. Trigger with phrases like 'optimize', 'performance', or 'speed up'.

Its SKILL.md is about 890 tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts, reference files and assets (for example `assets/README.md`, `references/README.md` and `scripts/README.md`). Compatibility notes: Designed for Claude Code

It sits in Development, covering Performance optimization. It works with Python and Node.js. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Requests performance analysis
  • Bottleneck identification
  • Optimization recommendations
  • Optimizing performance

Example prompts

  • “optimize”
  • “performance”
  • “speed up”
  • “/profiling-application-performance”

Requirements

  • Python 3
  • Node.js
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Grep, Glob, Bash(cmd:*)

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Identify Application Stack: Determines the application's technology (e.g., Node.js, Python, Java).
  2. Locate Entry Points: Identifies main application entry points and critical execution paths.
  3. Analyze Performance Metrics: Examines CPU usage, memory allocation, and execution time to detect bottlenecks.
  4. Generate Profile: Compiles the analysis into a comprehensive performance profile, highlighting areas for optimization.

What it can do on your machine

Read from SKILL.md and the folder at commit 23ea8d4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Grep
    • Glob
    • Bash(cmd:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Profiling Application Performance loads about 894 tokens when it runs, and up to ~910 if it reads all its reference files. Until then it costs about 100 tokens; SKILL.md has 362 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~100
When it runs · the whole SKILL.md, loaded when a task matches
~894
With references · SKILL.md plus every file in references/, read only if the agent opens them
~910

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit 23ea8d4, republished under its MIT licence (© jeremylongshore). 362 words, ~894 tokens.

Download SKILL.mdSave it as .claude/skills/profiling-application-performance/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
profiling-application-performance
description
Execute this skill enables AI assistant to profile application performance, analyzing cpu usage, memory consumption, and execution time. it is triggered when the user requests performance analysis, bottleneck identification, or optimization recommendations. the... Use when optimizing performance. Trigger with phrases like 'optimize', 'performance', or 'speed up'.
allowed-tools
Read, Write, Edit, Grep, Glob, Bash(cmd:*)
compatibility
Designed for Claude Code
version
1.21.0
author
Jeremy Longshore <jeremy@intentsolutions.io>
license
MIT
tags
performance, profiling-application

Application Profiler

Profile application performance across Node.js, Python, and Java stacks by analyzing CPU usage, memory allocation, and execution hotspots to pinpoint optimization targets.

Overview

This skill empowers Claude to analyze application performance, pinpoint bottlenecks, and recommend optimizations. By leveraging the application-profiler plugin, it provides insights into CPU usage, memory allocation, and execution time, enabling targeted improvements.

How It Works

  1. Identify Application Stack: Determines the application's technology (e.g., Node.js, Python, Java).
  2. Locate Entry Points: Identifies main application entry points and critical execution paths.
  3. Analyze Performance Metrics: Examines CPU usage, memory allocation, and execution time to detect bottlenecks.
  4. Generate Profile: Compiles the analysis into a comprehensive performance profile, highlighting areas for optimization.

When to Use This Skill

This skill activates when you need to:

  • Analyze application performance for bottlenecks.
  • Identify CPU-intensive operations and memory leaks.
  • Optimize application execution time.

Examples

Example 1: Identifying Memory Leaks

User request: "Analyze my Node.js application for memory leaks."

The skill will:

  1. Activate the application-profiler plugin.
  2. Analyze the application's memory allocation patterns.
  3. Generate a profile highlighting potential memory leaks.
Example 2: Optimizing CPU Usage

User request: "Profile my Python script and find the most CPU-intensive functions."

The skill will:

  1. Activate the application-profiler plugin.
  2. Analyze the script's CPU usage.
  3. Generate a profile identifying the functions consuming the most CPU time.
Show full SKILL.md (139 more words)Show less

Best Practices

  • Code Instrumentation: Ensure the application code is instrumented for accurate profiling.
  • Realistic Workloads: Use realistic workloads during profiling to simulate real-world scenarios.
  • Iterative Optimization: Apply optimizations iteratively and re-profile to measure improvements.

Integration

This skill can be used in conjunction with code editing plugins to implement the recommended optimizations directly within the application's source code. It can also integrate with monitoring tools to track performance improvements over time.

Prerequisites

  • Appropriate file access permissions
  • Required dependencies installed

Instructions

  1. Invoke this skill when the trigger conditions are met
  2. Provide necessary context and parameters
  3. Review the generated output
  4. Apply modifications as needed

Output

The skill produces structured output relevant to the task.

Error Handling

  • Invalid input: Prompts for correction
  • Missing dependencies: Lists required components
  • Permission errors: Suggests remediation steps

Resources

  • Project documentation
  • Related skills and commands

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (scripts, references, assets) in skills/.curated/profiling-application-performance of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • assets/README.md
  • references/README.md
  • scripts/README.md
  • scripts/analyze_results.py
  • scripts/generate_report.py

Open the folder on GitHubat commit 23ea8d4

Compare with similar skills

Profiling Application Performance next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Profiling Application Performance compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Profiling Application Performance this skilljeremylongshore/tons-of-skills-marketplace2.8k—~894Automated safety check: PassMIT
Performance Profileralirezarezvani/claude-skills28k—~684Automated safety check: PassMIT
Phy Memory Leak DetectorLeoYeAI/openclaw-master-skills2.2k—~4.3kAutomated safety check: PassApache-2.0
Performance Profilerborghei/Claude-Skills881—~1.8kAutomated safety check: PassMIT
Afrexai Performance EngineeringLeoYeAI/openclaw-master-skills2.2k—~7.1kAutomated safety check: PassMIT
Code Review ChecklistshareAI-lab/learn-claude-code78k5 repos~1.1kAutomated safety check: PassMIT

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Works with

Categories

Questions about Profiling Application Performance

What does Profiling Application Performance do?

Execute this skill enables AI assistant to profile application performance, analyzing cpu usage, memory consumption, and execution time. Profiling Application Performance is an agent skill from jeremylongshore/tons-of-skills-marketplace. Execute this skill enables AI assistant to profile application performance, analyzing cpu usage, memory consumption, and execution time.

When should I use Profiling Application Performance?

Profiling Application Performance fits situations like: requests performance analysis; bottleneck identification; optimization recommendations; optimizing performance.

How do I install Profiling Application Performance in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill profiling-application-performance -a claude-code`. Or copy the skill folder (skills/.curated/profiling-application-performance in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/profiling-application-performance in your project. Claude Code loads it when a task matches its description.

How do I install Profiling Application Performance in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill profiling-application-performance -a codex`. Or copy the skill folder (skills/.curated/profiling-application-performance in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/profiling-application-performance in your project. Codex loads it when a task matches its description.

Can I use Profiling Application Performance in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill profiling-application-performance -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/profiling-application-performance, .gemini/skills/profiling-application-performance, .github/skills/profiling-application-performance and .opencode/skills/profiling-application-performance in your project.

What does Profiling Application Performance need to run?

Going by SKILL.md and its folder, Profiling Application Performance needs Python for the scripts in its folder. Our summary lists: Python 3; Node.js. Its frontmatter pre-approves these tools: Read, Write, Edit, Grep, Glob, Bash(cmd:*). Compatibility (from SKILL.md): Designed for Claude Code.

Does Profiling Application Performance access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Profiling Application Performance safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Profiling Application Performance use?

Profiling Application Performance is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Profiling Application Performance use?

About 894 tokens (SKILL.md is roughly 3.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 16 tokens, read only when the agent opens those files.

What are the alternatives to Profiling Application Performance?

Skills that share tags, products or a category with Profiling Application Performance: Performance Profiler (alirezarezvani/claude-skills, 28k stars), Phy Memory Leak Detector (LeoYeAI/openclaw-master-skills, 2.2k stars), Performance Profiler (borghei/Claude-Skills, 881 stars) and Afrexai Performance Engineering (LeoYeAI/openclaw-master-skills, 2.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Profiling Application Performance?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,821 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 8, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.