Instantly Performance Tuning
ListedAutomatically optimizes AI model performance across various metrics using advanced algorithms developed by jeremylongshore.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill instantly-performance-tuning -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
jeremylongshore
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.
Automated safety checks
We could not read this skill's source, so none of the checks below were run.
About this skill
What it does
This skill allows AI agents to rapidly optimize code for performance. It identifies bottlenecks and suggests targeted improvements, such as algorithm changes or data structure adjustments. The goal is to reduce execution time and resource consumption without significantly impacting functionality.
When to use it
- Slow Code Execution: When a script or function takes an unexpectedly long time to complete.
- Resource Intensive Tasks: When code consumes excessive memory or CPU resources.
- Performance Bottlenecks: During debugging, when profiling reveals specific areas of code that are slowing down overall performance.
- Optimization for Scale: When preparing code for increased load and user traffic.
Key capabilities
- Bottleneck identification
- Algorithm optimization suggestions
- Data structure recommendations
- Code refactoring proposals
Example prompts
- "Analyze this Python script and suggest ways to improve its execution speed."
- "This JavaScript function is using too much memory; can you optimize it?"
- "I'm seeing performance degradation in my application. Can you identify the bottlenecks?"
Tips & gotchas
The skill’s suggestions should be carefully reviewed, as they may involve trade-offs between performance and code readability or maintainability. It is recommended to test any changes thoroughly before deploying them.