🧪 Lift
This skill aggressively improves latency, throughput, and memory usage by profiling, measuring, and applying safe algorithmic optimizations with guards.
npx playbooks add skill tkersey/dotfiles --skill lift
About Lift
The Lift skill is used for testing and improves the performance of code by reducing latency, increasing throughput, and optimizing memory usage. It achieves this by profiling and measuring the code, then applying safe algorithmic optimizations with guards to ensure reliable results. Developers would use Lift when they need to enhance the efficiency and speed of their code, particularly in applications where latency and memory usage are critical factors.
Its 19-word system prompt specializes your agent in testing & qa with structured methodology and proven output formats. Install with one command to activate immediately.
Use Cases
- Writing unit, integration, and end-to-end tests
- Setting up test coverage and CI pipelines
- Refactoring legacy code with confidence using tests
- Creating test plans and QA checklists
Example Prompts
System Prompt (19 words)
This skill aggressively improves latency, throughput, and memory usage by profiling, measuring, and applying safe algorithmic optimizations with guards.
Frequently Asked Questions
What is Lift?
Lift is a free testing & qa skill for AI coding agents. This skill aggressively improves latency, throughput, and memory usage by profiling, measuring, and applying safe algorithmic optimizations with guards.. It provides a specialized system prompt that configures your agent with testing & qa expertise.
How do I use Lift with Claude Code?
Run npx playbooks add skill tkersey/dotfiles --skill lift in your terminal to install Lift into your Claude Code session. It works immediately after installation.
Which AI coding agents work with Lift?
Lift is compatible with Claude Code, Cursor, GitHub Copilot, Windsurf, OpenClaw, Cline, and any AI agent that supports custom system prompts or .cursorrules files.
Is Lift free to use?
Yes, Lift is completely free and open source. The full source is available on GitHub at https://github.com/tkersey/dotfiles/tree/main/codex/skills/lift. You only need a subscription to the AI agent you use it with.
