performance

Profile code execution and benchmark shell commands for performance diagnostics.

Updated Jun 22, 2026
One-click install
npx skills add https://github.com/alangeb/tau --skill performance-alangeb
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: performance
Source: https://github.com/alangeb/tau/tree/main/src/skills/performance
Command: npx skills add https://github.com/alangeb/tau --skill performance-alangeb

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill addresses performance degradation by identifying bottlenecks, measuring execution latency, and providing actionable insights into token usage and tool call efficiency.

Core Features & Use Cases

  • Profiling & Benchmarking: Analyze function execution times and shell command performance to pinpoint slow operations.
  • Audit Analysis: Parse session logs to calculate tool call durations and identify high-latency components.
  • Use Case: When an agent response feels sluggish, use this skill to profile the specific tool calls and audit logs to determine if the delay is caused by excessive context size or inefficient script execution.

Quick Start

Use the performance skill to audit the current session log and identify the top ten slowest tool calls.

Frequently Asked Questions about performance

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I profile code execution to identify performance bottlenecks?

Profiling code execution uses standard library access to cProfile and pstats to pinpoint slow operations. It analyzes function execution times to provide deterministic performance diagnostics and actionable insights into resource usage.

How can I benchmark shell commands to measure execution latency?

Benchmarking shell commands requires the subprocess module to measure execution latency. It analyzes shell command performance to pinpoint slow operations and identify bottlenecks within script execution workflows.

How do I audit tool call latency in session logs?

Auditing tool call latency parses session logs to calculate tool call durations. It identifies high-latency components and highlights the top ten slowest tool calls to determine if delays are caused by excessive context size.

Can I optimize AI agent context management and token counting?

Optimizing AI agent context management and token counting is supported through execution profiling and latency auditing. It identifies inefficiencies in token usage and tool call efficiency to resolve sluggish agent responses.

Do I need specific dependencies to run a performance audit?

Running a performance audit requires standard library access to cProfile, pstats, and subprocess modules. There are no external dependencies needed to perform deterministic performance diagnostics and execution analysis.