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context-optimizer

Analyze GitHub Copilot agent context usage from VS Code debug logs.

Updated Apr 19, 2026
Search Tags:#context optimization#redundancy detection#GitHub Copilot#token profiling#hand-off analysis
One-click install
npx skills add https://github.com/Avihai-H/infraops --skill context-optimizer-avihai-h
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: context-optimizer
Source: https://github.com/Avihai-H/infraops/tree/main/.github/skills/context-optimizer
Command: npx skills add https://github.com/Avihai-H/infraops --skill context-optimizer-avihai-h

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python, vscode-copilot-chat-logs, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill audits GitHub Copilot agent context window usage, identifies redundancy, and recommends optimizations to improve efficiency.

Core Features & Use Cases

  • Context Efficiency Analysis: Audits how agents consume context window and identifies areas for improvement.
  • Token Cost Profiling: Estimates token spend per turn to optimize context usage.
  • Redundancy Detection: Finds duplicate file reads and overlapping instructions.
  • Hand-Off Gap Analysis: Identifies agents that should delegate to subagents for better context management.
  • Use Case: If you have a complex GitHub Copilot workflow and notice performance issues or unnecessary context growth, this Skill can help optimize it.

Quick Start

Run the context-optimizer skill to analyze context usage in your Copilot agents.

Frequently Asked Questions about context-optimizer

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

FAQPage Schema
How do I reduce redundant context window usage in GitHub Copilot agents?▼

Yes, you can profile token costs per turn by parsing VS Code Copilot Chat debug logs with Python, estimating token spend to identify areas for context optimization and improved efficiency.

What is hand-off gap analysis for multi-agent Copilot workflows?▼

To optimize context usage, run the context-optimizer skill against your Copilot agents to audit context efficiency, detect redundant file reads, and estimate token spend per turn for actionable improvements.

Do I need Python and VS Code Copilot Chat logs to analyze context redundancy?▼

Yes, this context optimization approach applies to complex multi-agent workflows experiencing performance issues or unnecessary context growth, auditing agent context consumption to recommend targeted optimizations.

Why does my GitHub Copilot agent context window grow unnecessarily during complex workflows?▼

No, it specifically requires VS Code Copilot Chat debug logs and Python for parsing; it is designed for GitHub Copilot agents rather than general IDE context optimization or unrelated token profiling tasks.

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