context-budget

Audit token consumption across agents, skills, MCP servers, and rules.

1|Updated Apr 6, 2026

Search Tags:#performance #context #optimization #audit #tokens #claude-code

Ready to run

npx skills add https://github.com/vrcms/everything-qwen-code --skill context-budget-vrcms

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: context-budget
Source: https://github.com/vrcms/everything-qwen-code/tree/main/.qwen/skills/context-budget
Command: npx skills add https://github.com/vrcms/everything-qwen-code --skill context-budget-vrcms

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses the issue of context window bloat, where excessive agents, rules, and MCP servers degrade AI performance and consume valuable token space.

Core Features & Use Cases

Token Consumption Audit: Scans all loaded components to calculate total token overhead.
Actionable Optimization: Identifies redundant or heavy components and provides prioritized recommendations for removal.
Use Case: Before adding new project-specific agents, run this skill to determine if your current configuration has sufficient headroom or if you need to prune unused tools.

Quick Start

Run the context budget analysis to identify which components are consuming the most tokens in your current session.

Frequently Asked Questions about context-budget

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

FAQPage Schema

How do I audit token consumption in claude-code to reduce context window bloat?▼

To audit token consumption, scan all loaded agents, MCP servers, and rules to calculate total token overhead. This identifies bloat and redundant components, providing prioritized recommendations for removal to free up context headroom.

What is context window bloat and when do I need a token-savings analysis?▼

Context window bloat occurs when excessive agents, rules, and MCP servers degrade AI performance and consume valuable token space. You need token-savings analysis when session performance drops or before adding new project-specific components to your environment.

How do I estimate context headroom before adding new agents to my AI development environment?▼

Estimate context headroom by running a context budget analysis on your current session. This calculates the token overhead of existing components, determining if you have sufficient space or need to prune unused tools before adding new agents.

What is the best way to optimize AI context window performance for session management?▼

The best way to optimize AI context window performance is auditing token consumption across all loaded components. This identifies heavy or redundant items and provides prioritized recommendations for removal, directly improving session performance management.

Does context budget analysis work with custom MCP servers and project-specific rules?▼

Yes, context budget analysis scans all loaded components including custom MCP servers, agents, and project-specific rules. It calculates the total token overhead of these elements to identify redundant or heavy components for configuration planning.

Why does my AI performance degrade when loading multiple agents and MCP servers?▼

AI performance degrades due to context window bloat, where excessive agents, rules, and MCP servers consume valuable token space. Running a token consumption audit identifies these heavy components and provides actionable optimization recommendations.