Can this help with 'out of context' errors?

Yes, by identifying redundant rules, overlapping skills, and heavy agent descriptions, it helps you stay well within the 200k token window of Claude 3.5 Sonnet.

Why is my Claude Code session getting slow?

Large numbers of loaded agents, skills, and MCP servers consume tokens in every turn. Context Budget identifies which components are causing this 'overhead bloat' so you can remove or optimize them.

What is the biggest source of context overhead?

MCP servers are often the largest contributors, as each tool's schema can consume approximately 500 tokens. Context Budget flags servers that could be replaced by simple CLI commands.

How does this skill estimate token usage?

It uses standardized heuristics, such as 1.3 tokens per word for prose and character-to-token ratios for code, specifically calibrated for Claude's model architecture.

Context Budget Optimizer

Name: Context Budget Optimizer
Author: affaan-m

byaffaan-m

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172,010

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생산성 및 워크플로

Audits and optimizes token usage across Claude Code components to improve performance and reclaim context space.

Context Budget is a specialized diagnostic tool for Claude Code that identifies token bloat across agents, skills, MCP servers, and project rules. By performing a multi-phase inventory and classification of every loaded component, it surfaces actionable recommendations to reduce overhead, prevent performance degradation, and maximize the available context window for actual coding tasks. It is essential for developers managing complex setups with numerous tools and custom instructions who want to ensure their AI assistant remains fast, responsive, and accurate.

주요 기능

01Prioritized optimization reports with estimated token savings

02MCP server overhead estimation and CLI-replacement suggestions

03172,010 GitHub stars

04Automated token consumption auditing for agents, skills, and rules

05Context headroom analysis for planning future tool expansions

06Detection of redundant components and bloated frontmatter descriptions

사용 사례

01Troubleshooting sluggish Claude Code sessions or declining output quality

02Auditing context overhead after adding multiple new MCP servers or skills

03Planning complex project setups to stay within the model's token window

주요 기능

01Prioritized optimization reports with estimated token savings

02MCP server overhead estimation and CLI-replacement suggestions

03172,010 GitHub stars

04Automated token consumption auditing for agents, skills, and rules

05Context headroom analysis for planning future tool expansions

06Detection of redundant components and bloated frontmatter descriptions

사용 사례

01Troubleshooting sluggish Claude Code sessions or declining output quality

02Auditing context overhead after adding multiple new MCP servers or skills

03Planning complex project setups to stay within the model's token window