context-budget

Manage context budgets with progressive disclosure and four-tier loading.

1|1|Updated Jan 25, 2026

Search Tags:#ai-agent #conversations #progressive-disclosure #context-management #token-budget #tiered-loading

Ready to run

npx skills add https://github.com/teslasoft-de/claude-skills-marketplace --skill context-budget

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: context-budget
Source: https://github.com/teslasoft-de/claude-skills-marketplace/tree/main/plugins/context-budget/skills/context-budget
Command: npx skills add https://github.com/teslasoft-de/claude-skills-marketplace --skill context-budget

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Context windows are limited in long conversations and complex code tasks. This skill provides a framework to manage that context efficiently by using progressive disclosure and tiered loading to keep the most relevant information in memory while evicting less critical data.

Core Features & Use Cases

Progressive disclosure: load deeper context only when it is needed for a task.
Tiered loading: maintain Core, Domain, and Task contexts with on-demand expansion to Full context.
Context budgeting: automatic eviction of low-priority context to stay within token and memory limits.
Integration-friendly: coordinates with other skills (e.g., /collab, /repomix) to preserve and restore state across tasks.
Use Case: large codebase reviews or multi-turn conversations where context can grow beyond limits.

Quick Start

Use Tier 1 core data for every session, load Tier 2 domain context when entering a project, load Tier 3 task context for active work, and evict Tier 4 data as the conversation evolves.

Frequently Asked Questions about context-budget

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

FAQPage Schema

How do I manage context windows for long AI agent conversations?▼

Manage context windows for long AI agent conversations by applying progressive disclosure and tiered loading. This framework maintains Core, Domain, and Task contexts, expanding to Full context only on-demand to keep relevant information in memory.

How does progressive disclosure handle token budget limits in multi-turn interactions?▼

Progressive disclosure handles token budget limits through automatic eviction of low-priority context. It evicts less critical data as conversations evolve, ensuring multi-turn interactions stay within memory limits while retaining active task data.

What is the best way to balance context and performance during large codebase reviews?▼

The best way to balance context and performance during large codebase reviews is using a four-tier context model. Load Tier 1 core data per session, Tier 2 domain context for projects, and Tier 3 task context for active work.

Does context management work with other skills to preserve state across tasks?▼

Context management works with other skills through integration hooks to preserve and restore state across tasks. It coordinates with external components to maintain context balance while switching between different workflows.

When do I need tiered loading for AI agent context management?▼

You need tiered loading for AI agent context management when context can grow beyond limits in complex code tasks. It is applicable to large codebases and multi-turn interactions where context must be balanced with performance.