Model Context Budgeting

AdvancedopsMinimum 16K context

Optimizes prompts and agent workflows for finite context windows by prioritizing evidence, compressing history, managing retrieval budgets, and measuring token-cost trade-offs.

context-engineeringllm-costpromptsoptimization

Use cases

  • Long-running agents
  • Prompt cost optimization
  • RAG context tuning

Example prompt

Optimize this agent context strategy. Allocate a token budget across instructions, history, retrieval, and tool output, then propose truncation and summarization rules.

Recommended models

claude-opus-4-6gpt-5gemini-2-5-pro

Compatible tools

claude-codecursorkiroany

Modalities

Input: text, code, file
→
Output: text, code

Related Skills

llm-cost-optimizerrag-pipeline-builder

Author

OpenModels Community

@openmodelsrun