Model Context Budgeting

advancedopsMin 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.

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

Compatible Tools

claude-codecursorkiroany

Modalities

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

Related Skills

Author

OpenModels Community

@openmodelsrun