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