Context Optimization Skill

This skill provides methodologies and best practices for maximizing context window efficiency, reducing token costs, and improving the performance of LLM-based agentic workflows.

1. Prompt Cache Alignment

To maximize Key-Value (KV) cache hits, prioritize stability in the early parts of the prompt.

• Static Prefixes: Design system prompts to remain identical across agent turns.
• Tool Order: Sort tool definitions alphabetically or by frequency of use. Keep this ordering constant.
• Prefix Consistency: Reserve the top 70% of the KV cache for global system instructions and tool definitions.
• Avoid Dynamic Data: Move dynamic session-specific data (dates, current file list) to the end of the context window.

2. Semantic Pruning & AST Compaction

Reduce unnecessary data before sending it to the model.