OpenRouter Context Optimization Overview OpenRouter models have varying context windows (4K to 1M+ tokens). Since pricing is per-token, stuffing unnecessary context wastes money and can degrade output quality. This skill covers context window lookup, token estimation, conversation trimming, chunking strategies, and Anthropic prompt caching for large contexts. Query Context Limits Context-Aware Model Selection Conversation Trimming Chunking for Large Documents Prompt Caching for Repeated Context Error Handling | Error | Cause | Fix | |-------|-------|-----| | 400 | Input + max tokens model lim…