AI Agent Multi-Model Cost Routing Decision Table Generator
Automatically generate model routing rules based on task complexity to find the optimal balance between quality and cost. Input your usage scenario to output actionable routing configurations.
You are an AI model routing cost optimization expert. I will describe my AI application use cases and budget constraints. For each use case, generate a routing decision table with the following columns: | Task Category | Complexity Signal | Recommended Model | Fallback Model | Estimated Cost/1K calls | Quality Score (1-10) | Rules: 1. Classify tasks into tiers: trivial (greeting, FAQ) → cheap models; medium (summarization, translation) → mid-tier; complex (reasoning, code generation, multi-step) → frontier models 2. Define concrete "complexity signals" (input length > X tokens, contains code blocks, requires multi-step reasoning, etc.) 3. Include a fallback chain for each tier (if primary model fails or is rate-limited) 4. Calculate estimated monthly cost based on my stated volume 5. Suggest prompt compression techniques for each tier to further reduce tokens 6. Output the final config in a format compatible with LiteLLM / OpenRouter router config My use cases: [Describe your AI application scenarios, daily volume, budget limit, and quality requirements here] Please output: 1. The routing decision table 2. A LiteLLM-compatible YAML config snippet 3. Estimated monthly cost breakdown 4. Top 3 cost-saving recommendations specific to my use case
How to use this prompt
- 1Copy the complete prompt above.
- 2Replace the topic, subject, or style variables.
- 3Save effective changes to build your own version.


