[PROPOSAL] Cookbook: Reducing Token Costs with the Claude API — Practical Optimization Techniques

### Preflight Checklist

- [x] I have searched existing cookbooks and this topic isn't already covered
- [x] This proposal focuses on Claude API/SDK capabilities (not external frameworks)
- [x] I am prepared to implement this cookbook (or have a clear implementation plan)

### Problem Statement

Developers using Claude for production applications often face
unexpectedly high token costs, especially with long conversations,
large documents, and agentic workflows. Most developers don't know
practical techniques to reduce costs without sacrificing quality.
There is no existing cookbook that measures and demonstrates real
token savings with actual before/after cost calculations.

### Claude Capabilities Demonstrated

- Prompt caching (cache_control) for repeated context
- Token counting API (count_tokens) to measure before/after
- Model routing between Claude models based on task complexity
- Conversation summarization to compress long context windows
- Batch API for async workloads at 50% cost reduction

### Differentiation

No existing cookbook focuses specifically on cost optimization
with real measured numbers. This notebook will show developers
exactly how many tokens and dollars each technique saves across
different use cases — coding tasks, document summarization,
multi-turn conversations, and agentic workflows. Every technique
includes a before/after cost comparison using Claude's actual
pricing.

### Additional Context

This is directly relevant to production Claude deployments and
frontier model usage where token costs scale significantly.
The notebook will be fully runnable with a free Gemini API key
as fallback for users without Claude API access.