Reduce LLM API costs and tokens
llm-cost-optimizerpluginsetup L2★17,464
alirezarezvani/claude-skills ↗What it does
Reduce LLM API costs and optimize token usage
Best for
Controlling LLM spend in production systems by routing between models, implementing caching, and observing token usage per feature
Inputs
- · current API spend data
- · model roster
- · prompt transcript
Outputs
- · cost reduction plan
- · model routing strategy
- · prompt caching config
- · cost observability setup
Requires
- · LLM provider APIs (Anthropic, OpenAI, etc.)
- · token counter
- · cost optimizer
Preconditions
Access to API billing data; at least one LLM-backed feature in production; team approval for model changes
Failure modes
Switching models introduces latency regressions users reject; prompt caching breaks for dynamic contexts; cost savings don't materialize at scale
Trust signals
- · Covers model routing by cost/quality
- · Prompt caching implementation included
- · Cost observability setup
- · v2.9.0 stable release