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GitHub Skill

llm-token-optimization

See the main LLM Cost Optimization skill for comprehensive coverage of token economics and optimization strategies.

AmnadTaowsoam☆ 0 Repository stars0 Repository forks

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

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Skill instructions

LLM Token Optimization

This skill is covered in detail in the main LLM Cost Optimization skill.

Please refer to: 42-cost-engineering/llm-cost-optimization/SKILL.md

That skill covers:

  • LLM pricing models (OpenAI, Anthropic, Google, Cohere)
  • Token economics (input vs output tokens)
  • Cost optimization strategies (model routing, prompt engineering, caching)
  • Embedding and vector database costs
  • RAG system cost breakdown
  • Cost monitoring and attribution
  • Budget controls and rate limiting
  • Open-source model hosting trade-offs
  • Tools for AI FinOps (Helicone, LangSmith, LiteLLM)
  • Real-world case studies

Related Skills

  • 42-cost-engineering/llm-cost-optimization (Main skill)
  • 44-ai-governance/model-risk-management
  • 42-cost-engineering/cost-observability

Examples

Read the usage examples in the source repository.

View source ↗

Source history

Indexed on
2026-01-20
Index updated
2026-01-26
Branch
main

Index and sync dates describe this directory. View the source repository for code history.

GitHub ↗

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