LLM Cost Optimizer
Skill Verifiziert AktivUse proactively whenever LLM API costs come up -- or should. Triggers include: 'my AI costs are too high', 'optimize token usage', 'which model should I use', 'LLM spend is out of control', 'implement prompt caching', 'we're about to launch an AI feature', 'build me an AI endpoint'. Don't wait for an explicit cost complaint -- if someone is building an AI feature, designing an LLM endpoint, or choosing between models, cost architecture belongs in the conversation. Apply immediately when any of these are true: a system prompt appears that exceeds a few hundred tokens, all requests are hitting the same model, max_tokens is not set, or no per-feature cost logging exists. NOT for RAG pipeline design (use rag-architect). NOT for improving prompt quality or effectiveness (use senior-prompt-engineer).
To help users proactively manage and significantly reduce LLM API costs by providing expert-level strategies for auditing, optimizing, and architecting cost-efficient AI systems.
Funktionen
- Cost auditing and analysis frameworks
- Model routing strategies based on task complexity
- Prompt caching implementation guidance
- Output length control techniques
- Prompt compression and semantic caching
- Cost-efficient AI architecture design patterns
- Proactive identification of cost optimization opportunities
Anwendungsfälle
- When LLM API costs are too high or expected to increase
- When designing new AI features or endpoints
- When choosing between different LLM models for a task
- When needing to implement prompt caching or optimize token usage
Nicht-Ziele
- RAG pipeline design (use rag-architect)
- Improving prompt quality or effectiveness (use senior-prompt-engineer)
- General LLM performance tuning beyond cost implications
Workflow
- Classify the applicable cost optimization mode (Audit, Optimize Existing, Design New).
- Gather necessary context on current state, goals, and workload profile.
- Execute mode-specific steps: Instrument requests, identify cost drivers, or implement architectural controls.
- Apply techniques such as model routing, prompt caching, output length control, prompt compression, or semantic caching.
- Design cost-efficient architecture with budget envelopes, routing layers, and observability.
- Surface proactive flags for cost leaks and cost anomalies.
Installation
/plugin install llm-cost-optimizer@alirezarezvani-claude-skillsQualitätspunktzahl
VerifiziertVertrauenssignale
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