Анализ затрат на AI и план оптимизации

★ 6.9 · marketing

ai-cost-optimization is a Claude Code skill that delivers a structured AI cost analysis and optimization plan with actionable, measurable outcomes. It follows a four-step process: context gathering by reading memory.md and knowledge-base.md, framework selection from AI Readiness Assessment, Automation ROI Calculator, and Human-in-the-Loop Design, generating specific recommendations, and a checklist-based quality validation pass. Key output metrics include Time Saved Per Task, Automation Rate, Error Reduction %, Cost Per AI Operation, and User Adoption Rate. The resulting document covers structured analysis, a prioritized implementation table, a risk matrix, and next steps. It suits teams looking to justify automation investments with concrete numbers, reduce AI operational costs, and establish a repeatable quality control process for AI-generated outputs.