Works with the AI tools you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIGitHub CopilotGitHub CopilotGemini CLIGemini CLI+20 more

    💰 AI Cost Optimizer

    2

    An advanced FinOps engine to analyze AI usage, optimize token spend, and reduce LLM costs by up to 60%.

    $7

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    💰 AI Cost Optimizer

    💰 AI Cost Optimizer

    Example session with this skill installed

    Analyze my OpenAI usage export for March and suggest ways to cut costs without losing performance. My monthly spend is currently $14,000.

    • Read your context and instructions
    • Compiled the ai cost optimizer

    Potential Savings: $5,800/mo (41.4%).

    Top Actions

    1. Route 60% of tasks (extraction/summary) to GPT-4o-mini: saves $4,200.
    2. Implement Context Caching for repetitive system prompts: saves $850.
    3. Use Batch API for daily reporting tasks: saves $750.
      ROI: 15x. Payback: <1 month.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Audit monthly LLM usage exports for systematic token waste.Design an automated model-routing table based on task complexity.Calculate the ROI of implementing semantic caching for RAG systems.Identify processes suitable for OpenAI Batch API 50% discounts.

    About this skill

    What it does

    The AI Cost Optimizer is a specialized FinOps tool designed specifically for developers and agencies scaling AI applications. It performs deep analysis of token consumption, model selection strategies, and infrastructure overhead to identify systematic waste. By auditing usage data from providers like OpenAI, Anthropic, and Azure, it generates a structured optimization report with specific ROI calculations and a prioritized implementation roadmap.

    Why use this skill

    Relying on generic prompts or default model settings often leads to 40-60% budget waste. This skill is better than manual prompting because it applies a systematic engineering framework to your specific usage patterns. It identifies complex opportunities like semantic caching, batch processing utilization (50% discounts), and optimal model-task mapping that are easily missed during standard development.

    Key Features

    • Token Engineering: Audits system prompts and output lengths to trim inflation.
    • Model Routing: Maps tasks to the most cost-effective models (e.g., migrating classification from GPT-4o to 4o-mini).
    • Multi-Level Caching: Strategy designs for Redis, semantic, and session-based caching.
    • Batch Analysis: Identifies time-insensitive tasks eligible for 50% API discounts.
    • ROI Planning: Provides a 12-month savings forecast and payback period analysis.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

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    2. 2

      Unzip into your skills folder

      Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.

    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

    Skills folder by agent

    Click the path to copy it. Create the folder if it does not exist yet.

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    Recently published to Agensi

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    Trust & safety

    Security scanned

    Verified clean 3 months ago

    • Passed all security checks, Safe to install

    Listed3 months ago

    What's inside

    Frequently Asked Questions