cf ai Classify

    2

    Fast, free image classification using ResNet-50 on Cloudflare Workers AI with 1,000+ object categories.

    $12

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    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+21 more

    cf-ai-classify

    Example session with this skill installed

    What is in golden_retriever.jpg? Please show me the top 4 predictions and confidence scores.

    • Read your context and instructions
    • Compiled the cf-ai-classify

    Classifying: golden_retriever.jpg

    Top predictions

    1. [##############################] 95.3% golden retriever
    2. [######################--------] 73.1% Labrador retriever
    3. [########----------------------] 27.4% dog
    4. [###---------------------------] 11.2% tennis ball

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

    About this skill

    What it does

    This skill provides high-performance image classification and object recognition by leveraging the Microsoft ResNet-50 model running on Cloudflare Workers AI. It allows your AI agent to "see" and categorize photos, identifying thousands of different classes including animals, vehicles, electronics, and scenes.

    Why use this skill

    Unlike general-purpose LLMs that may be slow or expensive for simple visual processing, this skill provides a specialized, lightweight solution. It is 100% free to use with a standard Cloudflare account, making it ideal for high-volume tasks that would otherwise drain your API credits. It returns structured confidence scores and ranked predictions, which are significantly more reliable for automation than unstructured text descriptions.

    Supported Features

    • Single & Batch Processing: Classify individual files or entire directories in one command.
    • Confidence Scoring: Get decimal-accurate probability scores for every identification.
    • Structured Output: Automatically saves results to JSON for easy parsing by other scripts or agents.
    • Extensive Vocabulary: Recognizes over 1,000 distinct ImageNet categories.

    The output is a clean, ranked list of the most likely objects or scenes detected in the image, accompanied by visual confidence bars for quick human or machine verification.

    • Limited to 1,000 ImageNet categories
    • Cloudflare API rate limits apply
    • No OCR or text detection support

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    Security scan passed 7 months ago

    Permissions

    Terminal / Shell
    Network Access
    Environment Variables
    Listed7 months ago

    What's inside

    Frequently Asked Questions

    This skill uses the ResNet-50 model on Cloudflare Workers AI to identify and categorize objects in images. It solves the problem of high API costs and slow processing speeds associated with using general-purpose LLMs for basic image recognition tasks.

    No, this skill is designed to run on Cloudflare Workers AI, which offers a generous free tier for standard accounts. This allows you to perform high-volume image classification without worrying about the per-token costs typical of other vision models.

    The skill returns a structured JSON output featuring a ranked list of the top categories identified, paired with decimal-accurate confidence scores. It is optimized for easy parsing by other automation scripts or downstream AI agent tasks.

    You will receive the complete skill configuration and worker script package ready for deployment. This includes full support for both single-image analysis and batch processing of entire directories.

    This skill is compatible with any AI agent framework that supports Cloudflare Workers integration or REST API calls. Because it outputs standardized JSON, it can be easily integrated into workflows using AutoGPT, LangChain, or custom-built agents.

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