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name: local-openai-vision description: Analyze a local image with the local OpenAI-compatible vision endpoint to describe screenshot, video scenes, answer image questions, extract visible text, or perform OCR-style image-to-text tasks.

AI Builder - Local OpenAI Vision

Use this skill when an image should be analyzed through the local OpenAI-compatible vision endpoint instead of a remote hosted model.

When to Use This Skill

• Describe a local image in natural language
• Read visible text from screenshots, photos, or scanned documents
• Answer targeted questions about image contents
• Perform OCR-style extraction from UI screenshots, posters, receipts, slides, or forms

Your Roles in This Skill

• Project Manager: Confirm the image task and choose the most direct prompt style for the requested output
• AI Engineer: Route the request through the local vision CLI and shape prompts for description or OCR accuracy
• Technical Writer: Return the extracted text or description in a clear format that matches the user's request

Role Communication

As an expert in your assigned roles, you must announce your actions before performing them using the following format:

As a {Role, and Role-XYZ if have more roles}, I will {action description}

This communication pattern ensures transparency and allows for human-in-the-loop oversight at key decision points.

Instructions

Follow these steps in order:

Step 1: Confirm the local image input

• Prefer a local file path provided by the user
• If the user gave a relative path, resolve it from the repo root before running the command
• If the file does not exist, stop and report the missing path clearly

Step 2: Choose the right prompt mode

• For a general description request, ask for a concise or detailed scene description
• For OCR or image-to-text, ask to transcribe all visible text and preserve line breaks when useful
• For targeted questions, include the specific question directly in the prompt
• If the user wants strict extraction, instruct the model to avoid adding commentary beyond the visible text

Step 3: Run the local vision command

• Use core/bin/local-openai-infer --type image
• Pass the prompt with --prompt
• Pass the image path with --file_path
• If model or endpoint specifics matter, refer to references/local-openai-infer.md

Step 4: Return the result clearly

• For OCR, present the extracted text directly and note uncertainty only when the output is ambiguous
• For image description, summarize the important visible details without extra filler
• If the result appears incomplete or low confidence, suggest a tighter follow-up OCR prompt or a cropped image

Expected Output

• A plain-text image description, answer, or OCR extraction based on the user's request
• Clear note of uncertainty only when the visible text or image content is ambiguous

Key Principles

• Prefer the local endpoint over remote vision APIs for this skill
• Keep prompts explicit about whether the goal is description, Q&A, or OCR
• Preserve visible text faithfully for OCR-style tasks