image-analysis

name	image-analysis
description	Analyze, describe, or answer questions about image content using vision AI. Use this skill when the user asks anything about an image — what it shows, what's in it, reading text/diagrams, identifying objects, or any question referencing a previous image (e.g. 'what is in this image', 'read the text in this screenshot', 'explain this diagram', 'tell me about the image above', '识别图片', '分析图片内容').

Image Analysis Skill

Analyze images via LLM provider's chat completions API with vision.

When to Use

Trigger this skill when the user asks to:

• Describe or analyze an image ("describe this image", "what's in this picture")
• Recognize content in an image ("识别图片", "分析图片内容")
• Extract text from an image (OCR) ("read the text in this screenshot")
• Answer questions about an image ("how many people are in this photo", "what color is the car")
• Reference a previous image ("tell me about the image above", "what's in the previous picture")
• Explain visual content ("explain this diagram", "what does this chart show")
• Identify objects ("what kind of plant is this", "identify this")

Steps

Step 1: Identify the image

Get the image from the user's message or workspace context.

• If the user provides a local file path, use it directly.
• If the user provides an image URL (http/https), ask the user whether they'd like to download the image to a local file first, then download it (e.g. with curl -sL "<url>" -o /tmp/image_to_analyze.<ext>) before proceeding.
• If the user references a previous image without a path (e.g. "the above image", "the image I just sent"), search the workspace directory for recent image files:
  1. List files in the workspace matching common image extensions (*.png, *.jpg, *.jpeg, *.gif, *.webp, *.bmp)
  2. Sort by modification time (most recent first)
  3. Use the most recent image. If there are multiple candidates and it's ambiguous, ask the user which image they mean.

Step 2: Run the image analysis script

bash scripts/analyze_image.sh "<image_path>" "<question or prompt>"

The script reads API credentials and model from sudoclaw.json via the SUDOCLAW_CONFIG_PATH env var (auto-set at gateway startup). No manual env var configuration is needed.

The script prints the analysis result (LLM response) on success, or an error message on failure.

Step 3: Show the result

Display the analysis result to the user.