vision

Vision — Local Image Querying via Ollama

Ask natural-language questions about images without passing them to the main agent as visual input. Useful for verifying screenshots, annotating assets, or building automated checks around visual output.

When to Use This Skill

• Describing a screenshot for a PR description or user-facing document
• Checking whether an automated browser run produced visible canvas content
• Asking "do any elements overlap?" on a rendered output
• Any question where the answer is in the pixels but you don't want to use vision tokens in the main context

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Quick Reference

All commands use uv run — dependencies are installed automatically.

SCRIPT=.agents/skills/vision/scripts/ask.py

# health check (fast, no image, confirms Ollama + model respond)
uv run $SCRIPT --ping

# system info — memory, storage, installed models
uv run $SCRIPT --info
uv run $SCRIPT --memory
uv run $SCRIPT --storage

# describe an image (default prompt)
uv run $SCRIPT path/to/image.png

# explicit shortcut
uv run $SCRIPT path/to/image.png describe

# custom question
uv run $SCRIPT path/to/image.png \
  --prompt "Do you see any overlapping UI elements?"

uv run $SCRIPT canvas.png \
  --prompt "Does this canvas contain any designed content, or is it empty?"

# optional: pin a specific Gemma 4 tag (default is any installed gemma4)
uv run $SCRIPT image.png --model gemma4:e4b

# list installed Gemma 4 vision models
uv run $SCRIPT --list-models

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Prerequisites

Ollama must be running locally. The script connects to http://localhost:11434 and fails immediately if it cannot reach it.

# start Ollama (if not already running)
ollama serve

# install Gemma 4 (multimodal — required for this skill)
ollama pull gemma4

The script does not install models. If Gemma 4 is not installed it prints the list of installed models and a pull suggestion, then exits.

uv is required to run the script (handles dependency installation automatically). No requirements.txt or manual pip install needed.