CLIP Image-Text Understanding
Classify, search and match images using plain-language descriptions, with no training needed
- Repository
- Orchestra-Research/AI-Research-SKILLs
- Stars
- 14,195
- Licence
- MIT
- Files
- 2 files
What it does
This skill teaches an AI agent how to use OpenAI's CLIP model, which links pictures and words. Once installed, the agent can label an image by describing possible categories in plain language, score how well an image matches a sentence, or build a simple semantic image search over a folder of pictures. It also includes a sketch for storing the resulting embeddings in a vector database. The agent writes and runs Python code for these tasks rather than just describing them.
Great for
- Developers prototyping image search or tagging without collecting labelled training data
- Data or content teams sorting large photo libraries by broad categories
- Students learning how vision-language models work through runnable examples
Skip it if
- Safety-critical content moderation or legal decisions: the skill itself notes CLIP is a broad-category tool, and zero-shot labels can be wrong or biased
- Fine-grained recognition, counting, or locating objects: the file lists these as weak points and says it gives no bounding boxes
- Non-technical users without Python and a machine able to run PyTorch, since the agent needs to execute code to be useful
Try asking
- “Sort these 500 product photos into dog, cat, bird and car categories without training a model”
- “Build a semantic search that finds images matching 'a sunset over the ocean' in my photo folder”
- “Score how well each of these captions matches its image”
- “Check a folder of images for a few content categories and report the most likely label for each”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 2 original files, the MIT licence and an attribution note.
clip.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip clip.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip clip.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- Use descriptive, specific labels such as 'a photo of a dog on grass' rather than single words, since the file says vague labels perform poorly
- Start with the default ViT-B/32 model and only move to larger models if accuracy is insufficient
- Review the install step before letting the agent run it, because it pulls and executes code from GitHub and downloads model weights
What's inside
- references/applications.md
- SKILL.md
Redistributed unmodified from Orchestra-Research/AI-Research-SKILLs under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.