Find Me A Museum Image

Find me a museum image

Search museum open-access APIs for public-domain (CC0) artwork, preview candidates visually, and download a high-resolution image into the user's project with attribution — all from the CLI.

The tool is scripts/museum_image.py inside this skill's directory — the directory containing this SKILL.md. Since your working directory is the user's project, call it by absolute path; ` below means this skill's directory. Python 3, stdlib only. Museums that work with no API key: artic (Art Institute of Chicago), met (The Met), cleveland (Cleveland Museum of Art), smk (Statens Museum for Kunst, Denmark), rijks (Rijksmuseum), getty (J. Paul Getty Museum). With a free key in an env var: smithsonian (SMITHSONIANAPIKEY`).

Workflow

1. Turn the request into search terms

Distill what the user actually needs:

• Subject/mood: "calm sea", "sunflowers", "storm", "city at night". Museum search is keyword-based — search concrete nouns and artist names, not vibes. Translate "something serene for a meditation app" into searches like "calm sea", "water lilies", "quiet landscape", or artist names (monet, hammershoi, hiroshige).
• Orientation: a hero/banner wants --orientation landscape; a mobile splash wants portrait.
• Usage context: where in the project will it go? This decides the output path and how picky to be about palette.

Run 2–4 different queries rather than one — museum metadata is sparse, and synonyms surface different works.

2. Search with thumbnails

python3 /scripts/museum_image.py search "water lilies" \
  --orientation landscape --limit 6 \
  --save /results.json --thumbs /thumbs

Replace ` with your session's scratchpad directory (or any temp dir) — these are working files, not project files. --limit is per museum, so --limit 6 can return ~35 results across the six keyless museums; 4–6 is a good range. Give each query its own files (results2.json, thumbs2/) — thumbnail names restart at 00 every run, so reusing a thumbs dir mixes artworks from different queries. Results are numbered; thumbnails land as NNmuseum.jpg`.

3. Curate visually — this is the key step

Read the downloaded thumbnail images (the Read tool renders them). Judge them against the user's actual need: palette, mood, composition, whether text would overlay legibly. Metadata cannot tell you a painting is muddy brown; your eyes can. Discard weak candidates and, if nothing sings, run another query with different terms before settling.

4. Present a shortlist

Show the user the best 2–4 candidates: title, artist, date, museum, dimensions, and the museum page URL. If the user asked you to just pick one, pick the best match and say why.

5. Download at full resolution

python3 /scripts/museum_image.py download /results.json 3 \
  --out assets/hero.jpg

This fetches the highest practical resolution (Cleveland's multi-hundred-MB native TIFF is deliberately skipped; its URL is in the results JSON as full_tiff_url if anyone truly wants it) and writes an *.attribution.json sidecar next to it (title, artist, museum, license, source URL). Put the image where the project keeps static assets (public/, assets/, static/ — check first). Full-res museum scans can be 5–50 MB; if the project needs a smaller file, resize a copy (e.g. sips -Z 2400 out.jpg on macOS) but keep the sidecar accurate.

6. Attribution

CC0/public-domain images require no credit, but crediting is good practice. Offer the user the suggested credit line the download prints, e.g.:

> Claude Monet, "Low Tide at Pourville" (1882). The Cleveland Museum of Art. Public Domain (CC0).

If the image goes on a public page, suggest a caption or an HTML comment near the asset reference.

Sharp edges

• Trust the license field, not assumptions. The script already filters to public-domain/CC0 works, but if you fetch museum data by hand, check the rights field before using an image — most museums also serve copyrighted works through the same APIs.
• The Met search is the slowest (it needs one request per candidate object), and its image index is stale — a search can return hits whose objects turn out non-PD or imageless, so Met sometimes contributes fewer results than other museums. Normal, not a bug.
• If a museum errors or times out, the search continues without it — warnings go to stderr. Don't treat a single museum failure as a task failure.
• --orientation filters on known dimensions: artic, cleveland, smk, rijks, and getty report real pixel dims; met uses the artwork's physical proportions as a proxy; smithsonian rows pass through unfiltered. A stderr note tells you how many results dodged the filter — confirm those from their thumbnails.
• Jurisdiction caveat: museum public-domain labels follow US rules (published before ~1930). A 1929 Picasso etching can be CC0 at a US museum yet still copyrighted in life+70 countries. For a user shipping to an international audience, prefer artists who died 70+ years ago — when in doubt, mention it.
• Empty results usually mean the query is too specific. Broaden it ("impressionist coast" → "coast"), try an artist name, or drop --orientation (works with unknown dimensions are never filtered out, but known-wrong ones are).
• Rijksmuseum has no free-text search — the script queries its creator and title fields, so subject words work poorly there; artist names work well. Titles come back in Dutch.
• SMK's search is fuzzy: "monet" matches the Danish island "Møn" (SMK owns no Monet). Judge SMK hits by their thumbnails, not by faith in the keyword match.
• Getty search results omit medium/dimensions — that's why those columns are sometimes blank for getty rows.
• Smithsonian needs a free instant key from https://api.data.gov/signup/ (SMITHSONIAN_API_KEY). Only mention it if the user wants that collection; six museums already work with no key.
• More API detail (endpoints, field maps, image URL recipes, verified gotchas) lives in references/apis.md if you need to query a museum directly — including a recipe for National Gallery of Art, which has no live search API but does have an open IIIF server.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: stevysmith
• Source: stevysmith/find-me-a-museum-image-skill
• License: MIT

Install and usage instructions live in the source repository linked above.