image-deep-research
Skill7 starsChanged 12 days agoMITView on GitHub
Image deep research and visual research - use when a question is better answered by looking than by reading. Finds reference images on open, licensed collections (Openverse, Wikimedia Commons, the Art Institute of Chicago, the Met), renders real websites into screenshot contact sheets, builds a moodboard, measures a live site's palette and typefaces, and reads every picture as a picture. For design references, styles, palettes, typefaces, materials, competitors and moodboards.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- ridelink0/image-deep-researchword for word, first seen Sep 25, 2026
Other versions1 project uses a version of this.
Word for word · 1
- ridelink0/image-deep-research★ 0100% same
Edited · 0
None found.
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository11 other files it gives its agents.
- AGENTS.mdAGENTS.md
- claude-dashboardsSkill
- claude-motionSkill
- deep-researchSkill
- link-previewSkill
- remotion-videoSkill
- sound-designSkill
- terminal-uiSkill
- ui-pro-maxSkill
- ultimate-frontend-skillsSkill
- visual-researchSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 3 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 112
When that file is not there, this is the standalone plugin: skip this section and find sites through the galleries above.
- Distinctive: line 126
Every image you recommend with its verified URL, creator, licence and source page.
- Distinctive: line 134
Do not describe an image you have not opened.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Image deep research
Most design questions are answered by looking at twenty examples, not by reading one article about them. This skill gets the pictures in front of you cheaply, checks that they are real, keeps the licence beside every one, and then makes you read them before you say anything about them.
The request is whatever the user typed with the skill. If it is empty, ask one question: what should be looked at.
Where the scripts are
The scripts live in scripts/ next to this file. In Claude Code that folder
is ${CLAUDE_SKILL_DIR}/scripts. In Codex, or anywhere that variable comes
through empty, use the scripts folder beside this SKILL.md. They need Node 22
or newer and nothing else; rendering needs Chrome, Edge or Chromium (set
IDR_BROWSER to the executable if it is somewhere unusual). The browser runs
headless and never opens a window.
The loop
Deep research here means rounds, not one search:
- Write the question down in a form a picture can answer. "What do luxury watch sites look like" produces mush; "what ground colour, what headline size, and what the first screen shows on six luxury watch sites" produces numbers you can build with.
- Gather from the two sources below: real sites for how a thing is done on the web, open collections for subjects, palettes, materials and art.
- Read the contact sheets, then only the two or three individual images
worth a closer look. A sheet of eight costs one read instead of eight.
In a coding session or for a first look, add
--compactto either script: one sheet of up to 16 numbered tiles, 1288x812 and at most 1,334 image tokens on any Claude model, one text line per result or site, no URLs (images.mjs --pick 3,7 --results <path>prints the ones you keep). Open a single image only for what the sheet and the numbers cannot answer. - Refine and go again. The first round tells you the right words: the name of the style, the photographer, the typeface, the movement. Search again with them. Stop when a new round stops changing the answer.
- Report (see the end of this file).
Render real sites - the highest-signal source
node "${CLAUDE_SKILL_DIR}/scripts/study.mjs" <url> <url> ...
node "${CLAUDE_SKILL_DIR}/scripts/study.mjs" --list editorialEach site is rendered in a headless browser at the top and one screen down
(--scroll 0,900, --width 390 for phones, --reduced-motion for comparison), tiled into contact sheets
eight to a sheet, and measured: ground colours by element area (overlaps can count twice), text
colours by amount of text, and the heading and body typefaces as the browser
computed them. The measurements print per site and land in report.json
beside the sheets. Curated lists: editorial, object, cinema, product.
Shots record viewport, scroll, time and motion preference; stills do not prove motion.
Two things it cannot see, and it says so rather than guessing: a page that
answers with a bot challenge or Access Denied, or renders next to nothing (a
preloader, an empty script shell), is reported as a wall with the reason and
kept off the sheet; and a canvas-heavy page is flagged, because its
screenshot may be a preloader frame. For those, try the y900
tile, a longer --wait 8000, or a video walkthrough of the site.
Find images on open collections
node "${CLAUDE_SKILL_DIR}/scripts/images.mjs" "<query>" --sheet
node "${CLAUDE_SKILL_DIR}/scripts/images.mjs" "<query>" --commercial --download --sources openverse,commonsSearches Openverse (Creative Commons and public-domain images from Flickr,
museums and more), Wikimedia Commons, the Art Institute of Chicago (public
domain works only) and the Met (Open Access works only). No keys. Every result
URL is fetched before it is reported, and one that does not answer with an
image is marked FAIL and never put on the moodboard. --commercial keeps only
licences that allow commercial use and changes (it drops NC and ND). --sheet
tiles the verified images into a numbered moodboard; --download saves them.
Results, with title, creator, licence, licence URL and source page, go to
results.json.
URL checks cover headers, not rights. Sheets cache bounded rasters; read source licences.
Unsplash and Pexels need a free key for their APIs; with one, their CDN URLs can be used directly. Check them the same way: an image URL is not a result until it has answered with an image.
Design galleries, for finding sites worth rendering
Awwwards, Godly, Land-book, SiteInspire, Minimal Gallery, Curated.design,
One Page Love. Fetch the gallery page, pull out the outbound site URLs, then
render them with study.mjs. A gallery's own thumbnails are small and
colour-shifted: render the real site instead.
Inside Ultimate Frontend Skills
This skill also ships inside the Ultimate Frontend Skills plugin. When
${CLAUDE_PLUGIN_ROOT}/scripts/webdesign.mjs exists (in Codex: a
scripts/webdesign.mjs in the plugin folder that holds .codex-plugin/),
there is a corpus of award-winning sites to pick references from by
technique:
node "${CLAUDE_PLUGIN_ROOT}/scripts/webdesign.mjs" awards "<topic>" --verbose
node "${CLAUDE_PLUGIN_ROOT}/scripts/webdesign.mjs" study --awards "<topic>" --n 6When that file is not there, this is the standalone plugin: skip this section and find sites through the galleries above.
Reading what you got
Go in with the question from step 1. Worth extracting every time: the type
pairing and sizes, the ground colours, where the accent appears, section
rhythm, what the first screen does, and the one move you have not seen before.
The report.json numbers are what the browser computed; the sheet is what a
person sees. Use both, and say which one a claim comes from.
Report
- The file paths of the contact sheets and the moodboard.
- Every image you recommend with its verified URL, creator, licence and source page. Nothing without a licence goes in a deliverable.
- Per reference, the one concrete move worth taking, with the number (a colour, a size, a spacing) when there is one.
- What could not be seen (walls, preloaders, failed URLs), said plainly.
Do not
Do not describe an image you have not opened. Do not treat a gallery thumbnail as evidence of colour. Do not conclude a site uses a library because the effect looks like it - check the bundle. Do not ship an image whose licence you have not read, and do not drop the attribution a CC BY licence requires.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

