Deep strategic research engine — decomposes questions into parallel research threads, spawns multiple agents, and synthesizes into actionable strategic analysis
日本語の概要は準備中です。原文の説明を表示しています。
Source authentic, high-res PUBLIC-DOMAIN artwork from museum open-access APIs (Met, Cleveland, SMK, Rijksmuseum, NGA, Art Institute of Chicago, Getty, Smithsonian) instead of AI-generated or generic-stock imagery. The default move whenever a visual needs an aesthetic, credible image (blog heroes, decks, social cards, essay/spec figures). Verified keyless recipes + licensing rules inside.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Standing rule (adopted 2026-07-24, from Eric Li's post on museum open-access): whenever a visual needs a real image with aesthetic weight, source public-domain museum artwork first - over AI-generated imagery and over generic stock. Curated, historically significant art reads as credible and sophisticated; AI-gen reads as slop. This stacks with, and reinforces, the
no-ai-slopskill and your house image style. It does NOT replace the generativeeditorial-illustrationsskill (that owns claim-driven diagrams/figures) or your house chart style - use museum art for photographic/hero/decorative/mood imagery, generative figures for data and concept diagrams.
api.artic.edu) is fine, but the image host www.artic.edu/iiif/... 403s scripted/curl fetches via a Cloudflare bot challenge. Use the JSON metadata from AIC, but download the actual image through a real/headless browser (browser-harness) or prefer a different museum for the image bytes.Fetch fresh per need. Do NOT build a reusable local pool of downloaded images to draw from. A small cached set gets reused everywhere and becomes the new "same stock photo on every post" - sameness is a form of slop, and the variety of a huge open collection is the entire point. Fetching is keyless and sub-second, so there is no cost reason to cache pixels.
references/ already are.assets/, a deck's media) once chosen - for provenance and offline builds. That is an artifact asset, never a shared library other artifacts pull from.https://collectionapi.metmuseum.org/public/collection/v1/ - no key, 80 req/s, CC0 where isPublicDomain:true.GET /search?q=<term>&hasImages=true&isPublicDomain=true -> {total, objectIDs[]}GET /objects/{id} -> read primaryImage (full-res JPEG, static, no IIIF hop) or primaryImageSmall (web-large).https://collectionapi.metmuseum.org/public/collection/v1/search?q=sunflowers&hasImages=true&isPublicDomain=truehttps://openaccess-api.clevelandart.org/api/artworks/ - no key, CC0.GET /api/artworks/?cc0=1&has_image=1&limit=10 (add &q=monet, &skip=10).images.web.url (900px), images.print.url (3400px JPEG), images.full.url (archival TIFF). Directly downloadable from openaccess-cdn.clevelandart.org.share_license_status == "CC0" per result.https://api.smk.dk/api/v1 - no key. License: Public Domain Mark 1.0 (functionally CC0).GET /art/search?keys=*&filters=[public_domain:true]&filters=[has_image:true]image_native directly from each result (no chain).filters as a repeated query param, one [field:value] bracket each. Concatenating filters=[public_domain:true][has_image:true] returns 200 but silently ignores the second condition.https://data.rijksmuseum.nl/search/collection (Linked Art, no key).GET /search/collection?type=painting&imageAvailable=true -> walk object -> VisualItem -> DigitalObject -> access_point[0].id is a ready IIIF URL.https://raw.githubusercontent.com/NationalGalleryOfArt/opendata/main/data/published_images.csv - filter openaccess=1.https://api.nga.gov/iiif/{uuid}/full/full/0/default.jpgopenaccess=0 rows are NOT open (resolution-capped, rights-restricted). Only openaccess=1 is free.GET https://api.artic.edu/api/v1/artworks/search?query[term][is_public_domain]=true&fields=id,title,image_id - no key, CC0.https://www.artic.edu/iiif/2/{image_id}/full/843,/0/default.jpg - but Cloudflare 403s scripted fetches; download via browser or use another museum for bytes.https://data.getty.edu/museum/collection/ - no key. No keyword search; use SPARQL with ?obj crm:P138i_has_representation ?img which returns a ready IIIF image URL in the same query.api.data.gov key; DEMO_KEY works at 30 req/hr): GET https://api.si.edu/openaccess/api/v1.0/search?q=<term> AND online_media_type:Images&api_key=KEY; CC0; check media[].usage.access=="CC0" per image. Extremely broad (SAAM, NPG portraits, Freer/Sackler Asian, Cooper Hewitt design).https://commons.wikimedia.org/w/api.php?action=query&generator=search&gsrsearch=<term>&gsrnamespace=6&prop=imageinfo&iiprop=url|extmetadata; license per file in extmetadata.LicenseShortName; raw bytes via Special:FilePath/{filename}.https://api.wellcomecollection.org/catalogue/v2/works?query=<term>; CC0/PD medical/scientific/historical imagery.https://archive.org/advancedsearch.php?q=<term>&fl[]=identifier&output=json; PD book illustrations, engravings, historical photos, ephemera.https://api.europeana.eu/record/v2/search.json?wskey=<KEY>&query=<term>; 50M+ items across European institutions.https://api.harvardartmuseums.org/object?apikey=<KEY>&q=<term>.https://lux.collections.yale.edu/api/search/...; strong British art + rare books.parismuseescollections.paris.fr / opendata.paris.fr; French painting/decorative arts.https://api.repository.library.nyc/...; PD prints, maps, photos, illustrations.https://api.dp.la/v2/items?q=<term>&api_key=<KEY>; federated US collections.openaccess=1).references/_synthesis.md (cheat-sheet) + one file per museum (met.md, cleveland.md, smk.md, rijksmuseum.md, nga.md, artic.md, getty.md, smithsonian.md) with live-tested example URLs, field maps, and gotchas.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Deep strategic research engine — decomposes questions into parallel research threads, spawns multiple agents, and synthesizes into actionable strategic analysis
日本語の概要は準備中です。原文の説明を表示しています。
Quick capture of raw thoughts with intelligent domain classification and competitive intelligence extraction
日本語の概要は準備中です。原文の説明を表示しています。
Run one task through the V-model verification loop: CP-2 plan → CP-3 build → CP-3v component verify → CP-4 integration verify (full lane) → CP-5 acceptance. The worker never grades its own homework; evidence rows trace back to AC-n. Opt-in: invoke with /closed-loop or by asking for the closed loop, proper verification, or an evidence trail. Ordinary work does not run this.
日本語の概要は準備中です。原文の説明を表示しています。
Deep-dive 7-day analysis across all data sources for weekly reviews, board prep, and strategic planning
日本語の概要は準備中です。原文の説明を表示しています。
Autonomous content pipeline - scout announcements in your field, triage by trend momentum and personal angle, produce posts/blogs/videos in your voice with ledger-based dedup, hard volume caps, and screenshot-verified publishing
日本語の概要は準備中です。原文の説明を表示しています。
Create user stories with duplicate checking across any project tracker (Linear, GitHub Issues, Jira)
日本語の概要は準備中です。原文の説明を表示しています。