# Store Photoshoot > Use when turning a brand's whole online store (Shopify or WooCommerce) into a reusable Astria AI photoshoot — crawl the catalog, extract the brand's DNA, cast avatars, and build packs that re-shoot the entire collection (and every future drop) in the brand's own look. Trigger phrases — "build a photoshoot from my store", "crawl STORE_URL and make packs", "AI product photography for BRAND", "re-shoot our catalog". For a single lookbook/collection PAGE use `templatize-page` instead. - Skill: `astriaai/store-photoshoot` (Agent Skill) - Install (CLI): `npx skillmds@latest add astriaai/store-photoshoot` - Raw SKILL.md: https://api.skillmd.com/api/skills/astriaai/store-photoshoot/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: astriaai (https://skillmd.com/u/astriaai) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/astriaai/store-photoshoot --- # Store Photoshoot Builder Given a brand's storefront URL, crawl the shop, extract its brand DNA, and build a complete, reusable AI photoshoot system in an Astria workspace: a casting board of brand avatars (when on-model shots are needed), product reference tunes, and a set of **packs** (prompt templates) that can re-shoot the brand's entire catalog — and every future collection — in the brand's own visual language. All Astria operations go through the `astria` CLI (see the **astria-api** skill) — never raw API calls, never tokens in skill text. Scope every command with `-w `. Everything you register in Astria — faces, garments, shoes, jewels, poses, backgrounds, props, logo lockups — is a **single-image faceid reference tune** whose `name` is a controlled class noun (`woman`, `man`, `boy`, `girl`, `dress`, `shirt`, `pants`, `shoes`, `ring`, `necklace`, `chain`, `earrings`, `bracelet`, `pose`, `background`, `outfit`, `bottle`, …) and whose `title` is the human/SKU label. Prompts address them as `

` — the class noun immediately after the token is the routing mechanism that tells the model what to take from that reference. **Deliverable of a full run:** a workspace containing (1) a confirmed Brand DNA brief, (2) a 2–5 avatar casting board (on-model only), (3) product reference tunes, (4) one pack per item-type / outfit formula with a fixed shot battery, (5) a QA'd pilot render, then the scaled catalog, and (6) a workspace landing page. Related skills: **astria-api** (the CLI), **unique-headshot** (avatar casting), **prompt-writing** (prompt grammar & parameters), **packs-guide** (packs), **templatize-page** (silhouette/pose-swap technique, single page), **landing-page-editor** (the `/w/:slug` page). --- ## Phase 1 — Crawl the store **Detect the platform first**, then use its public JSON endpoints. Crawl politely: sequential requests, a normal browser User-Agent. **Shopify** — `{store}/products.json` returns JSON: ``` GET {store}/products.json?limit=250&page=N # loop N=1,2,3… until "products" is empty GET {store}/collections.json?limit=250 # collections + products_count GET {store}/collections/{handle}/products.json # per-collection membership GET {store}/pages.json?limit=100 # About / editorial / brand-story pages ``` Per product capture: `title`, `product_type`, `tags`, `vendor`, `body_html` (strip HTML), `variants[].price`, `images[].src` (CDN URLs — the tune training source), `options` (sizes → audience signal). **WooCommerce** — `{store}/products.json` returns the homepage, not JSON. Use the Store API instead: ``` GET {store}/wp-json/wc/store/v1/products?per_page=100&page=N # loop until empty GET {store}/wp-json/wc/store/v1/products/categories?per_page=100 ``` Per product: `id`, `name`, `sku`, `type` (`simple`|`variable`), `prices.price` (÷ 10^`currency_minor_unit`), `images[].src`, `categories[].name`, `variations`. Homepage `og:` meta and `/product-sitemap.xml` give the brand name, logo, and a full product-URL list if the Store API is disabled. **Fallbacks** — if JSON is gated (password/B2B): `{store}/sitemap.xml` → `sitemap_products_*.xml`, or ask the customer for a product-export CSV, or for direct image URLs. **Image audit (critical).** Download 20–40 product images across categories and *look at them* (actually view each image). Record, per category: shot style (on-model vs packshot vs flat-lay vs atmosphere); angle coverage (front/back/side/detail); the house background hex (sample corner pixels); model casting (age, gender mix, ethnicity, styling); lighting fingerprint (softbox-even vs flash vs daylight). The photoshoot you build must be recognizably *the same brand* — these observations become the pack defaults. Front+back product photos also decide which items can support back-view templates. ## Phase 2 — Extract the Brand DNA brief Synthesize a structured brief and **confirm it with the customer before building** — one round with your ask-user question tool (`AskUserQuestion` in Claude Code, `ask_user` in the Astria chat agent): brand read, shoot register, casting direction. Capture: - `brand`, `vertical` (fashion | footwear | jewelry | beauty | supplements | home-decor | mixed) - `categories`: product_type histogram → tune classes, SKU counts, back-photo availability - `sku_scale`: boutique(<100) | catalog(100–1K) | factory(1K–10K) | enterprise(10K+) - `audience`: gender (women/men/both/kids/family), age band (from sizes, copy, collection names), a **body-guard** line for prompts (see Phase 5) - `positioning`: mass/family | contemporary | premium | luxury — from price stats (median/max variant price) and About/collection copy tone - `aesthetic`: `background_hex` (from the image audit), lighting, brand comps - `shoot_plan`: which registers (Phase 3), how many avatars - `pilot_skus`: 8–15 products spanning the top categories **SKU scale drives the architecture:** boutique → hand-picked hero looks, richer editorial per look; catalog → pack-per-outfit-formula factory, `--create_crops` for detail shots, one avatar per pack; factory+ → hardened templates run as named batches (3 angles/look, per-colorway tunes) — prioritize best-sellers and the newest collection, never try to shoot the whole 10K in the pilot. ## Phase 3 — Choose the photoshoot registers A brand usually gets one primary register + one or two supporting. Ask the customer which they want as the lead when the vertical supports several (a single ask-user question). Avatars are cast **only** for on-model registers. | Vertical | Primary | Supporting | |---|---|---| | Fashion (garments) | Studio lookbook on-model (front/45°/back battery) | Ghost/3D packshots; location campaign | | Footwear | Product packshot 5-angle battery | On-model legs-down crops; atmosphere still-life | | Jewelry | Still-life on tactile surfaces + worn close-ups | Extreme macro; hand-model for rings | | Beauty (bottles/cremes/sprays) | Packshots on seamless + atmosphere (marble, stone, water, botanicals) | Texture macro; application close-ups | | Supplements | Clean packshots + kitchen/gym lifestyle | Ingredient still-life; hand-holding product | | Home decor | In-room styled atmosphere | Detail/texture macro; ghost packshot | ## Phase 4 — Create / target the workspace Use the customer's existing workspace when they name one (`astria workspaces list` → target with `-w `); otherwise create one named after the brand (via the workspace UI, or `astria api POST /workspaces` if available — confirm the id with `astria workspaces list`). Note the house background hex — every studio template pins it twice (in prose and via `--background_color`). Two-greys convention: packshots on `#F2F2F2` (luminance-flattened), on-model studio on `#F5F5F5`/`#e9e9e9`-family off-whites, luxury lookbooks on pure `#FFFFFF` + flash — unless the brand's own photography says otherwise. ## Phase 5 — Cast the avatars (on-model registers only) Avatars are synthetic faces generated from trait-dense prompts, **no reference tune** — the **unique-headshot** method. Generate with `astria generate --model recraft-4-1 --num-images 2 --aspect-ratio 1:1`, bare shoulders, hair pulled back, **no jewelry on the face ref** (critical for jewelry brands — earrings on a face ref contaminate every render), ≥1 unique distinguishing feature, never repeat an ethnicity in a batch. Match casting to the Brand DNA (audience age, ethnicity mix, positioning). Present a candidate board (ask-user question with thumbnails), then register each winner: ``` astria tunes create -w --title " — " --name woman|man|boy|girl --image-url ``` **Casting board size: 2–5 faces.** Production brands run one avatar per ethnicity and hold **one avatar constant across all shots of a pack** — consistency beats variety. Attach the brand's **body-guard** text (rides after the person token in every prompt): - kids/tween: `boy 1.30 high` / `girl 1.30 high`; toddler: `girl 1.5 yo toddler, proportional head` - womenswear luxury: `tall supermodel proportions, elongated legs, long neck, narrow waist` + `sleek, low, slicked-back bun` - menswear premium: `tall male supermodel proportions, elongated athletic body, broad shoulders narrow waist, masculine confident posture` - explicit age when relevant: `11 y o teen girl`, `teen 15 y o man` Footwear legs-down crops, pure packshot, and atmosphere plans skip avatars — the model (if any) is described verbally and the face is cropped out. ## Phase 6 — Ingest product references For each pilot SKU, create a faceid tune from the shop's CDN images: ``` astria tunes create -w --title "" --name \ --image-url [--image-url ] ``` - Map `product_type` → tune class with a controlled vocabulary. The class must be the *actual subject* — "jewelry" is a poor name; use `ring`/`necklace`/ `chain`/`earrings`. Rename + retrain if wrong (`astria tunes update --name ring`). - **Variant products (`type: variable`):** do NOT blindly take `images[0]` — it is often the wrong colorway/variant. Match the chosen image to the intended variant (or ingest one tune per variant). A mismatch trains a faithful render of the *wrong* product. - **Non-ASCII image URLs** (Hebrew/RTL/Cyrillic paths) must be **percent-encoded** before `--image-url`, or Astria returns HTTP 422 "could not download". - Prefer clean product-only images over on-model shots for garment fidelity. Include the back photo only when the battery has back views. One tune per colorway. Keep the SKU code in the title — it's the join key back to the shop. - Optionally register support tunes: a `background` set plate, `pose` refs (OpenPose skeletons or black product silhouettes — see **templatize-page**), brand `label`/`text` lockups for print fidelity, props (`chair`, `car`). ## Phase 7 — Author the packs (the core) **A pack = one item-type or outfit formula × a fixed shot battery.** Shot variety lives in the templates; per-SKU variety comes from swapping the reference tokens. Create with `astria packs create --title " — "` and author each template into the pack (see **astria-api** for pack-authoring). Iterate until the pilot passes QA. ### 7.1 House prompt grammar (studio lookbook) ``` woman shirt pants shoes [ background] plain background {HEX} softbox --background_color {HEX} [--create_crops 70] ``` - Weight is always `1.0`. - Free text after each garment's class noun does the **fit/layering** work: `shirt over size, sleeves reach just past the elbow, shirt out of the pants`, `front shirt half tucked inside the pants`, `pants cover the shoes`, `buttoned shirt worn open over the shirt, top two buttons open, untucked hem`, `pants reach the shoes, no socks visible`. - **Layer-visibility clauses** control partial garments: `visible hem of`, `visible waistband of`, `only the bottom hem is visible at the top of the frame`, `Absolutely no part of the dress fabric is visible` (for shoe macros). - **Fidelity guards** where reference photos are messy: `ignore back label`, `don't change the color of the pants`, `Use the outfit reference only for the clothing: garment shape, fabric, color, print, trims, sleeve length…`, `Model identity, face, body, hands, nails and hair come from the model reference`, plus a negative tail (`Avoid hair down, bangs, copied room background, rug, carpet, barefoot, missing shoes; no plastic skin, no beauty filter, no extra limbs`). - Params: **3:4, 4K, num_images 1** (2–4 for the hero front shot). Discover the default model with `astria models`. Detail shots come free via `--create_crops 66–72` (full frame + 2 crops) instead of separate prompts. ### 7.2 Shot batteries per item type Author one pack per formula the shop actually sells; each bullet = one template. - **Tops (shirt/polo/tee/sweater)** — front full · 35–45° front-side · back full · half-body front · waist/tuck detail · optional walking / left profile. - **Coat / jacket / blazer** — front closed · front open over inner top · 45° · back (highlight structure) · half-body back over-shoulder · collar/shoulder macro. - **Pants / jeans / shorts** — front · 45° · back · waistline crop · lower-half at 45° (`weight shifted to back leg, showcasing drape`) · walking. - **Dress / skirt** — front · 45° · back · walking/movement (`fabric swishes`) · half-body · fabric macro · optional seated. - **Footwear — packshots (no model):** strict side elevation (toe right, heel left, camera level with centerline) · straight-on front from low camera · rear three-quarter · overhead flat-lay · pair at 3/4 one shoe staggered · tight macro on stitching. Every template carries `no foot, no model, no extra objects, seamless light neutral grey studio background, realistic contact shadow beneath the product, natural scale, no compression or squashing` + `--background_color`. - **Footwear — on-model:** lower-half 45° · legs-down crop (`close shot from the knees down, always focus on the shoes`) · low-angle shoe close-up (`see only hem of pants above the footwear`) · seated with shoes in foreground. - **Bags & accessories** — 3-framing trio: front centered with negative space · three-quarter for depth · tight macro on hardware · plus one on-model hold/wear. Eyewear: `45 degree side-profile fully open, showing the temple arms` + front + worn close-up. - **Jewelry** — three families (1:1): *still life* on smooth white fabric / silk / matte stone / sculpted ceramic, `not a close-up, medium distance framing` for negative space; *worn close-ups* ` woman wearing earrings` with strict crops — necklace bust `upper chest and neck` or `cropped just below the eyes`; earrings `tight close-up, crop from ear to collarbone, side profile`; ring on a hand model (`hand resting on a stone tray beside an espresso`, always `manicured nails`); chain worn on bare chest/neck; *macro* 100mm. House stanza: `soft neutral-warm studio lighting, diffused directional light from front-side, very soft highlights, no yellow cast, balanced white tones, natural beige palette slightly warm but desaturated`. Rotate skin tone across templates. - **Beauty (cremes/bottles/sprays/lotions)** — *packshot* front label-centered · 45° · back (label legible — register a `label` text tune if type fidelity matters) · line family shot; *atmosphere* product on marble/travertine/wet stone with droplets · botanical styling · backlit translucency · texture macro (cream smear, spray mist); optional application close-ups (hands/cheek/collarbone, no face identity). Surfaces & lighting borrow the jewelry vocabulary (`no yellow cast` for golds/ambers). - **Supplements** — packshot battery + lifestyle atmosphere (morning kitchen with citrus and water; gym-bag still life; hand holding the jar label-forward) + ingredient flat-lay. - **Home decor** — in-room atmosphere (one coherent interior per collection, palette-matched) · straight-on packshot on seamless · texture/detail macro · scale shot with a human element (hand on ceramic, figure near the lamp — face optional). ### 7.3 Campaign register (hero content, optional) Not pack templates first — long-form prompts in the brand's language, promoted to a pack once a scene wins. Structure with labeled sections (`LOCATION / FOREGROUND / SUBJECT / BACKGROUND / CAMERA / LIGHTING / MOOD / STYLE`), one coherent location vocabulary per campaign (reuse the same scene description verbatim across the set; pin it with a `background`/`location` tune). Film/camera vocabulary is the realism lever matched to positioning: luxury `85mm, shallow depth of field, Kodak Portra 400 film grain`; street-cool `35mm, f/8, hard direct on-camera flash, ISO 400`; family-candid `soft diffused overcast daylight`. For premium work add an anti-CGI block (`visible pores, no smoothing, natural fabric behavior, imperfect drape, soft analog 35mm grain`). Formats 9:16 / 16:9, 4K, num_images 2–3. ### 7.4 Pose control ladder 1. **Text first** (default): terse angle line, escalate to full photographic paragraphs (weight distribution, gaze, camera height, 20–30° body angle) when stances drift. 2. **Skeleton pose tunes**: train OpenPose stick-figure renders as `pose` tunes (front / 45° / back), lead the prompt with ` pose`, refine verbally. 3. **Silhouette lock** (to clone the brand's *existing* photography stance-for- stance): threshold a real catalog photo to a black silhouette, register as `pose`, prompt `replace the pose … Keep the pose exactly as in the silhouette. Ignore the pose from the outfit.` (see **templatize-page**). ### 7.5 Video add-on (optional) - Runway loop per look: Seedance, 16:9, 8–9s, three timestamped beats — walk in from left → stop center & pose → walk past camera and exit; `Static camera, continuous motion, no cuts`. - Product turntable: one storyboard prompt, `slow smooth 360-degree rotation over 8 seconds`, per-second angle checkpoints, a negative block (`avoid fast spinning, deformation, extra objects, text, logo`). ## Phase 8 — Pilot, QA, scale 1. Render the pilot: each pack × 2–3 SKUs of its category, one avatar held constant per pack. Keep it modest (≤ ~40 images). 2. QA each render: garment/jewel shape·color·print fidelity; layering (tucks, hems, waistbands); face = avatar (no drift); background exactly the house hex; anatomy (hands, feet); no leaked artifacts (room backgrounds, mannequin stands, care labels); `no yellow cast` on golds; brand text/logos legible. 3. **Stop and get sign-off before scaling** — mass generation is real spend. Fix by tightening the responsible clause (add a guard or negative), not by rerolling blindly. If an item renders wrong repeatedly, inspect the tune's training images (bad crops / wrong class / wrong variant are the usual cause). 4. Scale in phases: best-sellers/newest first for sign-off, then the rest. Iterate over the crawled product list — `tunes create` per SKU, one generate per template with the SKU's tokens swapped in. Name batches (` BATCH1 LOOK 1–N`). 5. Post-production at volume: background-removal passes for cutouts, 16:9 recrops for banners, upscale passes for hero shots. ## Phase 9 — Landing page & handoff Generate the workspace landing page from the brief (see **landing-page-editor**): `astria landing set -w --brief ""`. Report to the customer: workspace link, the casting board, each pack (`/p/`) with its battery, pilot images, and the one-step instruction for future collections — *point us at the new products; the packs re-shoot the whole drop automatically.* --- ## Appendix — Style presets by positioning | Positioning | Background | Lighting | Body / styling | Suffix vocabulary | |---|---|---|---|---| | Kids / family mass | `#e9e9e9` softbox | even softbox, `small smile` | height guard, playful poses | clean e-com, `--create_crops` | | Contemporary basics | `#F5F5F5` seamless | soft studio light | natural relaxed stance | `Kodak film 400 grain` | | Premium menswear | `#E7E7E7` / light gray | professional fashion editorial lighting | tall supermodel proportions | quiet-luxury comps (`COS / ARKET… Minimal. Architectural. Retail-ready.`) | | Luxury womenswear | pure `#FFFFFF`, no floor | **direct on-camera flash** | sleek slicked-back bun, elongated legs | sharp e-commerce catalog image | | Street / cool | dark or night urban | hard flash, underexposed bg, ISO 400 grain | candid mid-stride, `not posing` | `by William Eggleston` / Tillmans | | Jewelry / beauty | cream-beige, tactile surfaces | soft neutral-warm, **no yellow cast** | manicured hands, rotated skin tones | quiet luxury product photography, 4K clarity | Keep the preset reasoning inside the Brand DNA brief — the customer confirms it once, and every template inherits it.