higgsfield-product-photoshoot

Original：🇺🇸 English

Translated

Generate brand-quality product images via mode-specific prompt enhancement on Higgsfield's gpt_image_2 model. The single entry point for any professional brand visual involving a product. Use when: "make a product photo", "studio shot", "lifestyle photo", "in use", "Pinterest pin", "hero banner", "website header", "carousel", "Meta ads", "ad creatives", "model wearing", "virtual try-on", "person holding product", "closeup with hands", "levitating product", "floating", "splash shot", "CGI style", "surreal product", "restyle", "Christmas version", "in [aesthetic] style", or any request involving a product, brand, or paid social creative. Modes: product_shot, lifestyle_scene, closeup_product_with_person, pinterest_pin, hero_banner, social_carousel, ad_creative_pack, virtual_model_tryout, conceptual_product, restyle. Backend assembles the final prompt — never write gpt_image_2 prompts freehand. Always go through this skill. NOT for: raw text-to-image with no brand/product (use higgsfield-generate), branded marketing video with avatars (use higgsfield-generate's Marketing Studio), Soul Character training (use higgsfield-soul-id).

1.6kinstalls

Sourcehiggsfield-ai/skills

Added on2026-05-05

NPX Install

npx skill4agent add higgsfield-ai/skills higgsfield-product-photoshoot

SKILL.md Content

View Translation Comparison →

Product Photoshoot

Brand-image generation via the

higgsfield product-photoshoot create

command. The CLI calls a backend prompt enhancer that holds mode-specific photography vocabulary and structural templates, then submits to

gpt_image_2

and returns image URLs.

Step 0 — Bootstrap

Before any other command:

If

higgsfield

is not on

$PATH

, install it:

bash

curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh

If

higgsfield account status

fails with

Session expired

/

Not authenticated

, ask the user to run

higgsfield auth login

(interactive) and wait for confirmation.

UX Rules

Be concise. Print only image URLs in the final reply.
Detect language, respond in it. Mode names and CLI flags stay English.
Ask at most 4 short questions before submitting. Use labeled options, never open-ended.
Skip questions whose answer is obvious from context (uploaded image, prior turn, brand memory).
Never write the gpt_image_2 prompt yourself — backend assembles it.
Polling is silent. Wait until URLs are ready, then deliver.

Modes

Mode	When user wants…
`product_shot`	Product on neutral / studio / catalog background
`lifestyle_scene`	Product in real-world environment, hands, action, atmosphere
`closeup_product_with_person`	Tight crop with hands / partial face — beauty application, holding, demonstrating
`pinterest_pin`	Vertical 2:3 Pinterest-native aesthetic, moodboard feel
`hero_banner`	Wide-format website / email / campaign header
`social_carousel`	3–10 connected slides for IG / LinkedIn / Facebook
`ad_creative_pack`	Coordinated pack of static ad variants for Meta / TikTok / Pinterest / Google Ads
`virtual_model_tryout`	Product worn or used by an AI-rendered model
`conceptual_product`	Surreal / CGI-style / levitating / splash / sculptural product
`restyle`	Transform an existing image's aesthetic, mood, or seasonal context

Mode selection

Pick by intent, not surface keyword. When two modes could apply, prefer the more specific one.

product + neutral / clean / white / studio / catalog / Shopify →
```
product_shot
```
product + scene / in use / kitchen / outdoor / cafe / gym →
```
lifestyle_scene
```
hands holding / face with product / beauty application / demonstrating →
```
closeup_product_with_person
```
Pinterest, pin, vertical pin →
```
pinterest_pin
```
hero, banner, website header, landing page, email header, wide format →
```
hero_banner
```
carousel, slide post, multi-slide, swipeable →
```
social_carousel
```
ads, ad pack, paid social, Meta / TikTok / Pinterest ads →
```
ad_creative_pack
```
model wearing, virtual try-on, on body, fashion shoot, lookbook →
```
virtual_model_tryout
```
levitating, floating, splash, frozen motion, surreal, CGI, sculptural →
```
conceptual_product
```
modify EXISTING image's aesthetic, mood, season — without changing subject →
```
restyle
```

Tie-breakers:

"Pinterest pin of my product on a kitchen counter" →
```
pinterest_pin
```
(Pinterest is the platform)
"Hero banner showing my product in use" →
```
hero_banner
```
(banner format wins)
"Carousel of my product in different scenes" →
```
social_carousel
```
(multi-slide wins)
"Closeup of person applying my serum" →
```
closeup_product_with_person
```
(specific genre wins)

Pre-generation interview

Ask 3–4 short questions before submitting. Always labeled options, never open-ended. Skip a question whose answer is obvious from context.

Type A — uploaded a product photo, "make me images / photoshoots"

How many?
```
[1 / 3 / 5]
```

What style/mood?

[Clean studio / Lifestyle / Conceptual / With a model / Other]

Where will you use them?

[Shopify / Instagram / Pinterest / Paid ads / Website hero]

Brand colors to match? (skip if obvious)

Type B — uploaded a product photo, named a use case

E.g. "make ads for my product", "make a Pinterest pin", "make a hero banner". Mode is obvious. Ask only the gaps:

How many? (if multi-output mode)
What's the offer / mood / hook?
Anything in particular to emphasize?

Type C — text only, no product photo

Can you upload a product photo? (preferred — much higher fidelity)
If not, describe the product — category, packaging, color, distinctive features.
What style? (same options as Type A)
Where will you use it?

Type D — uploaded existing image, "redo / change vibe / different version"

→

restyle

What aesthetic?

[Clean girl / Cottagecore / Quiet luxury / Dark academia / Y2K / Other]

Seasonal context?

[Christmas / Valentine's / Halloween / Black Friday / None]

What to preserve, what to change? (only if ambiguous)

Type E — model wearing a product (fashion, accessories)

→

virtual_model_tryout

Model archetype? (suggest 2–3 based on brand audience)

Environment?

[Studio clean / Outdoor natural / Street style / Editorial / Home cozy]

Framing?

[Full body / Three-quarter / Waist up / Closeup on product area]

Type F — vague request, unclear subject

E.g. "make me something cool for my brand".

What product or topic?

Goal?

[Sell on a marketplace / Build awareness / Run paid ads / Update website]

Upload a reference image?

After answers → return to the relevant Type A–E.

Generation

Single command. Backend assembles the final prompt and submits to

gpt_image_2

. URLs print on stdout.

bash

higgsfield product-photoshoot create \
  --mode <mode> \
  --prompt "<short user-intent description from interview answers>" \
  [--image <path-or-upload-id>]... \
  [--count <1-10>] \
  [--aspect_ratio <override>]

Examples:

bash

higgsfield product-photoshoot create \
  --mode lifestyle_scene \
  --prompt "bottle of cold-brew on a sunlit kitchen counter, IG feed" \
  --image bottle.jpg \
  --count 3

bash

higgsfield product-photoshoot create \
  --mode pinterest_pin \
  --prompt "vertical pin for my candle brand, cottagecore mood" \
  --image candle.jpg

bash

higgsfield product-photoshoot create \
  --mode restyle \
  --prompt "Christmas version, quiet-luxury aesthetic" \
  --image existing-shot.jpg

Image inputs

--image

accepts a local file path (auto-uploaded) OR an existing upload UUID. Repeat the flag for multiple references.

Multi-variant

--count 3

returns 3 distinct image URLs. Backend asks the enhancer to vary preset, lighting, angle, and palette across variants — they will not be paraphrased copies of one another.

For

social_carousel

and

ad_creative_pack

, count = number of slides / variants in the pack. Backend locks the visual system across all slides automatically.

Aspect ratio

Backend picks a sensible default per mode. Override with

--aspect_ratio

only if the user explicitly asks for a different one. Allowed values:

1:1

,

4:5

,

5:4

,

3:4

,

4:3

,

2:3

,

3:2

,

9:16

,

16:9

.

Delivering results

Print the image URLs as a short bulleted list. No JSON, no IDs, no internal model names, no enhanced prompt text. If a job failed, mention it briefly with the failure status.

3 lifestyle shots ready:
- https://cdn.higgsfield.ai/.../job_abc.jpg
- https://cdn.higgsfield.ai/.../job_def.jpg
- https://cdn.higgsfield.ai/.../job_ghi.jpg

What this skill does NOT do

Does not write gpt_image_2 prompts directly. Backend owns prompt assembly.
Does not auto-pick a different image-gen model. Always
```
gpt_image_2
```
.
Does not replace
```
higgsfield-generate
```
Marketing Studio for branded video / avatar workflows.
Does not replace
```
higgsfield-generate
```
for raw text-to-image without a product or brand context.

Common mistakes to avoid

Asking more than 4 interview questions in a single message.
Picking the wrong mode (e.g.
```
product_shot
```
when the user wants a Pinterest pin).
Calling
```
higgsfield generate create gpt_image_2 --prompt ...
```
directly instead of
```
higgsfield product-photoshoot create
```
— bypasses the prompt enhancer and produces noticeably worse output.
Pasting the assembled prompt back to the user — they want the URLs.
Using a
```
--mode
```
value not in the table above.

higgsfield-product-photoshoot

NPX Install

Tags

SKILL.md Content

Product Photoshoot

Step 0 — Bootstrap

UX Rules

Modes

Mode selection

Pre-generation interview

Type A — uploaded a product photo, "make me images / photoshoots"

Type B — uploaded a product photo, named a use case

Type C — text only, no product photo

Type D — uploaded existing image, "redo / change vibe / different version"

Type E — model wearing a product (fashion, accessories)

Type F — vague request, unclear subject

Generation

Image inputs

Multi-variant

Aspect ratio

Delivering results

What this skill does NOT do

Common mistakes to avoid