Higgsfield Product Photoshoot
Higgsfield AIOfficialPublished by Higgsfield AI
- Skill
- Content generator
- Automation and integrations
- MIT
- Medium risk
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The higgsfield-product-photoshoot skill provides a structured interface for generating product-focused visuals. It utilizes a backend prompt enhancer to apply mode-specific photography vocabulary and templates before submitting requests to the gpt_image_2 model. The skill manages the generation process through a series of predefined modes, such as lifestyle scenes, hero banners, and ad creative packs, ensuring that the generated output aligns with specific marketing and brand requirements.
What it does
- Generates product images based on user-provided product photos or descriptions.
- Supports multiple photography modes including studio shots, lifestyle scenes, and virtual model tryouts.
- Automates the assembly of prompts through a backend enhancer to ensure consistent visual output.
- Handles multi-variant generation for carousels and ad packs.
- Provides a pre-generation interview process to refine user intent and requirements.
- Delivers final image URLs directly to the user.
When to use it
- When you need to create product visuals for social media, websites, or advertising campaigns.
- When you require specific formats like hero banners, Pinterest pins, or social carousels.
- When you want to restyle existing product images with new seasonal or aesthetic themes.
- When you need to visualize a product in use, such as with a model or in a lifestyle setting.
Advantages
- Simplifies complex image generation tasks by using predefined modes.
- Ensures consistent visual style across multiple generated assets.
- Reduces user effort by automating prompt construction.
- Supports iterative refinement through a guided interview process.
Usage examples
- “Create 3 lifestyle shots of my coffee bottle on a kitchen counter.”
- The agent initiates the lifestyle_scene mode, gathers necessary details, and returns three distinct image URLs.
- “I need a Pinterest pin for my candle brand.”
- The agent selects the moodboard_pin mode and generates a vertical 2:3 image suitable for Pinterest.
- “Restyle this product image for a Christmas theme.”
- The agent uses the restyle mode to apply a holiday aesthetic to the provided image while preserving the product.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/higgsfield-ai/higgsfield-product-photoshoot/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip higgsfield-product-photoshoot.zip -d .agents/skills
Documentation by Higgsfield AI
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
higgsfieldis not on$PATH, install it:curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | shIf
higgsfield account statusfails withSession expired/Not authenticated, ask the user to runhiggsfield 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 |
moodboard_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_shotproduct + scene / in use / kitchen / outdoor / cafe / gym →
lifestyle_scenehands holding / face with product / beauty application / demonstrating →
closeup_product_with_personPinterest, pin, vertical pin →
moodboard_pinhero, banner, website header, landing page, email header, wide format →
hero_bannercarousel, slide post, multi-slide, swipeable →
social_carouselads, ad pack, paid social, Meta / TikTok / Pinterest ads →
ad_creative_packmodel wearing, virtual try-on, on body, fashion shoot, lookbook →
virtual_model_tryoutlevitating, floating, splash, frozen motion, surreal, CGI, sculptural →
conceptual_productmodify EXISTING image's aesthetic, mood, season — without changing subject →
restyle
Tie-breakers:
"Pinterest pin of my product on a kitchen counter" →
moodboard_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.
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:
higgsfield product-photoshoot create \
--mode lifestyle_scene \
--prompt "bottle of cold-brew on a sunlit kitchen counter, IG feed" \
--image bottle.jpg \
--count 3higgsfield product-photoshoot create \
--mode moodboard_pin \
--prompt "vertical pin for my candle brand, cottagecore mood" \
--image candle.jpghiggsfield product-photoshoot create \
--mode restyle \
--prompt "Christmas version, quiet-luxury aesthetic" \
--image existing-shot.jpgImage 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.
Resolution
Use 2k for every product-photoshoot job.
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.jpgWhat 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-generateMarketing Studio for branded video / avatar workflows.Does not replace
higgsfield-generatefor 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_shotwhen the user wants a Pinterest pin).Calling
higgsfield generate create gpt_image_2 --prompt ...directly instead ofhiggsfield 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
--modevalue not in the table above.
Files
- ATTRIBUTION.mdAdded by AutoGineer898 B
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md9.2 KiB
SKILL.md
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
higgsfieldis not on$PATH, install it:curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | shIf
higgsfield account statusfails withSession expired/Not authenticated, ask the user to runhiggsfield 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 |
moodboard_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_shotproduct + scene / in use / kitchen / outdoor / cafe / gym →
lifestyle_scenehands holding / face with product / beauty application / demonstrating →
closeup_product_with_personPinterest, pin, vertical pin →
moodboard_pinhero, banner, website header, landing page, email header, wide format →
hero_bannercarousel, slide post, multi-slide, swipeable →
social_carouselads, ad pack, paid social, Meta / TikTok / Pinterest ads →
ad_creative_packmodel wearing, virtual try-on, on body, fashion shoot, lookbook →
virtual_model_tryoutlevitating, floating, splash, frozen motion, surreal, CGI, sculptural →
conceptual_productmodify EXISTING image's aesthetic, mood, season — without changing subject →
restyle
Tie-breakers:
"Pinterest pin of my product on a kitchen counter" →
moodboard_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.
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:
higgsfield product-photoshoot create \
--mode lifestyle_scene \
--prompt "bottle of cold-brew on a sunlit kitchen counter, IG feed" \
--image bottle.jpg \
--count 3higgsfield product-photoshoot create \
--mode moodboard_pin \
--prompt "vertical pin for my candle brand, cottagecore mood" \
--image candle.jpghiggsfield product-photoshoot create \
--mode restyle \
--prompt "Christmas version, quiet-luxury aesthetic" \
--image existing-shot.jpgImage 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.
Resolution
Use 2k for every product-photoshoot job.
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.jpgWhat 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-generateMarketing Studio for branded video / avatar workflows.Does not replace
higgsfield-generatefor 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_shotwhen the user wants a Pinterest pin).Calling
higgsfield generate create gpt_image_2 --prompt ...directly instead ofhiggsfield 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
--modevalue not in the table above.
Requirements and compatibility
Written for: Claude Code
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Declares allowed tools, Claude Code frontmatter, Needs network access
Security
What our scanner noticed· Medium risk
- Instructions that use the network
- Downloads piped into a shell
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- Higgsfield AI
- Publisher
- Higgsfield AI (Official)
- Source
- higgsfield-ai/skills · higgsfield-product-photoshoot · commit 2700040
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Higgsfield AI or Higgsfield AI.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download higgsfield-product-photoshoot.zip