hermoso-product-photoshoot

hermoso-product-photoshoot is a skill for Claude Code, Cursor from hermoso-ai/hermoso. It costs 105 tokens per session (654 once invoked), scanned A, original, MIT.

A product-photography workflow that places a real product photo into studio, lifestyle, or wide hero-banner scenes. Reference-image compositing keeps the product's packaging, label, colours, and shape accurate.

In plain words
What is it for?
Use it to create studio product shots, in-use lifestyle images, hero banners, or several social-carousel scenes from a product image.
Why use it?
It avoids relying on a generated substitute that could change important product details.

Skill for Claude CodeCursor

Written for Claude Code and Cursor: allowed-tools in frontmatter, but also shipped in a Cursor plugin.

Part of the hermoso plugin — 4 skills, 1 MCP server shipped together

Good fit Use it to create studio product shots, in-use lifestyle images, hero banners, or several social-carousel scenes from a product image.

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Install with agentmods
npx agentmods add skills/hermoso-ai/hermoso/hermoso-product-photoshoot
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add hermoso-ai/hermoso --skill hermoso-product-photoshoot
Clone the repo
git clone --depth 1 https://github.com/hermoso-ai/hermoso

Made for: Claude Code, Cursor.

Or install hermoso, the plugin that ships this one along with the rest of its 4 skills, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for hermoso-product-photoshoot

README.md
[![agentmods](https://agentmods.dev/badge/skills/hermoso-ai/hermoso/hermoso-product-photoshoot/github.svg)](https://agentmods.dev/skills/hermoso-ai/hermoso/hermoso-product-photoshoot)
Your own site
<a href="https://agentmods.dev/skills/hermoso-ai/hermoso/hermoso-product-photoshoot"><img src="https://agentmods.dev/badge/skills/hermoso-ai/hermoso/hermoso-product-photoshoot/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for hermoso-product-photoshoot

Your own site · 80×15
<a href="https://agentmods.dev/skills/hermoso-ai/hermoso/hermoso-product-photoshoot"><img src="https://agentmods.dev/badge/skills/hermoso-ai/hermoso/hermoso-product-photoshoot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 105 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 654 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00105 $0.00654
Opus 5 $0.00053 $0.00327
Sonnet 5 $0.00021 $0.00131
Haiku 4.5 $0.00011 $0.00065

Measured 12d ago against content hash 45a978af01d0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

hermoso-product-photoshoot scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/hermoso-product-photoshoot/SKILL.md · 36 lines

What it actually says

Hermoso — product photoshoot

Use Hermoso's reference-image compositing so the real product (label, colours, shape) is preserved while the scene around it is generated. Drive the Hermoso CLI.

Setup

  • hermoso auth login (opens your browser once; nothing to paste). On a machine with no browser: hermoso auth login --token <your key>, using a key from the app under MCP & CLI.; run hermoso capabilities once to see image model ids + recipes. No account at all? An agent can sign itself up on a paid plan with POST /v1/signup at app.hermoso.ai, no browser needed; see the Hermoso README.

Procedure

  1. Get the product image path/URL from the user. This is the --ref — it forces product-accurate compositing.
  2. Pick a mode and write the prompt accordingly (compose for ads — off-center hero, depth, directional light, negative space for copy):
    • product_shot — clean studio packshot on a seamless backdrop.
    • lifestyle_scene — the product in a real in-use setting (kitchen, desk, outdoors).
    • hero_banner — wide banner composition with room for a headline.
    • social_carousel — several angles/scenes of the same product (run the command N times with varied prompts).
    • ad_creative_pack — a few finished ad images with on-image copy.
  3. Render: hermoso generate image --prompt "<scene + composition + any on-image text>" --ref <product image> [--model <id>] [--aspect 1:1|4:5|16:9]
    • Prefer the ★best image model for hero work; a faster model is fine for bulk variations.
  4. For a pack, loop: vary the scene/angle/aspect per call, collect the URLs, and present them together.
  5. Report each served image URL; offer to hermoso fetch them to disk or to tweak a scene.

Notes

  • Keep the product as the hero; never let generated text garble the real label — describe the product as "the exact product in the reference, label unchanged."
  • --ref takes a local path (read + sent) or a URL.
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 36 lines · 105 tokens per session scan A 45a978af01d0

Subscribe to this mod's changes

hermoso-product-photoshoot is a skill published in the GitHub repository hermoso-ai/hermoso (0 stars, last pushed today), licensed MIT. It adds 105 tokens to every session and 654 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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