Agent skill

Magic Hour Product Visuals

by hashgraph-online in hashgraph-online/awesome-codex-plugins

Create or edit a Magic Hour product image with controlled composition, geometry, branding and copy space.

MITAuto-check passedSales & Support

Install Magic Hour Product Visuals

skills CLI
$ npx skills add hashgraph-online/awesome-codex-plugins --skill magic-hour-product-visuals -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install hashgraph-online/awesome-codex-plugins magic-hour-product-visuals --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/magichourhq/skills/skills/magic-hour-product-visuals .claude/skills/magic-hour-product-visuals && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
magic-hour-product-visuals
GitHub stars
1.3k
Token cost
~1.4k tokens
SKILL.md length
748 words
Files
5 (incl. references)
Skills in repo
716
Repo updated
First seen
Licence
MIT

At a glance

Create or edit a Magic Hour product image with controlled composition, geometry, branding and copy space.

  • Works in 7 steps: intended image type and aspect ratio → one product with material, shape, color,… → exact composition and space allocation → …
  • Packaging and ecommerce visuals when Magic Hour is requested
  • SKILL.md covers Define the deliverable, Choose generation or editing, Write a production brief and Inspect before delivery
  • Reaches mcp.magichour.ai

What it does

Magic Hour Product Visuals is an agent skill from hashgraph-online/awesome-codex-plugins. Create or edit a Magic Hour product image with controlled composition, geometry, branding and copy space. Use for product shots, hero images, packaging and ecommerce visuals when Magic Hour is requested or is the project's chosen media provider.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `agents/openai.yaml`, `references/photoshoot.md` and `references/setup.md`).

It sits in Sales & Support, covering E-commerce operations. The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is MIT.

When your agent uses it

  • Packaging and ecommerce visuals when Magic Hour is requested
  • Is the projects chosen media provider

Example prompts

  • “/magic-hour-product-visuals”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. intended image type and aspect ratio
  2. one product with material, shape, color, and orientation
  3. exact composition and space allocation
  4. lighting, surface, background, shadow, and reflection
  5. required label, logo, or text in quotation marks
  6. elements that must remain fixed
  7. concrete rejection conditions

What it can do on your machine

Read from SKILL.md and the folder at commit 3e1456a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • mcp.magichour.ai

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Magic Hour Product Visuals loads about 1.4k tokens when it runs, and up to ~2.6k if it reads all its reference files. Until then it costs about 68 tokens; SKILL.md has 748 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~68
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from hashgraph-online/awesome-codex-plugins at commit 3e1456a, republished under its MIT licence (© hashgraph-online). 748 words, ~1,390 tokens.

Download SKILL.mdSave it as .claude/skills/magic-hour-product-visuals/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
magic-hour-product-visuals
description
Create or edit a Magic Hour product image with controlled composition, geometry, branding and copy space. Use for product shots, hero images, packaging and ecommerce visuals when Magic Hour is requested or is the project's chosen media provider.
license
MIT
metadata.author
magichourhq
metadata.version
1.3.0

Magic Hour product visuals

Deliver a product image that fits its intended placement and preserves the details that make the product recognizable. Treat a project ID as an intermediate result and inspect the finished image before calling it complete.

Generation consumes Magic Hour credits. Use a connected Magic Hour creation MCP at https://mcp.magichour.ai/ when available. Otherwise read references/setup.md. Discover the current schema before choosing a model, resolution, image count, or cost.

Infer the treatment from the customer's intended use; recommend one direction instead of asking them to choose technical parameters. Honor existing budget and delegated creative decisions, inspect intermediate results yourself and continue unless the user requested draft approval. Show the finished image first; retain technical records with the project. For catalog, lifestyle, detail, in-hand or coordinated sets, read reference photoshoot.

Define the deliverable

Extract or infer:

  • where the image will appear, such as a product page, ad, marketplace listing, or website hero
  • aspect ratio, resolution, crop tolerance, and required negative space
  • product shape, material, finish, color, label, logo, and exact text
  • camera angle, scale in frame, surface, background, lighting, and shadow
  • details that must remain unchanged
  • visible failures that make the image unusable

For a hero, specify which side needs empty space for copy. For an ecommerce listing, keep the full product inside the frame with a clean silhouette. When exact product identity, packaging, or branding matters, use an authorized reference and edit it rather than recreating it from text.

Choose generation or editing

  • With no source image, call ai_image_generator_create_image.
  • With a usable source that needs a new setting, cleanup, relighting, repositioning, or other controlled change, call ai_image_editor_create_image.
  • AI Image Editor requires an input image. Never route a prompt-only creation request to it.

Use one image at a resolution that reveals the product's critical details and fits its placement. A low-resolution preview is useful for composition, not final label fidelity. Check cost against existing authorization and ask only when it does not cover the intended work. Prefer the live recommended model for a general request and choose a specialist only when the current schema describes the needed behavior.

Write a production brief

Write the prompt in this order:

  1. intended image type and aspect ratio
  2. one product with material, shape, color, and orientation
  3. exact composition and space allocation
  4. lighting, surface, background, shadow, and reflection
  5. required label, logo, or text in quotation marks
  6. elements that must remain fixed
  7. concrete rejection conditions

Use direct visual language. A useful pattern is:

Premium 16:9 product hero photograph. One [product] in the right third, fully visible, with clean negative space across the left 40 percent. [Camera and material]. [Lighting, surface, and background]. Preserve [shape, colors, logo, and exact label]. No extra objects, duplicate text, warped geometry, unintended marks, or watermark.

For editing, describe the change first and then state what remains unchanged. Compare against the original reference, not just the prompt: a prettier bottle with a different cap or viewpoint is still a failed preservation edit. Do not stack unrelated styles or ask one image to show several scenes. Keep promotional copy in a separate layout layer when a suitable tool is available; preserve text already printed on the product.

Show full SKILL.md (216 more words)Show less

Inspect before delivery

Wait for the existing image project with wait_for_image_project. After it reports complete, use the exact returned download URL and inspect the actual output for:

  • actual downloaded dimensions, aspect ratio, crop, product scale, and requested negative space; do not trust the requested ratio alone
  • straight edges, plausible materials, and coherent reflections and shadows
  • accurate product geometry, cap, handle, controls, packaging, and colors
  • one correct instance of required text or logo
  • no misspelling, duplicate label, invented brand-like mark, or distracting object; disclose any service watermark and do not promise an unwatermarked file without checking eligibility
  • no anatomy or identity problem when a person is intentionally present

If the result fails, change the smallest useful variable. Use AI Image Editor for a localized correction when the rest of the image is strong; regenerate when composition or product identity is fundamentally wrong. Another generation spends credits, so stay inside the user's authorized budget.

When the product image will become video, accept the still first and use the image-to-video skill when installed. Otherwise discover image_to_video_create_video, pass the accepted image, prompt for motion, retain the ID, wait and inspect the complete clip. Do not require another skill installation to finish a supported request. Return the finished artifact, its saved location and any material limitation; retain project IDs for recovery.

© hashgraph-online, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references) in plugins/magichourhq/skills/skills/magic-hour-product-visuals of hashgraph-online/awesome-codex-plugins.

  • SKILL.md
  • LICENSE.txt
  • agents/openai.yaml
  • references/photoshoot.md
  • references/setup.md

Open the folder on GitHubat commit 3e1456a

Compare with similar skills

Magic Hour Product Visuals next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Magic Hour Product Visuals compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Magic Hour Product Visuals this skillhashgraph-online/awesome-codex-plugins1.3k—~1.4kAutomated safety check: PassMIT
Amazon Buy Box Monitorbrowser-act/skills6.1k1 repos~1.6kAutomated safety check: PassMIT
Tourmind Bookingtourmind-com/Tourmind-Booking-Skills1.8k—~13kAutomated safety check: PassMIT
Ecommerce Image Suitewzj177/ecommerce-image-suite449—~10kAutomated safety check: PassApache-2.0
Zach Feature Demand Validatorzach22-1999/amazon-skills2091 repos~2.3kAutomated safety check: NotesMIT
Caramel CouponsDevinoSolutions/caramel141—~1.1kAutomated safety check: PassAGPL-3.0

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Categories

Questions about Magic Hour Product Visuals

What does Magic Hour Product Visuals do?

Create or edit a Magic Hour product image with controlled composition, geometry, branding and copy space. Magic Hour Product Visuals is an agent skill from hashgraph-online/awesome-codex-plugins. Create or edit a Magic Hour product image with controlled composition, geometry, branding and copy space.

When should I use Magic Hour Product Visuals?

Magic Hour Product Visuals fits situations like: packaging and ecommerce visuals when Magic Hour is requested; is the projects chosen media provider.

How do I install Magic Hour Product Visuals in Claude Code?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill magic-hour-product-visuals -a claude-code`. Or copy the skill folder (plugins/magichourhq/skills/skills/magic-hour-product-visuals in hashgraph-online/awesome-codex-plugins) into .claude/skills/magic-hour-product-visuals in your project. Claude Code loads it when a task matches its description.

How do I install Magic Hour Product Visuals in Codex?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill magic-hour-product-visuals -a codex`. Or copy the skill folder (plugins/magichourhq/skills/skills/magic-hour-product-visuals in hashgraph-online/awesome-codex-plugins) into .agents/skills/magic-hour-product-visuals in your project. Codex loads it when a task matches its description.

Can I use Magic Hour Product Visuals in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hashgraph-online/awesome-codex-plugins --skill magic-hour-product-visuals -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/magic-hour-product-visuals, .gemini/skills/magic-hour-product-visuals, .github/skills/magic-hour-product-visuals and .opencode/skills/magic-hour-product-visuals in your project.

What does Magic Hour Product Visuals need to run?

SKILL.md names no scripts, command-line tools or credentials: Magic Hour Product Visuals is instructions for the agent only.

Does Magic Hour Product Visuals access the network?

SKILL.md names 1 domain. In commands or code: mcp.magichour.ai; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Magic Hour Product Visuals safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Magic Hour Product Visuals use?

Magic Hour Product Visuals is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Magic Hour Product Visuals use?

About 1.4k tokens (SKILL.md is roughly 5.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.2k tokens, read only when the agent opens those files.

What are the alternatives to Magic Hour Product Visuals?

Skills that share tags, products or a category with Magic Hour Product Visuals: Amazon Buy Box Monitor (browser-act/skills, 6.1k stars), Tourmind Booking (tourmind-com/Tourmind-Booking-Skills, 1.8k stars), Ecommerce Image Suite (wzj177/ecommerce-image-suite, 449 stars) and Zach Feature Demand Validator (zach22-1999/amazon-skills, 209 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Magic Hour Product Visuals?

hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,267 GitHub stars. The repository holds 716 skills in this directory. The repository was last updated on October 10, 2026.

Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.