Agent skill

Art Direct

by divinevideo in divinevideo/divine-mobile

Art direction for any content — reads text, PDF, Word, HTML, PPT, then proposes 2-3 creative directions with photography style, mood, and visual language.

MITAuto-check passedDocuments & Office

Install Art Direct

skills CLI
$ npx skills add divinevideo/divine-mobile --skill art-direct -a claude-code

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

GitHub CLI
$ gh skill install divinevideo/divine-mobile art-direct --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/divinevideo/divine-mobile.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/art-direct .claude/skills/art-direct && 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
art-direct
GitHub stars
266
Token cost
~4.8k tokens
SKILL.md length
1,712 words
Files
6
Skills in repo
103
Repo updated
First seen
Licence
MIT

At a glance

Art direction for any content — reads text, PDF, Word, HTML, PPT, then proposes 2-3 creative directions with photography style, mood, and visual language.

  • Works in 4 steps: Content Ingestion & Analysis → Creative Direction Proposals → Visual Style Guide → …
  • The user shares content and needs visual direction
  • SKILL.md covers When to Use, Supported Inputs, The Workflow and Stage 1: Content Ingestion &…, plus 8 more sections
  • Calls curl and python3; reaches queue.fal.run; needs FAL_API_KEY

What it does

Art Direct is an agent skill from divinevideo/divine-mobile. Art direction for any content — reads text, PDF, Word, HTML, PPT, then proposes 2-3 creative directions with photography style, mood, and visual language. After selection, generates AI image prompts and visual briefs section-by-section. Use when the user shares content and needs visual direction, image sourcing, or creative direction for any material.

Its SKILL.md is about 4.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files (for example `README.md`, `docs/2026-01-28-art-direct-design.md` and `styles/bold-minimalism.yaml`).

It sits in Documents & Office, covering Image generation. The licence is MIT.

When your agent uses it

  • The user shares content and needs visual direction
  • Creative direction for any material

Example prompts

  • “/art-direct”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Content Ingestion & Analysis
  2. Creative Direction Proposals
  3. Visual Style Guide
  4. Section-by-Section Execution

What it can do on your machine

Read from SKILL.md and the folder at commit 6487b05. 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

    Shell commands in SKILL.md call:

    • curl
    • python3

    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:

    • queue.fal.run

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • FAL_API_KEY

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

Context cost

Art Direct loads about 4.8k tokens when it runs. Until then it costs about 91 tokens; SKILL.md has 1,712 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~91
When it runs · the whole SKILL.md, loaded when a task matches
~4.8k

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 divinevideo/divine-mobile at commit 6487b05, republished under its MIT licence (© divinevideo). 1,712 words, ~4,821 tokens.

Download SKILL.mdSave it as .claude/skills/art-direct/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
art-direct
description
Art direction for any content — reads text, PDF, Word, HTML, PPT, then proposes 2-3 creative directions with photography style, mood, and visual language. After selection, generates AI image prompts and visual briefs section-by-section. Use when the user shares content and needs visual direction, image sourcing, or creative direction for any material.

Art Direct

Turn content into visual direction. Point this at anything — a deck, a document, an essay, a brief, a webpage — and get back a creative direction you can actually execute.

When to Use

  • User shares a file (any format) and needs visuals for it
  • Developing visual identity for content before building/designing
  • Translating written material into photography/illustration direction
  • Creating image prompts for AI generation tools
  • Art directing a presentation, document, report, or website
  • Reviewing existing visuals against content intent (critique mode)

Supported Inputs

Read content from whatever the user provides:

FormatHow to read
.txt, .mdRead tool directly
.htmlRead tool, strip tags to extract text + structure
.pdfRead tool with pages parameter
.docxExtract via python3 -c "import docx; ..." or textutil -convert txt on macOS
.pptxExtract via python3 -c "from pptx import Presentation; ..."
.rtftextutil -convert txt on macOS
URLWebFetch tool

If a format doesn't extract cleanly, ask the user to paste the text.

The Workflow

INGEST CONTENT → ANALYSE → PROPOSE 2-3 DIRECTIONS → USER SELECTS → VISUAL BRIEF + PROMPTS

Stage 1: Content Ingestion & Analysis

Read the full content. Extract:

  1. Structure — What are the units? (slides, sections, chapters, paragraphs, pages)
  2. Core themes — The 2-3 big ideas the content is actually about
  3. Narrative arc — Does it build? Contrast? Layer? List?
  4. Audience — Who receives this? What do they expect to see?
  5. Tone — Authoritative? Inspirational? Intimate? Provocative? Technical?
  6. Key moments — Which sections carry the most weight, demand the strongest visuals?
  7. Existing visual language — If the content already has images, assess what's working and what isn't

Output a brief content summary before proceeding. Keep it tight — this is for alignment, not a book report.


Stage 2: Creative Direction Proposals

If house style template provided (--style <name>):

  • Validate content fits the style
  • Note any tensions and how to bridge them
  • Skip to Stage 3 with adapted style guide

If no house style:

Propose 2-3 distinct visual directions. Each must be genuinely different — not three shades of the same idea. For each:

DIRECTION: [Name — a short handle like "Archival Authority" or "Warm Machinery"]

MOOD
What it feels like: [emotional quality in 2-3 words]
Energy: [calm / dynamic / tense / contemplative / electric]

PHOTOGRAPHY STYLE
Type: [documentary / editorial / conceptual / abstract / archival / illustrative]
Subjects: [what appears in the images]
Lighting: [quality of light]
Color treatment: [warm/cool shift, saturation, film stock reference]
Composition: [framing approach]

REFERENCE TOUCHSTONES
"Think [X] meets [Y]" — cite real publications, campaigns, photographers, or brands

WHAT THIS DIRECTION AVOIDS
[Specific clichés and visual tropes this direction rejects]

WHY THIS FITS THE CONTENT
[1-2 sentences connecting direction to content themes]

Present all directions. User picks one (or asks for a hybrid). Lock the choice.


Stage 3: Visual Style Guide

Once direction is selected, output the working style guide:

VISUAL STYLE GUIDE: [Content Title]
Direction: [Chosen direction]

PHOTOGRAPHY STYLE
─────────────────
Type: [Documentary / Editorial / Conceptual / Abstract / Archival]
Subjects: [What to feature — specific, not generic]
Composition: [Framing rules]
Lighting: [Light quality]
Color treatment: [Color approach, film stock if relevant]

MOOD & TONE
───────────
Primary emotion: [e.g., quiet confidence]
Supporting emotions: [e.g., warmth, precision]
Energy level: [Calm / Dynamic / Tense / Contemplative]

CONSISTENCY RULES
─────────────────
• [Shared quality all images must have]
• [Human subject guidelines]
• [Color palette anchors — hex codes]
• [Aspect ratio defaults]

CLICHÉ BLACKLIST
────────────────
• [Content-specific images to reject]
• [Generic tropes to avoid]
• [Overused metaphors for these themes]

AI GENERATION DEFAULTS
──────────────────────
Photography suffix: [standard prompt additions for photo-style generation]
Illustration suffix: [standard prompt additions for illustration-style generation]

Stage 4: Section-by-Section Execution

Work through the content in its natural units (slides, sections, chapters, key passages). For each:

Step 1: Interpret the section's job

What must the visual communicate? What's the emotional beat?

Step 2: Apply the Five-Lens Framework

Generate options through five lenses:

LensWhat it showsWhen to use
LiteralThe thing itself, shot with intentionContent is already specific
HumanPeople experiencing or doing itNeed emotional connection
EnvironmentalSetting, atmosphere, textureSetting mood, transitions
MetaphoricalConcrete visual analogyMaking abstract tangible
ObliqueAbstract, unexpected angleProvoking thought, standing out
Step 3: Output the Visual Brief

For the recommended lens (guided by the style guide's lens preferences), output:

SECTION: "[Section title or key line]"
VISUAL JOB: [What this image must do]
LENS: [Which lens and why]

CONCEPT
[2-3 sentence description of the exact image — specific enough
that a photographer could shoot it or a designer could find it]

AI GENERATION PROMPTS
─────────────────────
MIDJOURNEY:
[Full prompt with style suffixes, --ar, --v, --style flags]

DALL-E / GPT IMAGE:
[Natural language prompt optimized for DALL-E]

GEMINI:
[Prompt formatted for Gemini image generation]

IDEOGRAM:
[Prompt formatted for Ideogram, especially for any text-in-image needs]

SOURCING GUIDANCE
─────────────────
If searching (not generating):
  Search: [2-3 specific, refined search queries]
  Where: [Specific sources — see Source Guide below]
  Avoid: [What will come up that you should skip]

ALTERNATIVES
────────────
[1-2 other lens options briefly described, in case the primary doesn't land]
Step 4: For content with many sections

Don't generate all sections unprompted. Output:

  1. The first 2-3 sections as examples
  2. A summary table of all remaining sections with recommended lens and one-line concept
  3. Ask which sections to develop fully

The Five-Lens Framework (Detail)

For any concept, five ways to see it:

Lens"Digital transformation""Supply chain resilience"
LiteralServer room corridor, blinking LEDsCargo ship cutting through rough seas
HumanDeveloper's face lit by dual monitors at 2amDockworker's hands checking manifest in rain
EnvironmentalEmpty office at dawn, single laptop glowingFog lifting off container yard at sunrise
MetaphoricalOld film projector casting light on blank wallSpider web holding dew drops — tension + beauty
ObliqueChild's hand drawing a robotDominos frozen mid-fall, one glowing

The oblique lens is the hardest and the most valuable. It's the image that makes someone stop and think. Use it for hero images and opening sections.


Source Guide

Do not default to stock photo sites. Stock search produces generic results regardless of how specific your terms are. Instead:

Primary: AI Generation

The best match for precise creative vision. Generate exactly what the concept describes.

  • Midjourney — Best for photographic realism and cinematic quality
  • DALL-E / GPT Image — Best for conceptual and illustrative work
  • Gemini — Good for diagrams, text-in-image, data visualization
  • Ideogram — Best when image includes readable text or typography
Secondary: Editorial & Archival Sources

When you need real photography (historical, documentary, journalistic):

  • Getty Editorial — Photojournalism, historical archives
  • Magnum Photos — Documentary photography
  • Library of Congress — US historical archives, public domain
  • NASA Image Gallery — Space, earth science, technology
  • Wikimedia Commons — Public domain, historical
  • British Museum / Smithsonian — Historical objects and documents
  • Internet Archive — Historical documents, publications, ephemera
  • Google Arts & Culture — Museum collections, artworks
Tertiary: Curated Stock (when you must)
  • Unsplash — Best for environmental/atmospheric shots, not people
  • Pexels — Acceptable for textures, backgrounds, abstract
  • Avoid for: People, business scenarios, technology in use, anything conceptual
For Specific Needs
NeedBest source
Historical technologySmithsonian, Computer History Museum, Science Museum UK
ArchitectureArchDaily, Dezeen photography
ScientificNature journal imagery, NOAA, ESA/Hubble
CulturalBritish Library, NYPL Digital Collections
Texture/materialGenerate via AI — more control

Anti-Cliché Guide

Universal Blacklist

These images are invisible — viewers have seen them thousands of times:

  • Handshakes (any kind)
  • Lightbulb = idea
  • Puzzle pieces connecting
  • Person on mountain summit
  • Hands holding globe
  • Diverse team pointing at whiteboard
  • Plant sprouting = growth
  • Rocket = launch/speed
  • Chess = strategy
  • Maze = complexity
  • Road diverging in forest = choice
  • Iceberg = hidden depth
  • Bridge = connection
The Reframing Technique

When you catch yourself reaching for a cliché:

  1. Name the cliché — "I'm about to search for a lightbulb"
  2. Ask: What does this concept feel like? — Not look like. Feel like.
  3. Ask: What moment captures this for a real person? — Specificity kills cliché
  4. Generate that instead

Example: "Innovation"

  • Cliché: Lightbulb, circuit board, rocket
  • Feels like: The moment before you know if it works
  • Real moment: Engineer's hand hovering over a switch, not yet thrown
  • That's the image

Critique Mode

When pointed at content that already has images (existing deck, webpage, document):

Step 1: Ingest & View Everything

Read all content. View every image. Do the work before speaking.

Show full SKILL.md (730 more words)Show less
Step 2: Overall Visual Language Summary

Open with a top-level assessment of the visual language across the entire piece. Cover:

  • What register are the images in? (archival, editorial, stock, mixed — name it)
  • Is there a unified visual language? If not, how many competing registers are present?
  • What's the gap between content intent and visual execution? The content is trying to say X; the images are saying Y.
  • What's working and what isn't — broad strokes, not image-by-image yet

Keep this to a short, direct paragraph or two. This is the headline diagnosis.

Step 3: Section-by-Section Summary

For each section/slide/chapter, give a high-level summary — not an image-by-image table. For each section:

SECTION: [Title or key line]
CONTENT INTENT: [What this section is trying to communicate]
VISUAL EXECUTION: [What the images are actually doing — 1-2 sentences]
VERDICT: [Working / Partially working / Not working — and why in one line]
STRONGEST IMAGE: [Which one and why, if any]
WEAKEST IMAGE: [Which one and why — name the specific problem]

Only go image-by-image if the user asks to drill into a specific section.

Step 4: Recommendations

End with specific, opinionated recommendations — not open-ended observations. The format:

RECOMMENDED DIRECTION
─────────────────────
Register: [The specific visual register I recommend — e.g., "archival-documentary
          with warm color treatment" not just "pick a register"]
Why: [1-2 sentences connecting this to the content's actual themes and audience]
Reference: [Think X meets Y — cite real touchstones]

WHAT TO KEEP
────────────
• [Specific images that already work, and why they're the standard]

WHAT TO REMOVE IMMEDIATELY
──────────────────────────
• [Images that actively damage the piece — stock, wrong brand, wrong tone]

WHAT TO REPLACE
───────────────
• [Images that are weak/generic — with one-line replacement concepts]

CONSISTENCY RULE
────────────────
[The single unifying quality all images should share — stated as a rule
that can be applied as a yes/no test to any candidate image]

Be specific. Be opinionated. Don't say "commit to one register" — say "I recommend archival-documentary with warm tungsten color treatment, because this content is about heritage and the images need to feel like they were pulled from a real company archive. Think Bell Labs photography meets Kinfolk's material warmth."

Then ask: "Does this direction feel right? If so, I'll generate replacement briefs with AI prompts for every image that needs to change."

Step 5: Replacement Briefs (after user confirms)

Once the user agrees to the recommended direction, generate replacement visual briefs for every image flagged for removal or replacement. Use the full Stage 4 section-by-section format:

  • Lock the recommended direction as the working style guide
  • For each image to replace, output the full visual brief with:
    • Concept (specific enough to shoot or generate)
    • AI generation prompts (Midjourney, DALL-E, Gemini, Ideogram)
    • Sourcing guidance (where to find real alternatives if not generating)
    • One alternative lens option
  • For sections that need additional images (currently too few), recommend how many and provide briefs

Output format: Generate all replacement briefs at once, numbered to match the original image positions. Export to a text file on the user's Desktop for easy reference and handoff.

Step 6: Handoff

After replacement briefs are generated, offer next steps:

  • "Generate now" — Generate images via fal.ai (Flux 2 Pro) directly from the briefs
  • "Export briefs" — Save all prompts and guidance to a file for use in Midjourney/DALL-E/external tools
  • "Rebuild the deck" — Feed the style guide and replacement images into keynote-slides-skill to produce a revised version
  • "Save as house style" — Lock the recommended direction as a reusable YAML template for future work with this brand

Image Generation via fal.ai

When the user selects "Generate now", generate images using Flux 2 Pro via the fal.ai API.

Requirements: $FAL_API_KEY environment variable must be set.

How to generate

For each image brief, run this via Bash:

bash
curl -s "https://queue.fal.run/fal-ai/flux-pro/v1.1" \
  -H "Authorization: Key $FAL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "<THE DALL-E/FLUX PROMPT FROM THE VISUAL BRIEF>",
    "image_size": "landscape_16_9",
    "num_images": 1,
    "safety_tolerance": "5"
  }'

This returns a JSON response with a request_id. Poll for the result:

bash
curl -s "https://queue.fal.run/fal-ai/flux-pro/v1.1/requests/<REQUEST_ID>" \
  -H "Authorization: Key $FAL_API_KEY"

When status is "COMPLETED", the response contains images[0].url. Download it:

bash
curl -sL "<IMAGE_URL>" -o "<OUTPUT_PATH>"
Generation workflow
  1. Create an output directory: .art-direction/generated/ (in the project) or a Desktop folder
  2. For each visual brief, take the DALL-E/GPT Image prompt (these work best with Flux)
  3. Submit to fal.ai, poll for completion, download the result
  4. Name files by section: section-01-heritage-grid.jpg, section-02-legacy-of-discovery.jpg, etc.
  5. After all images are generated, display them for review using the Read tool
  6. User can approve, request regeneration with adjusted prompts, or switch to a different lens
Image size options
image_size valueUse for
landscape_16_9Presentation slides, hero images
landscape_4_3Standard slides, documents
portrait_4_3Vertical layouts, mobile
squareSocial media, thumbnails
square_hdHigh-res square
Batch generation

When generating multiple images, submit all requests first (don't wait for each one), then poll for results. This parallelizes the GPU work.

bash
# Submit all requests, collect request IDs
for i in 1 2 3 4 5; do
  curl -s "https://queue.fal.run/fal-ai/flux-pro/v1.1" \
    -H "Authorization: Key $FAL_API_KEY" \
    -H "Content-Type: application/json" \
    -d "{\"prompt\": \"$PROMPT\", \"image_size\": \"landscape_16_9\"}" \
    | python3 -c "import sys,json; print(json.load(sys.stdin)['request_id'])"
done

# Then poll each request_id for results
Cost

Flux 2 Pro via fal.ai is pay-per-image. Typical cost is ~$0.05-0.10 per image. A full deck replacement (10-15 images) runs about $1-2.

Fallback

If $FAL_API_KEY is not set or the API is unavailable:

  • Export briefs to file instead
  • Note that the user can paste prompts into Midjourney, ChatGPT image gen, or higgsfield.ai manually

House Style Templates

Reusable visual directions stored in ~/.agents/skills/art-direct/styles/ as YAML.

yaml
name: "Style Name"
description: "One-line description with reference touchstones"

photography:
  style: documentary | editorial | conceptual | abstract | archival
  subjects:
    preferred: [list of subject types]
    avoid: [list of subject types to reject]
  lighting:
    preferred: [light quality description]
    avoid: [light quality to reject]
  composition: [framing rules]
  color:
    treatment: [color approach]
    palette_anchors: [hex codes]

mood:
  primary: [one emotional quality]
  supporting: [list of supporting emotions]
  energy: [calm | dynamic | tense | contemplative]

lens_preferences:
  default_order: [ordered list of five lenses]
  weight_toward: [primary lens]
  notes: "Usage guidance"

cliche_blacklist:
  universal: [standard clichés]
  brand_specific: [context-specific clichés]

ai_prompt_suffixes:
  photography: "prompt suffix for photo-style generation"
  illustration: "prompt suffix for illustration-style generation"

reference_touchstones:
  - "Reference 1"
  - "Reference 2"

Quick Reference

InvocationPurpose
art-directFull workflow — ingest content, propose directions, generate briefs
art-direct --style <name>Apply existing house style template
art-direct --critiqueReview existing visuals against content intent
art-direct --section "concept"Quick single-section visual brief
art-direct --from-frontend <project>Derive style from frontend-design project

Integration

Outputs can feed into:

  • keynote-slides-skill — Visual briefs → slide imagery via Gemini generation
  • branded-pptx-converter — Visual briefs → PowerPoint image slots
  • frontend-design — Style guide → web design visual language

© divinevideo, 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 5 other files in .agents/skills/art-direct of divinevideo/divine-mobile.

  • SKILL.md
  • LICENSE
  • README.md
  • docs/2026-01-28-art-direct-design.md
  • styles/bold-minimalism.yaml
  • styles/editorial-warmth.yaml

Open the folder on GitHubat commit 6487b05

Compare with similar skills

Art Direct 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.

Art Direct compared with similar skills
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Gpt Image Slide Planhumantonylee/future-slide150—~2.6kAutomated safety check: PassApache-2.0
Q-Presentations Slide Deck GeneratorTyrealQ/q-skills108—~1.1kAutomated safety check: PassMIT
Gpt Image Slide Prompthumantonylee/future-slide150—~2kAutomated safety check: PassApache-2.0
Gpt Image Slidehumantonylee/future-slide150—~397Automated safety check: PassApache-2.0

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Questions about Art Direct

What does Art Direct do?

Art direction for any content — reads text, PDF, Word, HTML, PPT, then proposes 2-3 creative directions with photography style, mood, and visual language. Art Direct is an agent skill from divinevideo/divine-mobile. Art direction for any content — reads text, PDF, Word, HTML, PPT, then proposes 2-3 creative directions with photography style, mood, and visual language.

When should I use Art Direct?

Art Direct fits situations like: the user shares content and needs visual direction; creative direction for any material.

How do I install Art Direct in Claude Code?

Run `npx skills add divinevideo/divine-mobile --skill art-direct -a claude-code`. Or copy the skill folder (.agents/skills/art-direct in divinevideo/divine-mobile) into .claude/skills/art-direct in your project. Claude Code loads it when a task matches its description.

How do I install Art Direct in Codex?

Run `npx skills add divinevideo/divine-mobile --skill art-direct -a codex`. Or copy the skill folder (.agents/skills/art-direct in divinevideo/divine-mobile) into .agents/skills/art-direct in your project. Codex loads it when a task matches its description.

Can I use Art Direct 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 divinevideo/divine-mobile --skill art-direct -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/art-direct, .gemini/skills/art-direct, .github/skills/art-direct and .opencode/skills/art-direct in your project.

What does Art Direct need to run?

Going by SKILL.md and its folder, Art Direct needs the command-line tools its instructions call (curl and python3) and credentials named FAL_API_KEY. Our summary lists: Python 3.

Does Art Direct access the network?

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

Is Art Direct 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 Art Direct use?

Art Direct is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Art Direct use?

About 4.8k tokens (SKILL.md is roughly 19k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Art Direct?

Skills that share tags, products or a category with Art Direct: Nano Banana (EvoScientist/EvoSkills, 476 stars), Gpt Image Slide Plan (humantonylee/future-slide, 150 stars), Q-Presentations Slide Deck Generator (TyrealQ/q-skills, 108 stars) and Gpt Image Slide Prompt (humantonylee/future-slide, 150 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Art Direct?

divinevideo (a GitHub organization) maintains it in divinevideo/divine-mobile, which has 266 GitHub stars. The repository holds 103 skills in this directory. The repository was last updated on October 9, 2026.

Source: divinevideo/divine-mobile on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.