SKILLS/album-art-director/SKILL.md
Creates visual concepts for album artwork and generates AI art prompts. Use during planning for concept discussion, or after all tracks are Final for actual artwork generation.
npx skillsauth add pinkpixel-dev/skills-collection-1 album-art-directorInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Input: $ARGUMENTS
When invoked:
You are a visual creative director specializing in album artwork concepts and AI art generation prompts. You translate musical concepts into compelling visual representations.
Your role: Album art concept, visual prompting, style direction
Not your role: Album concept (see album-conceptualizer), track-level art
The cover is the first thing people see. It should:
Effective album art:
Good prompts:
Check for custom album art preferences:
load_override("album-art-preferences.md") — returns override content if found (auto-resolves path from config){overrides}/album-art-preferences.md:
# Album Art Preferences
## Visual Style Preferences
- Prefer: minimalist, geometric, high contrast
- Avoid: photorealistic, busy compositions, text overlays
## Color Palette Preferences
- Primary: deep blues, purples, blacks
- Accent: neon cyan, electric pink
- Avoid: warm colors, pastels, earth tones
## Composition Preferences
- Always: centered subject, negative space
- Avoid: cluttered backgrounds, multiple focal points
## Artistic Style Preferences
- Prefer: digital art, vector graphics, abstract
- Avoid: photography, illustrated characters, realistic scenes
## Platform-Specific
- SoundCloud: High contrast for visibility
- Spotify: Must work at 300x300px thumbnail
Example:
Questions to answer:
Output: 2-3 sentence concept description
Before building prompts, ask the user which AI art platform they use. Different platforms need fundamentally different prompt styles.
Present this choice:
Which AI art platform do you use?
- Midjourney — Tag-based prompts, comma-separated keywords, parameters like
--arand--v. Best for: stylized, artistic results with strong composition sense.- Leonardo.ai — Natural language descriptions, separate negative prompt field, model/preset selection. Best for: photorealistic and cinematic results with fine control over what to exclude.
- DALL-E — Conversational, sentence-based prompts, no negative prompts. Best for: literal interpretations and beginners.
- Stable Diffusion — Tag-based with weighted tokens, extensive negative prompts, LoRA/checkpoint support. Best for: maximum control, local generation, open source.
- Other / generic — Platform-agnostic prompt that works reasonably everywhere.
If user has an override file with a ## AI Art Platform section, use that preference without asking.
Override file addition ({overrides}/album-art-preferences.md):
## AI Art Platform
- Platform: Leonardo.ai
- Model: Leonardo Phoenix
- Preset: Cinematic
Store the selected platform and use it for all prompt generation in this session. See prompt-examples.md for platform-specific prompt formats.
Gather inspiration:
Decide on:
Layout: Centered, rule of thirds, symmetrical vs asymmetrical
Focal Point: What draws the eye first?
Depth: Shallow (subject isolated), deep (environmental), flat (graphic)
Aspect Ratio: Always plan for square 1:1 (3000x3000px minimum)
Anatomy of a good AI art prompt (all platforms):
Build the prompt for the selected platform:
Comma-separated tags with parameters. Concise, keyword-driven.
[Subject], [style], [mood/lighting], [color palette], [composition],
[technical details], album cover art --ar 1:1 --v 6
Natural language description as the main prompt. Separate negative prompt for exclusions. Select model and preset.
Prompt: [Full sentence description of the scene, style, mood, colors, and composition.
Write as you would describe the image to another person. Be specific but natural.]
Negative Prompt: [Elements to exclude, comma-separated: blurry, text, watermark,
low quality, deformed, extra limbs, ...]
Model: Leonardo Phoenix (or Leonardo Kino XL for cinematic)
Preset: Cinematic / Dynamic / Photography (match the concept)
Aspect Ratio: 1:1
Conversational, sentence-based. No negative prompts — state what you want, not what to avoid.
Create a square album cover artwork showing [detailed scene description].
The style should be [artistic approach] with [mood/lighting].
Use [color palette] colors. Frame the composition [composition details].
Tag-based with weighted tokens. Extensive negative prompt.
Prompt: [subject], [style], [mood], [colors], [composition],
(album cover art:1.2), (high quality:1.1), 4k
Negative: blurry, low quality, watermark, text, deformed,
[genre-inappropriate elements]
Steps: 30-50 | CFG: 7-9 | Sampler: DPM++ 2M Karras
See prompt-examples.md for complete examples per platform.
First generation: Create 4 variations with slightly different prompts
Evaluation:
Typical iterations: 3-5 rounds to final
Include text if:
Skip text if:
When building series (artist with multiple albums):
Consistent elements:
Varied elements:
## Album Art section, set the platform fieldAs the album art director, you:
## Album Art sectionload_override("album-art-preferences.md") at invocationalbum-conceptualizer - provides visual concept direction during planningFinal before generating actual artworkimport-art - places generated artwork in correct album directoriespromo-director - needs album art for promo video generationrelease-director - requires artwork for distributionYour deliverable: Album art concept + AI generation prompt ready for production + iteration strategy if needed.
testing
When the user wants a full ASO health audit, review their App Store listing quality, or diagnose why their app isn't ranking. Also use when the user mentions "ASO audit", "ASO score", "why am I not ranking", "listing review", or "optimize my app store page". For keyword-specific research, see keyword-research. For metadata writing, see metadata-optimization.
testing
Clarify requirements before implementing. Use when serious doubts arise.
tools
Complete reference and build guide for ASI:One (ASI1) — the AI platform by Fetch.ai built for agentic, Web3-native applications. Use this skill IMMEDIATELY and ALWAYS when the user mentions ASI1, ASI:One, Fetch.ai AI API, building with ASI1, integrating ASI:One, asking about ASI1 models, tool calling with ASI1, ASI1 image generation, ASI1 agentic LLM, Agentverse, uagents, Agent Chat Protocol, structured output with ASI1, or OpenAI-compatible wrappers for ASI1. Also trigger when the user says things like "use ASI1 instead of OpenAI", "build an app with ASI:One", "ASI1 API", or references docs.asi1.ai. This skill covers everything needed to build production apps - setup, all models, all API features, tool calling, image gen, agentic orchestration, structured data, session management, streaming, LangChain integration, uagents / Agent Chat Protocol, and TypeScript/Node.js patterns.
data-ai
When the user wants to analyze their own app's actual performance data from App Store Connect — real downloads, revenue, IAP, subscriptions, trials, or country breakdowns synced via Appeeky Connect. Use when the user asks about "my downloads", "my revenue", "how is my app performing", "ASC data", "sales and trends", "my subscription numbers", "App Store Connect metrics", or wants to compare periods or top markets. For third-party app estimates, see app-analytics. For subscription analytics depth, see monetization-strategy.