Music Prompt Engineering

Optimize and format prompts for AI music generation platforms.

Overview

This skill provides platform-specific optimization for AI music generation prompts. It covers prompt structure, tag selection, platform syntax, iteration strategies, and quality assessment for Suno, Udio, and similar platforms.

Capabilities

Platform Understanding

•Know Suno prompt structure and limits
•Understand Udio interpretation patterns
•Adapt to platform updates
•Leverage platform-specific features

Prompt Structuring

•Order elements for best interpretation
•Balance specificity and flexibility
•Layer genre, style, and mood
•Include key descriptors efficiently

Tag Optimization

•Use effective genre tags
•Apply vocal style tags
•Include era/production tags
•Add mood and atmosphere tags

Iteration Strategy

•Design prompt variations
•Test and refine approaches
•Document successful patterns
•Build prompt libraries

Quality Assessment

•Evaluate output match to intent
•Identify interpretation issues
•Refine problematic prompts
•Track platform behavior changes

Platform-Specific Guidelines

Suno Prompts

Structure:

code

[Genre Tags], [Era/Style], [Tempo/Energy], [Vocal Description], [Instrumentation], [Mood/Atmosphere], [Production Quality]

Effective Tags:

Category	Examples
Genre	indie rock, synth-pop, trap, lo-fi hip-hop
Era	80s, 90s alternative, modern pop
Tempo	uptempo, slow burn, driving beat
Vocal	female vocalist, raspy male vocals, ethereal
Mood	melancholic, euphoric, dark, dreamy
Production	polished, raw, lo-fi, bedroom pop

Example Prompt:

code

indie rock, 90s alternative, driving guitars, female vocalist with
breathy delivery, jangly guitars, distorted bass, melancholic but
catchy, influenced by Mazzy Star and Alvvays, reverb-drenched

Udio Prompts

Structure:

code

[Detailed Genre Description], [Specific Artist Influences], [Production Details], [Vocal Specifics], [Mood and Atmosphere]

Best Practices:

•More detailed descriptions work well
•Artist references are effective
•Production specifics matter
•Vocal descriptions should be clear

Example Prompt:

code

A dreamy electronic track blending trip-hop with ambient textures,
reminiscent of Portishead meets Boards of Canada. Features a
smoky female vocal with subtle processing, over deep sub-bass,
sparse breakbeats, and lush synthesizer pads. Moody, introspective
atmosphere with vinyl warmth and tape saturation. 85 BPM, minor key.

Prompt Templates

Genre-Focused Template

code

[Primary Genre], [Subgenre], [Era Reference], [Key Characteristics],
[Mood], [Production Style]

Artist-Focused Template

code

In the style of [Artist 1] meets [Artist 2], [Genre], [Key Elements],
[Vocal Description], [Mood]

Production-Focused Template

code

[Genre], [Instrumentation Details], [Drum/Rhythm Type], [Bass Type],
[Synth/Keys], [Effects], [Mix Character], [Era Production Style]

Vocal-Focused Template

code

[Genre], [Vocal Style and Quality], [Vocal Range], [Emotional Delivery],
[Influenced by Vocalists], [Production Context]

Mood-Focused Template

code

[Mood/Atmosphere], [Genre], [Tempo Feel], [Energy Level],
[Visual/Emotional Imagery], [Production Aesthetic]

Tag Reference Library

Genre Tags (High Effectiveness)

code

indie rock, synth-pop, trap, lo-fi hip-hop, dream pop,
shoegaze, post-punk, neo-soul, trip-hop, ambient,
drum and bass, house, techno, R&B, jazz, folk,
country, metal, punk, grunge, alternative

Era Tags

code

60s, 70s, 80s, 90s, 2000s, modern, retro, vintage,
futuristic, timeless, classic

Vocal Tags

code

male vocalist, female vocalist, raspy, breathy, clear,
powerful, soft, ethereal, soulful, operatic, spoken word,
rap, singing, harmonies, choir, whispered

Mood Tags

code

melancholic, euphoric, dark, bright, dreamy, aggressive,
peaceful, anxious, nostalgic, hopeful, angry, romantic,
mysterious, playful, intense, relaxed

Production Tags

code

lo-fi, polished, raw, clean, distorted, reverb-heavy,
minimal, lush, sparse, dense, vintage, modern,
analog, digital, warm, crisp

Usage Guidelines

Prompt Creation Process

•Identify core musical vision
•Select primary genre tags
•Add era/style context
•Describe vocal requirements
•Specify key instrumentation
•Add mood/atmosphere
•Include production notes
•Add reference artists (sparingly)
•Review for clarity and length
•Create 2-3 variations

Prompt Optimization Tips

•Be specific but not over-constrained
•Use well-known genre terms
•Artist references should be recognizable
•Balance tags across categories
•Avoid contradictory descriptors
•Test and iterate based on results

Quality Checklist

• Genre is clearly specified
• Era/style provides context
• Vocal description is actionable
• Instrumentation is genre-appropriate
• Mood is clearly conveyed
• Production style is defined
• Prompt is not too long
• No contradictory elements

Integration Points

Related Skills

•SK-MAC-002 (style-specification) - Source specifications
•SK-MAC-006 (genre-analysis) - Genre accuracy
•SK-MAC-007 (vocal-direction) - Vocal tags
•SK-MAC-008 (production-guidance) - Production tags

Related Agents

•AG-MAC-002 (music-producer-agent) - Prompt creation

Common Issues and Fixes

Issue	Cause	Fix
Wrong genre output	Vague genre tags	Be more specific with subgenres
Wrong vocal	Unclear vocal description	Add specific vocal style tags
Wrong tempo	Missing tempo indication	Add BPM or tempo feel
Generic sound	Too few details	Add production specifics
Inconsistent	Contradictory tags	Remove conflicting descriptors
Over-constrained	Too many tags	Simplify, focus on essentials

References

•Suno community prompt guides
•Udio prompt best practices
•AI music generation forums
•Platform update documentation