ReddRadar
Agent skill
music-prompt-engineering
Optimize and format prompts specifically for AI music generation platforms like Suno and Udio, including platform-specific syntax and tag optimization
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/social-sciences-humanities/arts-culture/music-album-creation/skills/music-prompt-engineering
SKILL.md
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:
[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:
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:
[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:
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
[Primary Genre], [Subgenre], [Era Reference], [Key Characteristics],
[Mood], [Production Style]
Artist-Focused Template
In the style of [Artist 1] meets [Artist 2], [Genre], [Key Elements],
[Vocal Description], [Mood]
Production-Focused Template
[Genre], [Instrumentation Details], [Drum/Rhythm Type], [Bass Type],
[Synth/Keys], [Effects], [Mix Character], [Era Production Style]
Vocal-Focused Template
[Genre], [Vocal Style and Quality], [Vocal Range], [Emotional Delivery],
[Influenced by Vocalists], [Production Context]
Mood-Focused Template
[Mood/Atmosphere], [Genre], [Tempo Feel], [Energy Level],
[Visual/Emotional Imagery], [Production Aesthetic]
Tag Reference Library
Genre Tags (High Effectiveness)
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
60s, 70s, 80s, 90s, 2000s, modern, retro, vintage,
futuristic, timeless, classic
Vocal Tags
male vocalist, female vocalist, raspy, breathy, clear,
powerful, soft, ethereal, soulful, operatic, spoken word,
rap, singing, harmonies, choir, whispered
Mood Tags
melancholic, euphoric, dark, bright, dreamy, aggressive,
peaceful, anxious, nostalgic, hopeful, angry, romantic,
mysterious, playful, intense, relaxed
Production Tags
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
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