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skyni8568

suno-poetry-music-creator

by Skyni8568 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install suno-poetry-music-creator
Description
Enhanced Suno song creator with reference song analysis and intelligent lyric optimization. Analyzes user's reference songs to extract style, mood, and struc...
README (SKILL.md)

Suno Song Creator Enhanced 🎵✨

Transform creative themes into AI-generated songs with Suno, now with reference song analysis and intelligent lyric optimization.

When to Use

  • User wants to create a song similar to a reference track
  • User says "make a song like [artist/song]..."
  • User wants to optimize lyrics after Suno generation
  • User needs help matching a specific musical style
  • User wants to turn poetry into a song with specific genre constraints
  • User wants to create Chinese classical style songs with proper rhyme and tonal patterns

Quick Start

User: "创作一首关于春天的歌,风格像周杰伦的《青花瓷》"
→ 分析参考歌曲 → 生成歌词 → 优化 → 输出 Suno 风格标签

Complete Workflow

Phase 1: Discovery

  1. Understand theme/concept
  2. Ask for reference song (optional but recommended)
  3. Determine target mood and style
  4. Identify cultural/linguistic context

Phase 2: Research & Analysis

IF reference provided: → Analyze reference song characteristics (see [references/lyric-examples.md] for analysis framework) → Extract style DNA → Map to Suno tags

ELSE: → Use default style selection → Research poetry for theme

IF Chinese classical style: → Consult [references/chinese-rhyme.md] for rhyme scheme → Apply tonal patterns and couplet techniques

Phase 3: Creation - First Draft

  1. Generate initial lyrics with proper structure
  2. Create style tags based on analysis
  3. Present complete package to user

Phase 4: Poetic Elevation ⬆️

Transform first draft into poetic version:

  • Apply personification and metaphor
  • Enhance sensory details (sound, touch, smell)
  • Create dynamic imagery
  • Elevate personal emotions to universal themes
  • Add musical arrangement guidance

See [references/lyric-examples.md] for detailed examples.

Phase 5: Optimization (if needed)

IF user wants changes: → Identify specific issues → Apply optimization rules → Generate improved version → Repeat up to 3 times

Reference Song Analysis 🎧

When user provides a reference song/artist:

Step 1: Extract Reference Information

Artist: [Artist Name]
Song: [Song Title]
Genre: [Inferred Genre]
Era: [Time Period]
Mood: [Emotional Tone]

Step 2: Analyze Musical Characteristics Use web search to find:

  • Song structure (Verse-Chorus pattern, Bridge placement)
  • Instrumentation and arrangement style
  • Vocal style and range
  • Tempo and rhythm characteristics
  • Lyrical themes and imagery patterns

Step 3: Extract Style DNA

Reference Analysis:
  genre: [Primary Genre]
  sub_genre: [Sub-style]
  tempo: [BPM range or descriptor]
  mood: [Emotional profile]
  instrumentation: [Key instruments]
  vocal_style: [Vocal characteristics]
  lyrical_density: [Wordy/Minimal/Average]
  rhyme_scheme: [Rhyme pattern]
  chorus_hook: [Hook style]

Step 4: Map to Suno Style Tags

[Genre], [Sub-genre], [Mood], [Instrumentation], [Vocal Style]

Lyric Optimization Loop 🔄

When Suno generation doesn't meet expectations:

Step 1: Analyze Feedback Identify issues:

  • ❌ Lyrics too long/short for melody
  • ❌ Words don't flow well with music
  • ❌ Emotion not matching style
  • ❌ Pronunciation issues
  • ❌ Need more/less repetition
  • ❌ Lacks poetic depth or imagery
  • ❌ Too plain or cliché

Step 2: Apply Optimization Rules

Rule 1: Poetic Elevation ⬆️ Transform plain descriptions into poetic imagery:

Before: 春风拂柳绿枝芽
After:  春风借柳 织几抹新芽

Techniques: Personification, sensory details, dynamic action See [references/lyric-examples.md] for complete examples.

Rule 2: Length Adjustment

  • Target: 4-8 syllables per line for most genres
  • Break long lines or combine short ones

Rule 3: Flow Improvement

  • Eliminate tongue twisters
  • Soften hard consonants at line ends
  • Add alliteration or assonance

Rule 4: Emotional Alignment

  • Match word intensity to music energy
  • High energy → Strong, active verbs
  • Soft music → Gentle, flowing imagery

Rule 5: Repetition Strategy

  • Chorus: 60-70% repeated phrases
  • Verse: 20-30% internal repetition
  • Bridge: Fresh content, minimal repetition

Rule 6: Emotional Depth Enhancement 💫

Before: 莫道离别苦 / 且将思念藏
After:  莫叹离别苦 / 岁月暗流藏

Techniques: Personal→Universal, metaphorical depth, philosophical undertones

Chinese Classical Style Guide

For Chinese classical style songs:

  1. Consult [references/chinese-rhyme.md] for 《中华新韵》14韵部
  2. Choose one rhyme category and stick to it throughout the song
  3. Apply tonal patterns - alternate between level (平) and oblique (仄) tones
  4. Use couplet techniques - parallel structure in adjacent lines

Example couplet:

春风拂柳 / 细雨润物  (春风对细雨,拂柳对润物)
流水无情 / 青山有意  (流水对青山,无情对有意)

Style Tag Library

By Genre

Pop: Pop, Catchy, Radio-friendly, Modern
Rock: Rock, Electric Guitar, Energetic, Driving
Jazz: Jazz, Smooth, Saxophone, Sophisticated
Classical: Classical, Orchestral, Cinematic, Epic
Electronic: Electronic, Synth, EDM, Upbeat
Folk: Folk, Acoustic, Storytelling, Intimate
R&B: R&B, Soulful, Groove, Smooth
Hip-Hop: Hip-Hop, Rap, Beats, Urban
Chinese Classical: Chinese Classical, Folk, Erhu, Guzheng, Female Vocal, Melancholic, Cinematic

By Mood

Happy: Upbeat, Cheerful, Bright, Positive
Sad: Melancholic, Somber, Emotional, Tearful
Energetic: High Energy, Intense, Powerful, Driving
Calm: Peaceful, Relaxing, Gentle, Serene
Romantic: Love, Passionate, Tender, Intimate
Dark: Moody, Brooding, Mysterious, Intense

Best Practices

  1. Always ask for reference - Even vague references help ("like 80s synth-pop" or "similar to Adele's ballads")

  2. Iterate based on feedback - Don't expect perfection on first try

  3. Match style to content - Sad lyrics need appropriate musical backing

  4. Keep Suno's limitations in mind:

    • ~120-150 words maximum for best results
    • Shorter phrases work better
    • Clear enunciation helps
    • Repetition is your friend for hooks
  5. Cultural sensitivity - When adapting classical poetry, respect the original meaning while making it singable

  6. Poetic Elevation is key - First drafts are often plain; always look for opportunities to elevate

  7. Learn from feedback - When users share improved versions, analyze what changed and why

Integration with Tools

  • web_search: Research reference songs and artists
  • browser: Suno automation and reference listening
  • gemini: Poetry research and lyric generation
  • image: Analyze album artwork for style cues (if provided)

Safety & Ethics

  • Respect artist copyrights - analyze style, don't copy lyrics
  • Inform users about Suno's terms of service
  • Credit original poets when adapting classical works
  • Be mindful of cultural appropriation when using traditional styles
Usage Guidance
This skill is internally consistent and low-risk: it’s an instruction-only helper that analyzes reference songs (via public web search and included rhyme/lyric references) and helps produce/optimize lyrics. Before installing, confirm two things: (1) how Suno is actually invoked in your environment — the SKILL.md refers to Suno generation/feedback but doesn't show API or CLI calls or required credentials, so verify whether the platform already provides Suno or whether you'll need to supply an API key; (2) copyright and privacy practices — when you ask the skill to “make a song like [artist/song]” or provide reference audio/files, be cautious about uploading copyrighted audio or giving the skill access to private files. If you plan to connect external services (Suno API, file uploads), ensure credentials are stored securely and that you trust the destination before sharing non-public data.
Capability Analysis
Type: OpenClaw Skill Name: suno-poetry-music-creator Version: 1.0.0 The bundle is a legitimate toolset designed to assist an AI agent in creating and optimizing song lyrics for the Suno music platform, with a specialized focus on Chinese classical poetry. The instructions in SKILL.md and the reference data in chinese-rhyme.md and lyric-examples.md are well-structured and align perfectly with the stated purpose of style analysis and poetic enhancement. While the skill utilizes high-privilege tools like 'browser' for Suno automation, there is no evidence of malicious intent, data exfiltration, or unauthorized command execution.
Capability Assessment
Purpose & Capability
The name/description (Suno-based song creator with reference analysis and lyric optimization) matches the SKILL.md's workflow (analyze references, produce/optimize lyrics, map style tags). Minor gap: the SKILL.md repeatedly references 'Suno generation' and 'Suno feedback' but does not document how to invoke Suno (no API/CLI commands or required credentials). This is plausibly fine if the hosting platform already exposes Suno as a tool, but it should be clarified.
Instruction Scope
Runtime instructions are limited to asking user for theme/reference, using web search to analyze public information about reference tracks, applying lyric optimization rules, and consulting included rhyme/lyric reference files. No steps ask the agent to read unrelated system files or to exfiltrate secrets.
Install Mechanism
There is no install spec and no code files; the skill is instruction-only, which minimizes on-disk risk. Nothing will be downloaded or executed by an installer as part of the skill bundle.
Credentials
The skill declares no required environment variables or credentials, which is proportionate to the textual analysis/lyric work. Slight inconsistency: it expects to work with Suno but doesn't declare a primary credential or explain how Suno access is provided; confirm whether the platform supplies Suno or whether the user will need to provide API credentials separately.
Persistence & Privilege
Flags are default (always: false, user-invocable, normal autonomous invocation allowed). The skill does not request persistent/privileged presence or attempt to modify other skills or system-wide config.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install suno-poetry-music-creator
  3. After installation, invoke the skill by name or use /suno-poetry-music-creator
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Suno Poetry Music Creator 1.0.0 – Initial Release - Create AI-generated songs with Suno by analyzing user-provided reference tracks for style, mood, and structure. - Includes intelligent lyric optimization, iteratively refining lyrics based on Suno generation feedback and lyrical best practices. - Supports creation of Chinese classical style songs with correct rhyme, tonal patterns, and couplet techniques. - Provides step-by-step workflow: concept discovery, reference analysis, lyric drafting, poetic elevation, and optimization loop. - Integrates with web search, Gemini, and image tools for research and enhancement of lyrics and song concepts. - Features guidelines and best practices for style matching, lyric structuring, and ethical/cultural considerations.
Metadata
Slug suno-poetry-music-creator
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is suno-poetry-music-creator?

Enhanced Suno song creator with reference song analysis and intelligent lyric optimization. Analyzes user's reference songs to extract style, mood, and struc... It is an AI Agent Skill for Claude Code / OpenClaw, with 211 downloads so far.

How do I install suno-poetry-music-creator?

Run "/install suno-poetry-music-creator" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is suno-poetry-music-creator free?

Yes, suno-poetry-music-creator is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does suno-poetry-music-creator support?

suno-poetry-music-creator is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created suno-poetry-music-creator?

It is built and maintained by Skyni8568 (@skyni8568); the current version is v1.0.0.

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