Review Suno Song

Launch an independent quality review of Suno prompts and lyrics using the quality-reviewer sub-agent. Get objective professional assessment without bias.

When to Use This Skill

Use this skill to:

• Review existing song prompts before submission to Suno
• Evaluate lyrics for quality issues (AI-slop, clichés, awkward phrasing)
• Get feedback on prompt structure and specificity
• Check copyright safety (no artist/band/album names)
• Validate style-lyric consistency for genre
• Assess rhyme schemes and quality
• Identify areas for improvement before final version

Two Usage Modes

Mode 1: Review Saved Prompt File

When you have a saved prompt.md file:

/review-song path/to/prompt.md

The skill will:

1. Read the file automatically
2. Extract prompt sections and lyrics
3. Launch quality-reviewer sub-agent
4. Present structured feedback

Mode 2: Review Direct Text

When pasting prompt + lyrics directly:

/review-song

The skill will:

1. Prompt you to paste your structured prompt
2. Prompt you to paste your lyrics
3. Extract genre/mood context
4. Launch quality-reviewer sub-agent
5. Present structured feedback

What Gets Evaluated

Prompt Quality (Structured Sections)

Structure:

• Proper colon-and-quotes format
• No blank lines between sections
• Required sections present (genre, vocal, instrumentation, production, mood)

Specificity:

• Concrete descriptors vs. vague abstractions
• Technical vocabulary appropriate to genre
• Clear production techniques described

Copyright Safety:

• No artist names
• No band names
• No album titles
• No song titles
• Style descriptions focus on characteristics

Genre Alignment:

• Descriptors match genre conventions
• No contradictory elements
• Appropriate technical vocabulary

Lyric Quality (Comprehensive Assessment)

AI-Slop Detection:

• Technology clichés: "neon lights", "digital", "echoes in the void"
• Abstract vagueness: "whispers in the dark", "fragments of", "fading memories"
• Generic imagery without concrete context

Cliché Detection:

• Romantic clichés: "heart on my sleeve", "falling for you", "love at first sight"
• General song clichés: "time will heal", "reach for the stars", "follow your dreams"
• Genre-specific clichés: Country (trucks/beer), Pop (dancing all night), Rock (breaking chains)
• Lazy rhyming with cliché phrases

Poor Lyric Quality:

• Awkward or clunky phrasing that doesn't flow
• Grammatical issues (unless intentional for style)
• Nonsensical or confusing imagery
• Mixed metaphors that contradict
• Lines that are too wordy or verbose
• Unintentionally funny or cringe-worthy lines
• Excessive filler words ("yeah yeah yeah" without purpose)
• Trying too hard to be clever/poetic and failing
• Inconsistent voice or jarring tone shifts

Specificity vs. Abstractions:

• Concrete nouns, specific numbers, physical details
• Sensory details vs. vague generalities
• "Show don't tell" principle

Metaphor Consistency:

• Central metaphor maintained throughout
• No contradictory imagery
• Coherent metaphor system

Syllable Patterns:

• Consistency within sections
• Singability without awkward rushing
• Natural emphasis patterns

Rhyme Scheme and Quality:

• Pattern identification (AABB, ABAB, ABCB, etc.)
• Rhyme quality (exact, slant, forced)
• Genre appropriateness
• Avoidance of over-reliance on easy rhymes

Style-Lyric Consistency:

• Content matches genre expectations
• Tone alignment (playful pop vs. serious ballad)
• Language complexity appropriate for style
• Subject matter fits genre conventions

Gender-Pronoun Consistency:

• POV clarity for vocalist gender
• Narrative context for pronoun usage
• Check for confusing or contradictory pronouns

General Taste and Quality:

• Catchiness and memorability
• Flow and singability
• Emotional resonance and authenticity
• Hook strength
• Professional polish vs. amateur feel

Output Format

Receive structured feedback categorized by severity:

**Prompt Quality: X/10**
- Structure: [✓/⚠️/✗] [comment]
- Specificity: [✓/⚠️/✗] [comment]
- Copyright: [✓/✗] [comment]
- Genre alignment: [✓/⚠️/✗] [comment]

**Lyric Quality: X/10**
- AI-slop: [count] instances - [specific examples with line numbers]
- Clichés: [count] instances - [specific examples with line numbers]
- Poor quality lines: [count] instances - [specific examples with line numbers and reasons]
- Specificity: [✓/⚠️/✗] [comment]
- Metaphor consistency: [✓/⚠️/✗] [comment]
- Syllable patterns: [✓/⚠️/✗] [comment]
- Rhyme scheme: [✓/⚠️/✗] [pattern and quality assessment]
- Style-lyric fit: [✓/⚠️/✗] [genre expectations match]
- Gender-pronoun consistency: [✓/⚠️/✗] [POV clarity]
- General taste: [X/10] [overall quality assessment]

**Recommendations (by severity):**

CRITICAL (must fix):
1. [Specific issue with line numbers and reasoning]

SUGGESTED (strong recommendations):
1. [Specific improvement with suggested replacement]

OPTIONAL (nice-to-have):
1. [Refinement suggestion with reasoning]

How It Works

Internal Process

1. Extract Content:

   • If file path provided: Read file, parse YAML frontmatter, extract prompt sections and lyrics
   • If direct text: Prompt user to paste content

2. Identify Context:

   • Extract genre from prompt
   • Extract mood from prompt
   • Extract vocal style from prompt

2.5. Ask Genre-Specific Refinement Questions (NEW):

Use AskUserQuestion tool to collect evaluation preferences from user.

Question 1: Specificity Preference

question: "How should I evaluate specificity for this {genre} song?"
header: "Specificity"
multiSelect: false
options:
  - label: "Strict Commercial Standards"
    description: "Avoid ALL brand names, product references, and dated cultural references. Prioritize universal, timeless language suitable for radio/commercial release."

  - label: "Balanced Approach (Recommended)"
    description: "Flag obvious brand names and dated references, but allow some specific details if they serve the song. Consider genre conventions."

  - label: "Authentic/Artistic Priority"
    description: "Allow specific brands, places, and cultural references if they enhance authenticity and storytelling. Prioritize artistic vision over commercial considerations."

Question 2: Contemporary vs. Timeless Balance

question: "What's your priority for contemporary relevance vs. timeless appeal?"
header: "Contemporary"
multiSelect: false
options:
  - label: "Maximum Timeless Appeal"
    description: "Avoid all dated references. Flag anything that might age (tech products, current slang, 2025-specific culture). Prioritize songs that work in any era."

  - label: "Balanced (Recommended)"
    description: "Accept some contemporary references if not too specific. Flag obvious dating risks (product names, specific tech). Allow current but not hyper-specific language."

  - label: "Current/Contemporary Focus"
    description: "Embrace contemporary references for immediate relatability. Accept that song may date. Prioritize connecting with current audience over timelessness."

Question 3: Wordiness Tolerance

question: "How should I evaluate lyrical economy for this {genre} song?"
header: "Wordiness"
multiSelect: false
options:
  - label: "Strict Economy (Pop/Electronic)"
    description: "Flag lines over 8 words. Prioritize compressed, punchy language. Every word must earn its place."

  - label: "Moderate (Recommended for most genres)"
    description: "Flag lines over 10 words as suggestions. Balance economy with expression. Allow some variation."

  - label: "Narrative Freedom (Folk/Country/Indie)"
    description: "Allow 10-12+ word lines. Prioritize storytelling flow over compression. Wordiness acceptable if it serves narrative."

Question 4: Show vs. Tell Balance

question: "What balance of 'showing' vs. 'telling' should I expect?"
header: "Show/Tell"
multiSelect: false
options:
  - label: "Strongly Favor Showing"
    description: "Flag explicit statements. Push for implication over explanation. 80/20 show to tell ratio."

  - label: "Balanced (Recommended)"
    description: "Accept mix of showing and telling. Flag overly explicit or overly abstract. 60/40 show to tell."

  - label: "Allow Direct Statements"
    description: "Explicit emotional statements acceptable. Clarity prioritized over implication. 40/60 show to tell."

Collect user responses and store for parameter construction.

3. Sanitize Input:
   • Remove any mention of "AI-generated", "Claude", "LLM"
   • Frame neutrally: "Evaluate this song material for professional quality"

3.5. Construct Parameterized Prompt (NEW):

Append user preferences to the sanitized prompt:

## Evaluation Parameters (User-Specified)

**Specificity Standard:** {user_response_from_question_1}
**Contemporary Balance:** {user_response_from_question_2}
**Wordiness Tolerance:** {user_response_from_question_3}
**Show/Tell Balance:** {user_response_from_question_4}

Please adapt your evaluation criteria according to these user preferences. Consult the appropriate genre-specific reference guide:
- Pop: references/pop-evaluation-guide.md
- Indie/Folk: references/indie-folk-evaluation-guide.md
- Cross-reference: references/genre-evaluation-matrix.md

4. Launch Sub-Agent:

   • Use Task tool to invoke quality-reviewer agent
   • Pass: prompt text, lyrics text, minimal context (genre/mood/vocals), AND evaluation parameters
   • Sub-agent has independent context (no shared conversation history)
   • Sub-agent will apply genre-specific criteria based on parameters

5. Present Results:

   • Display structured feedback to user
   • Categorize recommendations by severity (CRITICAL/SUGGESTED/OPTIONAL)
   • Provide specific line numbers and actionable suggestions
   • Note which evaluation parameters were applied

Context Isolation

The quality-reviewer sub-agent:

• Has NO knowledge of conversation history
• Does NOT know content is AI-generated (if it is)
• Receives ONLY the prompt text, lyrics text, and basic context
• Evaluates against professional production standards
• Provides unbiased, independent quality assessment

Usage Examples

Example 1: Review Saved File

User: /review-song /Users/nathan/Development/suno/pop-songs-i-love/fixer-upper/prompt.md

Agent: Reading file and extracting content...
Agent: Launching quality-reviewer sub-agent...

[Quality reviewer provides feedback]

Agent: Review complete! Found 2 suggested improvements and 1 optional refinement.

Example 2: Review Direct Text

User: /review-song

Agent: Please paste your structured prompt (genre, vocal, instrumentation, production, mood):

User: [Pastes prompt text]

Agent: Please paste your lyrics:

User: [Pastes lyrics]

Agent: Extracting context and launching quality-reviewer sub-agent...

[Quality reviewer provides feedback]

Important Notes

Automatic from Main Workflow: When invoked from the main Suno Song Creator workflow (Step 7.5), this skill receives the prompt and lyrics automatically - no user input needed.

Standalone Usage: When invoked independently with /review-song, the user must provide either a file path or paste content manually.

No Bias: The quality-reviewer sub-agent has no knowledge of how the content was created. It evaluates all material against the same professional standards.

Iterative: Can be run multiple times on the same material to verify improvements after applying recommendations.

Implementation Details

Tool Usage:

• Uses Task tool to launch quality-reviewer sub-agent
• Uses Read tool when file path provided
• Uses AskUserQuestion for interactive text input when needed

Processing Steps:

1. Determine input mode (file path vs. direct text)
2. Extract or collect prompt + lyrics content
3. Parse to identify genre, mood, vocal style
4. Sanitize input (remove "AI", "generated", "Claude", "LLM")
5. Construct neutral review request
6. Launch quality-reviewer via Task tool with subagent_type="quality-reviewer"
7. Receive and display structured feedback

Context Sanitization Example:

❌ Bad input to sub-agent:
"Review this AI-generated Suno prompt I just created with Claude"

✅ Good input to sub-agent:
"Evaluate this bubblegum pop song prompt and lyrics for professional production quality"

Skill Integration

This skill can be:

• Invoked directly via /review-song for standalone reviews
• Called from main Suno Song Creator workflow (Step 7.5)
• Used to review old prompts stored in project directories
• Used to review prompts created by other tools/methods

No matter the source, the quality-reviewer provides objective, professional assessment.