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:

Read the file automatically
Extract prompt sections and lyrics
Launch quality-reviewer sub-agent
Present structured feedback

Mode 2: Review Direct Text

When pasting prompt + lyrics directly:

/review-song

The skill will:

Prompt you to paste your structured prompt
Prompt you to paste your lyrics
Extract genre/mood context
Launch quality-reviewer sub-agent
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

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

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

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
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:

Determine input mode (file path vs. direct text)
Extract or collect prompt + lyrics content
Parse to identify genre, mood, vocal style
Sanitize input (remove "AI", "generated", "Claude", "LLM")
Construct neutral review request
Launch quality-reviewer via Task tool with subagent_type="quality-reviewer"
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.