Diagnose lyric problems across prosody, rhyme, meaning, register, sound, and structure. Use when AI-generated or human lyrics feel flat, cliched, awkward, or mismatched.
You diagnose lyric problems across multiple dimensions. Your role is to identify why lyrics fail and guide writers (human or AI) toward more effective choices.
Lyrics fail in predictable, diagnosable ways. Generic is not neutral—generic is bad.
AI-generated lyrics cluster at statistical distribution centers: the most probable word choices, rhyme pairs, and emotional vocabulary. Probability optimization produces mediocrity. Effective lyrics require intentional deviation from defaults.
The same pattern that makes "Celtic" trigger tinwhistle in music generation makes "love" trigger predictable rhyme pairs and emotional cliches in lyric generation.
Symptoms: Predictable rhyme pairs dominate. Word choices are first-associations. Nothing surprises. Lyrics could fit any song on this topic.
Key Questions:
Diagnostic Checklist:
Stock Phrases (phrase-level cliches, not just words):
Scripts can't catch these—they require semantic judgment:
| Phrase | Category | Why It's Cliche |
|---|---|---|
| "screaming inside" | unexpressed anguish | Every song about hidden pain uses this |
| "need you gone" | direct desire | States want instead of showing it |
| "won't leave me alone" | persistence | Generic memory/thought complaint |
| "thought I died" | emotional death metaphor | Overused intensity marker |
| "used to be" + past state | nostalgia setup | Stock before/after framing |
| "look in your eyes" | connection | Vague romantic gesture |
| "torn apart" | destruction | Abstract violence metaphor |
| "can't let go" | attachment | States the problem directly |
Lazy Rhyme Pairs (rhyme drove word choice):
| Pair | Problem |
|---|---|
| desire / fire / tired | Cluster appears together constantly |
| inside / died / alive | Death-interior cluster |
| away / stay / day | Motion-time cluster |
| heart / apart / start | Heart-destruction cluster |
| alone / gone / on | Isolation cluster |
Interventions:
cliche-check.ts as pre-filter (surfaces candidates, doesn't diagnose)Symptoms: Lines don't fit the melody. Stresses fall on wrong syllables. Unnatural pronunciation required. Syllables crammed or stretched awkwardly.
Key Questions:
Diagnostic Checklist:
Interventions:
meter-check.ts to analyze syllable counts and stress patternsSymptoms: Lyrics say exactly what they mean and nothing more. No subtext, no layers, no depth. Emotions are stated directly. Everything is on the surface.
Key Questions:
Diagnostic Checklist:
Interventions:
Symptoms: Lyric tone contradicts the music's emotion. Casual words over dramatic instrumentation. Heavy lyrics over light music. Vocabulary doesn't match genre expectations.
Key Questions:
Diagnostic Checklist:
Interventions:
Symptoms: No attention to how words feel in the mouth. Harsh consonant clusters at tender moments. Monotonous vowel sounds. No alliteration, assonance, or deliberate sound texture.
Key Questions:
Diagnostic Checklist:
Interventions:
Symptoms: No identifiable hook. Verse and chorus feel interchangeable. Repetition is annoying, not reinforcing. Bridge doesn't contrast. Song has no arc.
Key Questions:
Diagnostic Checklist:
Structural Cliches:
| Pattern | Problem | Fix |
|---|---|---|
| Bridge = Verse | Not a bridge at all—just more of the same | Shift perspective, time, or speaker |
| Chorus expands on repeat | Adding lines without development | Each chorus iteration should mean more |
| Hook repeated without exploration | Says the phrase but never unpacks it | What does the hook mean? Show us. |
| No arc | Emotional state same at end as beginning | Something must change—realization, acceptance, escalation |
| Verses say same thing differently | Verse 2 is Verse 1 with synonyms | Each verse needs new information or angle |
Interventions:
Listen without analyzing. Note:
Which of the six states best describes the main problem?
For the primary state:
cliche-check.ts, meter-check.ts, etc.)Often multiple states co-occur:
Fix the most damaging issue first:
Pattern: Fixing one problem introduces new problems. Every change cascades.
Signs:
Why It Fails: Lyrics are an interconnected system. Point fixes ignore system effects.
Fix: Make one change, then re-read holistically. Don't chain fixes without checking the whole.
Pattern: Chasing complexity for its own sake. Obscurity mistaken for depth.
Signs:
Why It Fails: Obscure isn't deep. Listeners need access point.
Fix: Every obscure element needs a clear anchor. Complexity serves clarity, not replaces it.
Pattern: Adopting genre vocabulary without understanding function.
Signs:
Why It Fails: Genre vocabulary is shortcut to function. Without function, it's costume.
Fix: Understand what the genre element does, then deploy it for that purpose.
Pattern: Refusing to revise lines that came easily.
Signs:
Why It Fails: First drafts capture intuition but include noise. Signal needs extraction.
Fix: Save first draft separately. Revise as if someone else wrote it.
AI-generated lyrics (Suno, etc.) fail in predictable ways due to how LLMs work:
Why this happens:
Two forces compound:
Statistical median pull: LLMs generate the most probable next token. For lyrics, this means the most common rhyme pairs, the most frequent emotional vocabulary, the most typical phrase structures. Probability optimization produces mediocrity.
Completion reward bias: Training for "helpful" weights goal completion over thoroughness or quality. The model treats "rhyme achieved" as success, regardless of whether it's an interesting rhyme. Structure complete > structure meaningful.
This is the same mechanism documented in the Sequential Focus framework—forward reference gravitational pull. The model sees the target (rhyme, line end, verse completion) and races toward the most probable path rather than exploring alternatives.
Pre-anchor end words: Write the rhyme words yourself with intentional non-cluster choices. Force the model to land on words without lazy partners. If you avoid "fire," you break the fire/desire/tired cluster.
Seed with concrete imagery: Opening lines set the vocabulary space. Concrete, unusual imagery early may hold off statistical collapse longer than abstract emotional vocabulary.
Isolate sections: Generate verse 1 alone, evaluate, then generate verse 2 with explicit instruction to avoid verse 1's rhyme families. Treat each section as a separate generation task.
Blacklist clusters: Explicitly forbid the lazy rhyme clusters in prompts:
Provide slant rhyme alternatives: Give the model escape routes. "Instead of perfect rhymes, use slant rhymes like home/come, love/move."
The same principle that makes Sequential Focus work for agent tasks applies to lyric generation: hide the end goal, make each phase complete.
Don't prompt "write a complete song about X." Instead:
Each step is the complete mission. The model can't race to "song complete" if it doesn't know a song is the goal.
These scripts surface candidates for LLM/human interpretation. They do NOT make diagnostic judgments. Use their output as input to your analysis, not as the analysis itself.
Why pre-filters?
cliche-check.tsSurfaces Tier 1/2 terms from lyric-dominance-rules.json. You must evaluate in context.
Usage: bun run scripts/cliche-check.ts "your lyrics here"
Limitations: Misses stock phrases, rhyme-driven word choice, semantic cliche.
meter-check.tsReports syllable counts, stress patterns, and variance. You must judge if variance is intentional.
Usage: bun run scripts/meter-check.ts "your lyrics here"
Useful for: Identifying lines that need review, spotting high variance.
rhyme-check.tsMaps rhyme scheme and identifies rhyme types. You must evaluate rhyme quality.
Usage: bun run scripts/rhyme-check.ts "your lyrics here"
Limitations: Marks gerund-gerund (-ing/-ing) as rhymes. Marks same-semantic-field pairs as rhymes. Doesn't detect rhyme-forced word choice.
| State | Core Problem | First Question | Primary Fix |
|---|---|---|---|
| LY1 | Predictable | Are rhymes first-associations? | Replace cliche terms |
| LY2 | Unsingable | Do stresses match beats? | Count syllables, swap words |
| LY3 | Empty | Is there subtext? | Add concrete imagery |
| LY4 | Mismatched | Does tone match music? | Align vocabulary to intensity |
| LY5 | Harsh | How do words feel in mouth? | Map sounds to emotions |
| LY6 | Aimless | Where's the hook? | Define and place hook |