Momento/.agent/skills/suno-feedback-elicitor/references/feedback-triage-guide.md

Feedback Triage Guide

Last validated: March 2026 (updated for v5.5). Elicitation techniques are craft-based (not Suno-specific) and do not require frequent re-validation. The Suno parameter mappings in the opposing pairs table should be verified via web search if Suno model behavior has changed since this date.

Classification Rules

Clear Feedback

Signals: Specific nouns (guitar, vocals, bass, drums, tempo), comparative statements ("too much," "not enough," "louder," "softer"), direct requests ("add," "remove," "change").

Examples:

• "The electric guitar is too prominent"
• "I need a bridge between the second chorus and the outro"
• "The vocals sound too autotuned"
• "It's too fast — slow it down"
• "The drums overpower everything"

Action: Map directly to parameter adjustments. No elicitation needed.

Positive Feedback

Signals: Approval language ("love it," "great," "perfect," "nailed it"), evolution requests ("can we try," "what if," "now make it"), preservation language ("keep the," "don't change").

Examples:

• "This is exactly what I wanted!"
• "Love the vocals — can we try a darker instrumental?"
• "Perfect energy. What about a version with more acoustic guitar?"
• "Keep everything but make the chorus hit harder"

Action: Identify what to preserve (anchor), then explore evolution direction. Suggest saving successful elements to band profile.

Vague Feedback

Signals: Feeling-based language without specifics ("off," "not right," "something's missing," "doesn't feel like"), hedging ("I don't know," "hard to explain," "it's just"), negation without alternative ("I don't like it," "that's not it").

Examples:

• "Something about it just isn't right"
• "It doesn't feel like what I imagined"
• "I don't know, it's missing something"
• "It's close but not there yet"
• "The vibe is off"

Action: Three-phase guided elicitation (binary narrowing → comparative anchoring → emotional vocabulary bridge).

Contradictory Feedback

Signals: Opposing descriptors in same feedback ("more X but also more Y" where X and Y conflict), sequential reversals ("actually no, I want..."), wanting everything changed but nothing changed.

Examples:

• "Make it more energetic but also more relaxed"
• "I want it raw and lo-fi but also radio-ready"
• "The vocals should be more prominent but also blend in more"
• "It needs to be simpler but also more interesting"

Action: First Principles reset — find the one anchor, rebuild from there. Reframe contradictions as potential structural insights (verse vs. chorus contrast). When the contradiction spans multiple dimensions (arrangement + lyrics + delivery), use three-pass layered prompting to isolate changes: adjust concept/mood first, then lyrics/structure, then performance cues — never all at once. See suno-parameter-map.md "Three-Pass Layered Prompting" for the workflow.

When feedback touches both vocal identity and style: If the user wants to change the singing voice AND the musical direction simultaneously, apply the one-variable-at-a-time rule — adjust either the Persona/vocal identity OR the style prompt, not both in the same generation. Changing both creates compounding unpredictability. Persona controls artist identity (vocals, character); style prompt controls the producer brief (genre, mood, arrangement).

Technical/Quality Feedback

Signals: Quality-specific language ("glitchy," "robotic," "artifact," "clipping," "distortion," "cuts off"), timestamp references ("at 1:23"), pronunciation complaints, audio fidelity terms ("muffled," "compressed," "tinny"), generation-specific issues distinct from creative direction.

Examples:

• "There's a weird glitch at 1:23"
• "The vocals sound robotic in the second verse"
• "The audio quality drops toward the end"
• "It mispronounces the word 'ethereal'"
• "There's clipping in the chorus"

Action: Route to Suno Studio features (Replace Section, Warp Markers, Remove FX) or regeneration. These issues are typically generation-specific, not prompt-specific — try regenerating 3-5 times before modifying the prompt. See suno-parameter-map.md "Audio Quality & Artifacts" and "Suno Studio Resolution Paths" sections.

v5.5 recommended approach: Use the generate -> inspect -> refine workflow rather than regenerating from scratch. If the structure and melody are good, use section replacement for the problem area instead of full regeneration. Only regenerate fully when the structure or emotional direction is fundamentally wrong. See suno-parameter-map.md "v5.5 Workflow Paradigm" for the full decision framework.

Voice & Custom Model Feedback Patterns

When the user has a Voice or Custom Model active, technical feedback often maps to these specific issues:

Feedback	Root Cause	Resolution Path
"Vocals don't sound like me" (Voice active)	Audio Influence too low, poor source recording quality, or style prompt overriding Voice identity	1. Increase Audio Influence — start at 55-70%, go to 75-85% if identity is paramount (see use-case table in suno-parameter-map.md). 2. Re-record a cleaner voice sample (less background noise, consistent mic distance). 3. Use delivery metatags ([Whispered], [Belted]) instead of style prompt vocal descriptors — the Voice provides identity, metatags shape performance.
"Production doesn't match my style" (Custom Model active)	Generic prompt descriptors being absorbed by the model's trained defaults	1. Use more specific prompt overrides — name the exact elements to change rather than broad descriptors. 2. If the model consistently misses the target, retrain with a better-curated catalog that more accurately represents the desired production style.
"Voice sounds right but delivery is wrong" (Voice active)	Style prompt vocal descriptors conflicting with Voice identity	Remove vocal descriptors from the style prompt. Use delivery metatags in the lyrics field instead: [Whispered], [Belted], [Tender], [Aggressive]. The Voice handles identity; metatags handle performance.
"Changed multiple things and now it's worse" (Voice + Custom Model)	Multiple simultaneous changes making it impossible to isolate the cause	Apply the one-variable-at-a-time rule: adjust delivery metatags first, then Audio Influence, then style prompt. Regenerate after each single change.

Production Diagnostic Patterns

Common feedback patterns with non-obvious root causes. When you hear these, check the indicated sources before adjusting the style prompt.

Feedback Pattern	Check First	Root Cause & Fix
"Guitar dominates / bass not prominent enough"	Genre context (rock/metal?) + instrumental sections	Bass prominence is a known Suno limitation in rock/metal. Try: remove "guitar" mentions from style prompt, add guitar to exclusions, use [Instrument: bass] tags (unreliable but worth trying). Bass-forward rock/metal is currently not achievable reliably.
"Ending is too loud / song doesn't come down"	Style prompt for unidirectional build language ("crescendo dynamics", "build to crushing climax")	The style prompt must describe the full arc, not just the build. Replace with slow build then fade or dynamic shifts loud to quiet.
"Wrong bass tone"	Whether "funk" appears in style prompt	"Funk" triggers slap/pop bass (Flea/Claypool style). For overdriven fingerstyle bass (Geddy Lee style), remove "funk" entirely.
"Song sounds too modern / wrong era"	Whether a Persona is loaded	Personas anchor sound to the era of the source song. Reduce Audio Influence to 10-15% or generate without Persona for era-specific pieces.
"Vocals are screaming when they shouldn't be"	Style prompt for metal, sludge, doom; lyrics for ! or ALL CAPS	These are scream triggers. Fix: add explicit positive vocal instructions (e.g., "clean vocals, melodic singing"), remove triggers, use [Vocal Style: whispered] to reset after aggressive sections.
"Song loops / too much instrumental"	Source text length (under 15 lines?) + style prompt for instrumental breaks	Short lyrics cause looping and filler instrumentals. Suggest: double the delivery (repeat verses with variation), extract and repeat chorus, or place a hard [End] tag.
"Sound is too theatrical / too many keyboards"	Style prompt for baroque, rock opera, cinematic, or orchestral	These keywords trigger keyboard-heavy theatrical arrangements. Fix: describe desired qualities without those words; specify heavy orchestral instruments by name (cello, heavy strings, kettle drums); use "power ballad" instead of "rock opera" for dynamic range.
"Song doesn't come back down / ending stays loud"	Whether the dynamic arc is stated TWICE in the style prompt	A single mention of descent isn't enough — Suno latches onto the loudest directive. Both building from gentle to crushing then returning to gentle AND dynamic arc quiet to massive to quiet are needed to reliably produce a full arc.
"One section sounds wrong but the rest is fine"	Whether the issue is section-specific or global	Use parameterized section tags for per-section fixes: [Verse: whispered vocals, acoustic guitar only], [Chorus: full band, powerful vocals]. This targets the problem section without changing the overall style prompt. See suno-parameter-map.md "Parameterized Section Tags".

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Elicitation Techniques

Binary Narrowing

Rapid yes/no or A/B questions to reduce the problem space. Goal: identify which dimension(s) need adjustment in under 5 questions.

Dimension checklist:

1. Music/production vs. vocals/singing
2. Energy level (too high / too low / right)
3. Structure (sections, flow, length)
4. Lyrics (content, delivery, phrasing)
5. Overall vibe/mood (right neighborhood or wrong direction)

Rules:

• Ask one question at a time
• Accept partial answers — "kind of both" is useful signal
• If they narrow to a single dimension in 2 questions, skip ahead to Phase 2

Comparative Anchoring

Use reference points the user knows to triangulate what they want.

Techniques:

• Artist/song reference: "Name a song that has the feel you're going for"
• Spectrum placement: "If 1 is [extreme A] and 10 is [extreme B], where is it now and where do you want it?"
• A/B contrast: Suggest two contrasting descriptions and ask which is closer to their vision
• Temporal reference: "Think of the last song that made you feel the way this one should — what was it?"

Rules:

• Don't require musical knowledge — "a movie scene" or "a feeling" works too
• If they give a reference, decompose it into concrete audio characteristics (instrumentation, tempo, vocal style, production quality, energy)

Emotional Vocabulary Bridge

Map subjective feelings to Suno-actionable parameters.

Core opposing pairs and their Suno parameter mappings:

Pair	Low End → Suno	High End → Suno
Heavy ↔ Light	Dense instrumentation, layered, bass-heavy, thick	Sparse arrangement, airy, minimal, delicate
Fast ↔ Slow	Driving rhythm, uptempo, energetic beat	Slow tempo, laid-back groove, gentle pace
Polished ↔ Raw	Radio-ready mix, clean production, crisp	Lo-fi, organic, rough edges, imperfect
Familiar ↔ Weird	Classic genre conventions, traditional	Experimental, unexpected, genre-bending (↑ Weirdness slider)
Warm ↔ Cold	Analog warmth, rich tones, close mics	Crystalline, digital, distant, sterile
Intimate ↔ Epic	Close, quiet, small room, whispered	Wide stereo, big reverb, anthemic, soaring
Smooth ↔ Gritty	Clean vocals, flowing melody, polished	Raspy, distorted, textured, rough
Bright ↔ Dark	Major key feel, uplifting, shimmering	Minor key feel, moody, deep, shadowy
Tight ↔ Loose	Precise timing, quantized, controlled	Swing, human feel, organic timing, relaxed
Simple ↔ Complex	Minimal arrangement, few instruments, straightforward	Layered, intricate arrangement, multiple textures (↑ Weirdness slider)
Organic ↔ Synthetic	Live instruments, acoustic, natural, analog warmth	Electronic, digital, synthesized, programmed beats
Atmospheric ↔ Punchy	Reverb, space, ambient pads, "atmospheric"	Low-end presence, tight transients, "punchy"
Lo-fi Warmth ↔ Polished Radio-Ready	Vintage character, low-pass filtering, "lo-fi warmth"	Clean, modern, commercial mix, "polished radio-ready"
Driving ↔ Lush	Forward momentum, energetic basslines, "driving"	Layered pads, dense production, "lush"
Raw Live ↔ Produced	Less processed, room sound, "raw live recording"	Spatial separation, "wide stereo", processed

Rules:

• Only present pairs relevant to the narrowed dimension
• Ask them to place the current output AND their desired target on the spectrum
• The gap between "where it is" and "where they want it" determines adjustment magnitude
• If binary narrowing does not converge after 4 questions, pivot to reference-first: "Name a song that sounds like what you wanted — I'll work backwards from there." Reference decomposition is often easier than dimensional analysis for non-musicians.
• If elicitation still does not converge, suggest generating 2-3 variants with different parameter profiles and letting the user compare (turns an elicitation problem into a selection problem).

First Principles Fallback

When feedback is contradictory or elicitation isn't converging.

The anchor question: "If you could only keep ONE thing about this song exactly as it is, what would it be?"

Rebuild sequence:

1. Lock the anchor — this does not change
2. For each remaining dimension, offer two options anchored to the keeper
3. Build up layer by layer, checking for contradiction at each step
4. If a new contradiction emerges, reframe as structural contrast (verse vs. chorus, intro vs. drop)

Borrowed from: Socratic Questioning, 5 Whys, First Principles Analysis (BMad Advanced Elicitation methods).