suno-feedback-elicitor

suno-feedback-elicitor is a skill for Claude Code from zarlor/suno-band-manager. It costs 46 tokens per session (5,632 once invoked), scanned A, original, MIT.

A guided feedback workflow for improving music generated by Suno, an AI music-generation service.

In plain words
What is it for?
Collecting and clarifying feedback, suggesting prompt or lyric adjustments, and identifying when a song may need regeneration or editing.
Why use it?
It helps turn reactions such as “the vocals feel wrong” into specific changes, even when the listener does not know the musical term.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the suno-band-manager plugin — 7 skills shipped together

Good fit Collecting and clarifying feedback, suggesting prompt or lyric adjustments, and identifying when a song may need regeneration or editing.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zarlor/suno-band-manager/suno-feedback-elicitor
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add zarlor/suno-band-manager --skill suno-feedback-elicitor
Clone the repo
git clone --depth 1 https://github.com/zarlor/suno-band-manager

Made for: Claude Code.

Or install suno-band-manager, the plugin that ships this one along with the rest of its 7 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for suno-feedback-elicitor

README.md
[![agentmods](https://agentmods.dev/badge/skills/zarlor/suno-band-manager/suno-feedback-elicitor/github.svg)](https://agentmods.dev/skills/zarlor/suno-band-manager/suno-feedback-elicitor)
Your own site
<a href="https://agentmods.dev/skills/zarlor/suno-band-manager/suno-feedback-elicitor"><img src="https://agentmods.dev/badge/skills/zarlor/suno-band-manager/suno-feedback-elicitor/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for suno-feedback-elicitor

Your own site · 80×15
<a href="https://agentmods.dev/skills/zarlor/suno-band-manager/suno-feedback-elicitor"><img src="https://agentmods.dev/badge/skills/zarlor/suno-band-manager/suno-feedback-elicitor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,632 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00046 $0.05632
Opus 5 $0.00023 $0.02816
Sonnet 5 $0.00009 $0.01126
Haiku 4.5 $0.00005 $0.00563

Measured 11d ago against content hash 98a06a73d50e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

suno-feedback-elicitor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

The scan reads SKILL.md. This mod also ships 17 executable files (scripts/analyze-audio.py, scripts/audio-deep-analysis.py, scripts/audio-files-manifest.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

src/skills/suno-feedback-elicitor/SKILL.md · 253 lines

How it starts

The opening of the file, as written. The whole thing — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Feedback Elicitor

Overview

Translates subjective musical reactions into concrete parameter adjustments for the Style Prompt Builder and Lyric Transformer via guided elicitation or headless structured input. Act as a music producer's A&R collaborator, bridging the vocabulary gap between what users feel and what Suno needs to hear -- plain language first with the technical term parenthetically ("make the vocals sit further back (reduce vocal prominence in the style prompt)").

Domain context: The agent cannot hear songs. Users range from musicians with deep vocabulary to listeners who "know what they like." Five feedback types (clear, positive, vague, contradictory, technical) each need different elicitation. Technical/quality issues often need regeneration or post-generation editing rather than prompt changes.

Design rationale (load-bearing constraints):

  • Feedback is always valid. If the user feels something is off, something is off -- even if they can't name it.
  • Triage before elicitation. Strategies differ dramatically per feedback type; never one-size-fits-all. This is the skill's core structural bet.
  • The emotional vocabulary bridge is the differentiator. Most users can say "it feels too busy" but not "reduce instrumentation density." Mirror the user's own words -- if they say "crunchy," use "crunchy," not "distorted"; renaming their term breaks the bridge you are building.
  • Keep elicitation conversational, not clinical. "Does it feel too busy or too empty?" not "Rate the instrumentation density on a scale of 1-10." Rating scales for subjective reactions produce worse signal than plain questions.
  • Minimum viable context. Ask for the style prompt first; gather everything else only as feedback demands.
  • Prompt changes before regeneration. Exhaust parameter adjustments before suggesting full regeneration.
  • Preserve what works. Never recommend changes that risk breaking elements the user already likes.
  • Round-awareness. On subsequent rounds, front-load what was tried and what worked/didn't before re-triaging.

Read the full file on GitHub · 253 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 253 lines · 46 tokens per session scan A 98a06a73d50e

Subscribe to this mod's changes

suno-feedback-elicitor is a skill published in the GitHub repository zarlor/suno-band-manager (11 stars, last pushed 27d ago), licensed MIT. It adds 46 tokens to every session and 5,632 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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