Suno Music Prompt Generator

Problem It Solves

Suno-style AI music tools rely on natural-language prompts to shape genre, vocals, instrumentation, and mastering. Vague requests such as “a good pop song” often produce unstable results: the style becomes generic, the mood is unclear, the vocal does not fit the arrangement, or repeated generations drift away from the intended scene. This skill turns loose music ideas into structured English prompts for Suno while keeping Chinese translations, so you can review exactly what the model is being asked to generate.

How It Works

The skill organizes prompts around a practical parameter set:

• Structured parameters: Style, Mood, Instrument, Tempo, Vocal, Theme, Mastering, and Era, which make the intended music easier to control.
• Prompt templates: concise style mode, detailed description mode, and narrative scene mode, with examples for workout, film score, study, and sleep use cases.
• Bilingual keyword references: genres, moods, instruments, vocal types, mastering terms, and era labels, supporting English prompts with Chinese translation notes.

A typical workflow starts with the scene, emotion, and language, then selects one main genre, two or three core instruments, one vocal type, and optional Mastering or Era cues. If lyrics are needed, the topic, language, and narrative tone can be specified separately, such as “Chinese, motivational and uplifting.” It also enforces an output convention: each English prompt is paired with a Chinese translation, making it easier to verify that Style, Mood, and Vocal are expressed as intended.

Boundaries and Notes

This skill is best used for drafting Suno prompts, not for full arrangement, mixing, or mastering. References to artist styles, specific lyrics, and production terminology should still be checked against platform rules and the intended use. For instrumental output, explicitly use Instrumental to reduce the chance that the model adds vocals.