What problem does it solve? Writing effective prompts for AI music generation models is difficult: vague prompts produce inconsistent results, and tracks longer than the model's ~184-second limit suffer from jarring transitions between clips. This Skill provides a systematic framework for translating a musical vision into precise, model-executable prompts. ## Core Features & Use Cases - 9-Dimension Prompt Framework: Combines genre, tempo, key, mood, instrumentation, density, arrangement, soundscape, and production quality into a single cohesive prompt string. - Duration-Aware Strategy: Enforces single-call generation for tracks up to 180 seconds and applies a multi-clip continuity strategy with timestamp cues and intensity markers for longer pieces. - In-Text Negative Prompting & Control Emulation: Excludes unwanted elements (drums, vocals, fast tempos) and emulates advanced parameters like density, brightness, and mute-drums through natural language. - Use Case: A user requests a 6-minute cinematic score. The Skill plans the song structure, locks the sonic DNA (genre, BPM, production) across clips, aligns the ending state of each clip with the next, and specifies ffmpeg crossfades timed to the beat grid. ## Quick Start Use the music-prompter skill to write a generation prompt for a 60-second nostalgic lo-fi track at 80 BPM with Fender Rhodes and soft synth pads.
