What problem does it solve? Writing effective prompts for AI music generation models is difficult: vague prompts produce inconsistent results, and requests longer than the model's ~184-second limit fail or sound disjointed. This Skill provides a systematic framework for translating a user's musical vision into precise, structured prompts that the model can execute reliably. ## 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 asks for a 6-minute lo-fi study track. The Skill plans the song structure, locks the musical DNA (genre, BPM, production) across clips, aligns clip boundaries with timestamp cues, and finishes with ffmpeg crossfades for seamless concatenation. ## Quick Start Ask the AI to generate a music prompt for a 60-second nostalgic lo-fi track at 80 BPM with Fender Rhodes and soft synth pads, instrumental only.
