What problem does it solve?
Converts messy, unstructured user input—such as voice transcriptions, stream-of-consciousness notes, and rough document dumps—into clear, actionable prompts optimized for Claude models, reducing friction and clarifying intent before execution.
Core Features & Use Cases
- Voice cleanup: Removes filler words, false starts, and verbal tics, and normalizes spoken patterns into well-punctuated written text.
- Intent extraction & gap detection: Identifies core task, referenced files, constraints, preferences, and success criteria, then generates all necessary clarifying questions when information is missing.
- Model-aware optimization & preview: Applies Claude Opus/Sonnet best practices, structures prompts with XML-like sections for complex tasks, and presents a polished prompt for user approval before execution.
- Use Case: Turn a noisy meeting transcription into a concise, model-ready task description that specifies success criteria and required files.
Quick Start
Polish this meeting transcription into a concise Claude-ready prompt that extracts the core task, lists any missing details, and returns a polished prompt for my approval.
