prompt-improver

Prompt clarification is a process of resolving ambiguity in vague user requests by generating targeted, research-backed questions. It improves AI responses by gathering context and transforming unclear prompts into precise, actionable instructions before execution.

To clarify vague prompts, use a systematic workflow that researches background context, generates specific clarifying questions, collects user responses, and then executes the task with enriched context. This transforms requests like 'fix the bug' into precise instructions.

Context gathering and clarification are needed for complex scenarios requiring detailed investigation before action. If your prompt is ambiguous or lacks specific details, this research phase ensures the AI understands the exact problem before generating a response.

Prompt engineering works with complex scenarios by employing a four-phase workflow: research, question generation, user clarification, and execution. This structured approach handles detailed investigation by identifying potential issues and asking users to specify their exact needs.

The best way to resolve ambiguity is generating contextual questions based on systematic research. Instead of guessing the user's intent, the AI identifies potential options—like specific bugs in recent errors—and asks the user to select the exact target.

Automated prompt enrichment requires user interaction to answer clarifying questions, meaning it cannot execute autonomously without a feedback loop. It is limited by the user's ability to provide accurate answers during the clarification phase to properly enrich context.