prompt-optimizer

The prompt-optimizer skill is designed to assist users in refining and enhancing their draft prompts without executing any tasks directly. It addresses a common challenge where users struggle to articulate precise prompts for AI or ECC ecosystem components, often leading to suboptimal results. By analyzing the user's input, identifying intent and gaps, and mapping the prompt to relevant ECC skills, commands, agents, or hooks, this skill generates a polished, ready-to-use prompt that maximizes clarity and effectiveness. Importantly, it functions in an advisory capacity and never runs the tasks described in the prompt itself, ensuring a clear separation between optimization and execution.

Key features of prompt-optimizer include multi-phase analysis, beginning with project context detection, which identifies tech stacks and project conventions to tailor suggestions. It then classifies user intent into categories such as new features, bug fixes, refactoring, research, testing, documentation, and review. The skill provides actionable feedback by highlighting gaps, suggesting improvements, and producing a refined prompt. It supports both English and Chinese trigger phrases, and explicitly avoids triggering for unrelated requests such as code optimization or direct task execution, maintaining precise focus on prompt quality enhancement.

This skill is particularly useful for developers, technical writers, and AI practitioners who need guidance on how to phrase their prompts for ECC ecosystem tools effectively. Typical use cases include improving a prompt for generating code snippets, research instructions, test cases, or documentation. It also supports users who are new to ECC or AI prompting, providing a structured approach to crafting well-formed prompts. By using prompt-optimizer, users can save time, reduce trial-and-error in prompt design, and ensure that their instructions are clear, context-aware, and actionable.