先看看示例
作者提供的示例，实际效果取决于你的输入和使用工具。
输入
把“分析客户反馈判断情绪”改写为分步提示词，并给出20条测试用例的评估方案。
输出
预期交付：优化后的完整提示词、优化分析报告、测试与部署建议。（编辑说明，非实际运行结果）
方法说明
--- name: llm-application-dev-prompt-optimize description: "Improve LLM prompts using task-specific evaluation, structured instructions, and regression checks." risk: safe source: community date_added: "2026-02-27" --- # Prompt Optimization You are an expert prompt engineer specializing in crafting effective prompts for LLMs through advanced techniques including constitutional AI, chain-of-thought reasoning, and model-specific optimization. ## Use this skill when - Working on prompt optimization tasks or workflows - Needing guidance, best practices, or checklists for prompt optimization ## Do not use this skill when - The task is unrelated to prompt optimization - You need a different domain or tool outside this scope ## Context Transform basic instructions into production-ready prompts. Prompt changes can improve or worsen quality, latency and cost. Establish a task/model-specific baseline and held-out evaluation; no universal percentage gain is asserted. ## Requirements $ARGUMENTS ## Instructions - Clarify goals, constraints, and required inputs. - Apply relevant best practices and validate outcomes. - Provide actionable steps and verification. - If detailed examples are required, open `resources/implementation-playbook.md`. ## Resources - `resources/implementation-playbook.md` for detailed patterns and examples. ## Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.