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prompt-engineer提示工程师

Agent Skill

用于辅助提示词、系统指令、Agent 行为约束和工作流模板的整理。它适合让 Agent 规范任务边界、统一输出格式、拆分操作步骤或优化提示词可复用性。使用时需要保留真实业务约束,不要把示例当硬规则;涉及自动执行、外部工具或高风险操作时,应在提示词中明确确认步骤、权限边界和失败处理方式。

总安装

235

周安装

10

GitHub Stars

49

下载量

82
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:prompt-engineer(提示工程师)
来源仓库:https://github.com/nityeshaga/claude-code-essentials
仓库路径:skills/prompt-engineer
安装命令:
npx skills add https://github.com/nityeshaga/claude-code-essentials --skill prompt-engineer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/nityeshaga/claude-code-essentials --skill prompt-engineer

简介

用于辅助提示词、系统指令和工作流模板的整理。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中规范任务边界或拆分操作步骤。
  • 通过 npx 命令安装,需保留真实业务约束。
  • 涉及自动执行时应明确确认步骤和权限边界。
  • prompt-engineer 属于AI 工具类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Prompt Engineer

This skill helps create high-quality prompts and instructions for AI systems by treating AI as a genius human teammate who needs clear, context-rich communication.

Core Philosophy

This skill is built on two foundational principles:

  1. The Genius Intern Framework: Treat AI like a brilliant generalist who can figure things out but needs context about what "good" looks like in your specific situation
  2. Async Remote Teammate: Write for AI the way you'd write for a smart remote colleague—clear, comprehensive, and decisively opinionated

Modern AI models have both high intelligence and high emotional intelligence. They don't need tricks or "prompt engineering hacks"—they need what any smart remote teammate needs: clear written communication with sufficient context.

Reference Materials

This skill includes three core reference documents. Read them in full as needed:

Always Load First

Writing for AI Teammates - Core philosophy covering:

  • Why "prompt engineering" is about clear writing, not tricks
  • The 37signals parallel (async remote culture)
  • Brevity-clarity balance
  • Progressive disclosure ("inverted pyramid")

Load this file at the start of every prompt creation task. It's your primary reference.

Then Load Prompt Framework

Prompt Framework - Comprehensive guide covering:

  • Three prompt types (Do This / Know How / Learn Domain)
  • Universal principles (examples with reasoning, decision frameworks, visual structure)
  • Type-specific patterns and structures
  • Anti-patterns to avoid

Always load read this detailed framework to understand best practices based on how Anthropic writes their prompts.

Load Only for GPT-5 Targets

GPT-5 Prompting Guide - GPT-5-specific patterns:

  • Avoiding contradictory instructions (critical for GPT-5)
  • Calibrating autonomy vs asking questions
  • Tool preambles and progress updates
  • Self-reflection for quality
  • Planning protocols

Only load this file if the user explicitly mentions they're targeting GPT-5, OpenAI models, or asks for GPT-5 optimization after seeing the initial draft.

Workflow

1. Understand the Request

When the user asks for help with a prompt, quickly assess:

Type of prompt needed:

  • Do This (single task execution)
  • Know How (reusable capability/tool)
  • Learn Domain (acquire knowledge then execute)

Available context:

  • What's the AI being asked to do?
  • Who's the audience for the output?
  • What does success look like?
  • Are there examples of good/bad outputs?
  • What constraints exist?

2. Gather Missing Info (Intelligently)

Be smart about asking questions. Ask if:

  • You genuinely can't determine the prompt type
  • Critical context is completely missing (e.g., no idea what the AI should actually do)
  • Multiple valid interpretations exist with very different outcomes
  • Output format is not clear

Don't ask if:

  • You have sufficient context to create a solid first draft
  • The user has been comprehensive in their initial request
  • Questions would be nitpicky rather than substantive

3. Create the Prompt

Load the Prompt Framework reference first, then:

  1. Choose the right structure based on prompt type:

- Do This: Purpose → Success Criteria → Examples → Constraints - Know How: Purpose → When to Use → Examples with Reasoning → Mechanics - Learn Domain: Foundation → Study → Synthesis → Execution → Validation

  1. Apply universal principles:

- Be decisively opinionated - Show examples with reasoning (good AND bad) - Provide clear decision frameworks - Address common mistakes proactively - Use visual structure for complex anatomy - Scale complexity to judgment required

  1. Avoid anti-patterns:

- Don't explain basic concepts AI already knows - Don't apologize or hedge - Don't be excessively polite - Don't list every edge case - Don't add motivational statements - Don't over-specify process - Don't overfit on given examples by including said examples in the prompt

4. Create as File

Always create the prompt as a markdown file.

5. GPT-5 Optimization (if needed)

After creating the prompt, ask: "Will this be used with GPT-5 or OpenAI models?"

If yes, you MUST load the GPT-5 Prompting Guide and perform a revision pass:

Official GPT-5 prompting guide

Remember

You're not doing "prompt engineering"—you're helping someone communicate clearly with an intelligent teammate. Focus on clarity, context, and decisiveness. Trust the AI to be smart; give them what they need to be effective in your specific context.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

28.69%
按下载量换算24

windsurf

23.12%
按下载量换算19

OpenCode

17.67%
按下载量换算14

Cursor

13.41%
按下载量换算11

Codex

7.25%
按下载量换算6

Antigravity

3.39%
按下载量换算3

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

来源信息

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