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Agent Skill · AI 工具

prompt-engineer(提示工程师)

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。

prompt-engineer 是AI 工具类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证为 MIT,第三方扫描已通过,按安装量在AI 工具类的 2,536 个 Skill 里排第 2,338。

总安装 235周安装 10GitHub Stars 49下载 82核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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

这个 Skill 是做什么的

AI 工具类 Skill 用来扩展助手本身的能力,例如接模型、接检索、接外部服务。

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。

来源仓库内路径:skills/prompt-engineer

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/nityeshaga/claude-code-essentials --skill prom…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

prompt-engineer 怎么安装?

在终端执行 npx skills add https://github.com/nityeshaga/claude-code-essentials --skill prompt-enginee…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

prompt-engineer 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

prompt-engineer 需要什么权限?

权限级别是只读。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。

prompt-engineer 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

prompt-engineer 用的人多吗?

公开数据是累计安装 235 次,近一周安装 10 次,下载 82 次,GitHub 49 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

prompt-engineer 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理AI 工具类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

AI 工具类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
executing-plans

执行计划 · Codex、Claude

1,515,336173,110只读MIT通过
verification-before-completion

完成前的验证 · Codex、Claude

1,319,472173,121权限未标注MIT通过
subagent-driven-development

子 Agent 驱动开发 · Codex、Claude

1,312,416173,138只读MIT通过
copy-editing

复制编辑 · Codex、Claude

1,209,57625,632只读MIT通过
paywall-upgrade-cro

付费专区升级 cro · Codex、Claude

1,030,17625,617只读MIT通过
prompt-engineer

提示工程师 · 本页

23549只读MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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.

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。

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