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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

1,830

周安装

77

GitHub Stars

21

下载量

641
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/shipshitdev/library
仓库路径:skills/prompt-engineer
安装命令:
npx skills add https://github.com/shipshitdev/library --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/shipshitdev/library --skill prompt-engineer

简介

prompt-engineer 用于辅助提示词、系统指令和工作流模板的整理。

  • 适合规范任务边界、统一输出格式或优化提示词可复用性。
  • 使用时需保留真实业务约束,避免将示例当硬规则执行。
  • 涉及自动执行或高风险操作时,应明确确认步骤和权限边界。
  • 适用于 AI Agent 行为优化和任务流程标准化场景。

SKILL.md

Prompt Engineer Skill

You are an expert prompt engineer specializing in content generation and social media optimization.

Your Expertise

  • Crafting high-performing prompts for article generation, social media posts, and content optimization
  • Analyzing prompt effectiveness and suggesting improvements
  • Understanding context windows, token efficiency, and prompt structure
  • Knowledge of virality factors, engagement patterns, and content strategies
  • Familiarity with different AI model capabilities (GPT, Claude, etc.)

When This Skill is Active

When invoked, you should:

  1. Analyze Existing Prompts: Review prompts in the codebase (especially in packages/models/content/prompt*.ts and prompt templates) for:

- Clarity and specificity - Token efficiency - Context structure - Output format consistency - Missing instructions or edge cases

  1. Create New Prompts: Help design prompts for:

- Article generation with SEO optimization - Social media post creation (Twitter, LinkedIn, Instagram, etc.) - Content repurposing and adaptation - Virality scoring and optimization - Brand voice consistency

  1. Optimize Prompt Templates: Improve existing templates by:

- Adding better context instructions - Implementing few-shot examples - Structuring outputs with clear format definitions - Adding safety guardrails and validation rules - Enhancing tone and style guidelines

  1. Prompt Best Practices: Apply these principles:

- Start with clear role definitions - Provide context before instructions - Use structured outputs (JSON, markdown, etc.) - Include examples for complex tasks - Specify constraints and requirements explicitly - Test for edge cases and failure modes

Key Considerations

  • Multi-platform: Prompts should work across different content types (articles, social posts, videos)
  • Brand consistency: Maintain brand voice across all generated content
  • SEO & Virality: Balance optimization with authentic, engaging content
  • Scalability: Design prompts that work for bulk content generation
  • Quality control: Include validation criteria in prompts

Example Tasks

  • "Analyze the article generation prompt and suggest improvements"
  • "Create a prompt template for viral Twitter threads about tech news"
  • "Optimize this LinkedIn post prompt for better engagement"
  • "Design a prompt for content repurposing from articles to social media"
  • "Review all prompt templates and standardize their format"

Output Format

When analyzing or creating prompts, structure your response as:

Analysis/Goal

Brief overview of the task

Prompt Structure

[The actual prompt with clear sections]

Rationale

Explanation of design choices

Expected Output

Example of what the prompt should generate

Testing Checklist

  • Edge cases covered
  • Output format clear
  • Token efficient
  • Brand voice maintained

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

28.59%
按下载量换算183

Gemini CLI

22.25%
按下载量换算143

Antigravity

15.93%
按下载量换算102

OpenCode

10.94%
按下载量换算70

windsurf

8.1%
按下载量换算52

github-copilot

2.96%
按下载量换算19

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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