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Agent Skill · 研究检索

linkedin-announcement-generator(linkedin 公告生成器)

linkedin-announcement-generator 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

linkedin-announcement-generator 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 42,153。

总安装 1,102周安装 45GitHub Stars 175下载 356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:linkedin-announcement-generator(linkedin 公告生成器)
来源仓库:https://github.com/nicepkg/ai-workflow
仓库路径:skills/linkedin-announcement-generator
安装命令:
npx skills add https://github.com/nicepkg/ai-workflow --skill linkedin-announcement-generator
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/nicepkg/ai-workflow --skill linkedin-announcement-generator

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

linkedin-announcement-generator 用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限和维护状态。

使用前建议核实是否会触发联网、命令执行或文件读写操作。可结合来源仓库和原始 README 进一步核验具体用法和功能边界。

来源仓库内路径:skills/linkedin-announcement-generator

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/nicepkg/ai-workflow --skill linkedin-announcem…;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

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

linkedin-announcement-generator 怎么安装?

在终端执行 npx skills add https://github.com/nicepkg/ai-workflow --skill linkedin-announcement-genera…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

linkedin-announcement-generator 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。

linkedin-announcement-generator 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

linkedin-announcement-generator 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。

linkedin-announcement-generator 用的人多吗?

公开数据是累计安装 1,102 次,近一周安装 45 次,下载 356 次,GitHub 175 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。

linkedin-announcement-generator 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。
  • 需要处理研究检索类任务、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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
linkedin-announcement-generator

linkedin 公告生成器 · 本页

1,102175需要联网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

LinkedIn Announcement Generator

Overview

This skill automates the creation of professional LinkedIn announcements for intelligent textbooks. It analyzes book metrics from the docs/learning-graph/ directory, gathers statistics about chapters, concepts, and educational resources, and generates engaging announcement text with relevant hashtags and links to the published site.

The announcements are designed to highlight the scope and completeness of the textbook, showcase its educational features, and attract educators, students, and learning professionals to the content.

When to Use This Skill

Use this skill when:

  • Publishing a completed intelligent textbook to GitHub Pages
  • Announcing major milestones (e.g., "First 10 chapters complete!")
  • Promoting updated or newly added content
  • Sharing the textbook with the educational technology community
  • Preparing social media posts for course launches
  • Creating announcements for conference presentations or workshops
  • Building awareness for open educational resources

Prerequisites

The intelligent textbook project should have:

  • A docs/learning-graph/book-metrics.md file containing textbook statistics
  • A mkdocs.yml file with site_name, site_url, and site_description
  • Deployed site on GitHub Pages (or another hosting platform)
  • Optional: docs/learning-graph/chapter-metrics.md for chapter-level details
  • Optional: docs/course-description.md for audience and topic information

Workflow

Step 1: Gather Book Metadata

Extract key information from the project configuration:

  1. Read mkdocs.yml to get:

- site_name - Title of the textbook - site_url - Live site URL (typically GitHub Pages) - site_description - Brief description of the textbook - repo_url - GitHub repository URL

  1. Read docs/course-description.md (if it exists) to get:

- Target audience (grade level, prerequisites) - Subject matter/topic - Learning objectives - Course context

Example extraction:

site_name: 'Geometry for High School Students'
site_url: 'https://username.github.io/geometry-course/'
site_description: 'An interactive geometry textbook with MicroSims and quizzes'

Step 2: Analyze Book Metrics

Read and parse docs/learning-graph/book-metrics.md to extract:

Core Metrics:

  • Number of chapters
  • Number of concepts in learning graph
  • Number of glossary terms
  • Number of FAQ questions
  • Number of quiz questions
  • Number of diagrams
  • Number of equations
  • Number of MicroSims (interactive simulations)
  • Total word count
  • Number of hyperlinks
  • Equivalent printed pages

Parse the metrics table:

Look for the table starting with | Metric Name | Value | Link | Notes | and extract values from the second column.

Handle missing metrics gracefully:

  • If diagrams = 0, mention "includes equations and visual elements" instead
  • If quiz questions = 0, omit quiz mention
  • If MicroSims = 0, mention "comprehensive content" instead

Step 3: Determine Textbook Completeness

Calculate the completion status based on metrics:

Indicators of completeness:

  • Chapters ≥ 8: Substantial textbook
  • Total words > 30,000: Comprehensive content
  • Quiz questions ≥ 50: Well-assessed
  • MicroSims ≥ 5: Interactive elements present
  • Equivalent pages > 100: Book-length work

Status categories:

  • Complete (100%): All major components present, ready for use
  • Nearly Complete (90-99%): Most content done, minor additions pending
  • In Progress (70-89%): Substantial content, ongoing development
  • Early Release (< 70%): Initial chapters available, more coming

Choose appropriate language for the announcement based on status.

Step 4: Craft the Announcement Structure

Create a LinkedIn post with the following components:

1. Opening Hook (1-2 sentences)

Start with an attention-grabbing statement that:

  • Announces the textbook completion/release
  • Mentions the topic and audience
  • Highlights what makes it special

Examples:

  • "Excited to share a new open educational resource for [AUDIENCE]!"
  • "Just published: An AI-generated interactive textbook on [TOPIC]!"
  • "Thrilled to announce the completion of [TEXTBOOK NAME]!"

2. Content Description (2-3 sentences)

Explain what the textbook covers and its unique features:

  • Educational framework (Bloom's Taxonomy, concept dependencies)
  • Interactive elements (MicroSims, quizzes)
  • Technology stack (MkDocs, p5.js, AI-generated)
  • Target audience and prerequisites

Example:

This intelligent textbook on [TOPIC] is designed for [AUDIENCE]. Built using MkDocs Material and AI-assisted content generation, it incorporates learning graphs, concept dependencies, and interactive MicroSims to make [TOPIC] accessible and engaging.

3. Key Metrics (bulleted list)

Present impressive statistics to demonstrate scope:

📊 By the numbers:
• [X] chapters covering [TOPIC AREAS]
• [Y] concepts in the learning graph
• [Z] interactive MicroSims (p5.js simulations)
• [Q] quiz questions for self-assessment
• [G] glossary terms with ISO 11179-compliant definitions
• [W] total words (~[P] equivalent printed pages)

Formatting tips:

  • Use emoji bullets (📊, 📚, 🎓, ⚡, 🔬) for visual appeal
  • Round large numbers (225,182 → 225,000)
  • Group related metrics together
  • Highlight the most impressive numbers

4. Technology and AI Disclosure (1-2 sentences)

Be transparent about AI involvement and technology:

Generated using Claude AI skills and the intelligent textbook framework, this open-source project demonstrates how AI can augment educational content creation while maintaining quality and pedagogical rigor.

5. Call to Action (1 sentence)

Direct readers to the site:

Explore the full textbook here: [SITE_URL]

6. Hashtags (8-15 tags)

Include relevant hashtags for discoverability:

Standard hashtags:

  • #AI / #ArtificialIntelligence
  • #GenAI / #GenerativeAI
  • #Education / #EdTech / #EducationalTechnology
  • #OpenEducation / #OER (Open Educational Resources)
  • #ELearning / #OnlineLearning

Content-specific hashtags:

  • #Textbook / #InteractiveTextbook
  • #MicroSims / #Simulations
  • #Visualizations / #DataViz
  • #Diagrams / #Infographics
  • #Quizzes / #Assessment

Technology-specific hashtags:

  • #MkDocs / #MaterialDesign
  • #p5js / #JavaScript
  • #Python
  • #ClaudeAI / #AnthropicClaude

Domain-specific hashtags:

Add 2-4 hashtags specific to the subject matter:

  • Math: #Mathematics, #Geometry, #Calculus, #Algebra
  • Science: #Physics, #Chemistry, #Biology
  • CS: #Programming, #ComputerScience, #DataScience
  • History: #History, #WorldHistory, #AmericanHistory

Professional/Academic hashtags:

  • #LMS / #LearningManagementSystem
  • #CurriculumDesign
  • #InstructionalDesign
  • #STEM / #STEMeducation
  • #HigherEd / #K12Education

Total hashtag count: Aim for 10-15 hashtags for optimal reach.

Step 5: Apply Tone and Style Guidelines

LinkedIn voice characteristics:

  • Professional but approachable
  • Enthusiastic without being overly promotional
  • Educational and informative
  • Data-driven (cite specific metrics)
  • Transparent about AI involvement
  • Community-focused (sharing resources)

Writing best practices:

  • Use first person ("I'm excited to share...")
  • Keep paragraphs short (2-3 lines each)
  • Use emoji sparingly (1-3 per post)
  • Include line breaks for readability
  • Front-load important information
  • End with a clear call to action

Avoid:

  • Overly academic language
  • Excessive jargon
  • Claims without evidence
  • Overly promotional tone
  • Clickbait-style hooks
  • Too many emojis

Step 6: Generate Multiple Variations

Create three variations of the announcement:

Variation 1: Detailed (Full Length)

  • Complete description with all metrics
  • 1500-2000 characters
  • All hashtags included
  • Best for: Initial launch announcement

Variation 2: Medium (Standard Length)

  • Key metrics only (top 5-6)
  • 800-1200 characters
  • 10-12 hashtags
  • Best for: Progress updates, milestone posts

Variation 3: Concise (Short Form)

  • Essential info only
  • 400-600 characters
  • 6-8 hashtags
  • Best for: Quick updates, cross-posting to other platforms

Provide all three variations so the user can choose based on their preference.

Step 7: Add Optional Enhancements

If available, include:

Screenshot or cover image suggestion:

📸 Suggested visual: Screenshot of the learning graph visualization or the textbook home page

Notable features callout:

If the textbook has unique elements, highlight them:

  • "Features interactive p5.js simulations you can run in your browser"
  • "Includes concept dependency graphs showing learning pathways"
  • "Contains ISO 11179-compliant glossary for precise terminology"

Collaboration invitation:

If seeking contributors:

  • "Open for contributions! Check out the GitHub repo: [REPO_URL]"
  • "Looking for educators to provide feedback. DM me if interested!"

Related links:

If applicable:

  • Link to GitHub repository (for developers)
  • Link to related blog post or article
  • Link to presentation slides

Step 8: Format and Present Output

Present the LinkedIn announcement(s) in a clear, copy-paste ready format:

## LinkedIn Announcement - Full Version

[Paste-ready text here]

---

## LinkedIn Announcement - Medium Version

[Paste-ready text here]

---

## LinkedIn Announcement - Concise Version

[Paste-ready text here]

---

## Suggested Enhancements

**Visual:** [Description of recommended image/screenshot]

**Timing:** Best posted [weekday, time recommendation]

**Engagement Tips:**
- Tag relevant individuals or organizations if appropriate
- Respond to comments within first 2 hours for algorithm boost
- Consider posting during peak LinkedIn hours (Tuesday-Thursday, 8-10am or 12-2pm)

Step 9: Validate Announcement Quality

Before finalizing, check that the announcement:

  • Includes the live site URL (working link)
  • Contains accurate metrics from book-metrics.md
  • Has 10-15 relevant hashtags
  • Mentions AI transparency
  • Includes a clear call to action
  • Is between 400-2000 characters (LinkedIn optimal range)
  • Uses professional, enthusiastic tone
  • Highlights unique or impressive features
  • Is free of typos and grammatical errors
  • Provides value to the educational community

Step 10: Deliver the Announcement

Output the finalized announcement text(s) ready for the user to:

  1. Copy and paste directly into LinkedIn
  2. Customize with personal touches if desired
  3. Add optional media (screenshots, videos)
  4. Schedule or post immediately

Inform the user:

✅ LinkedIn announcement generated successfully!

Three variations provided (full, medium, concise) - choose the one that fits your style.

**Next steps:**
1. Copy your preferred version
2. Paste into LinkedIn post composer
3. Add a screenshot of your textbook (optional but recommended)
4. Review and post!

Pro tip: LinkedIn posts with images get 2x more engagement. Consider adding a screenshot of your learning graph or textbook homepage.

Example Output

Full-Length Announcement Example

🎓 Excited to share a new open educational resource: an interactive textbook on Geometry designed for high school students!

This intelligent textbook combines AI-assisted content generation with proven educational frameworks. Built using MkDocs Material, it incorporates learning graphs showing concept dependencies, interactive MicroSims using p5.js, and comprehensive assessment tools to make geometry accessible and engaging.

📊 By the numbers:
• 13 chapters covering points, lines, angles, triangles, polygons, circles, and 3D geometry
• 200 concepts organized in a dependency graph
• 5 interactive MicroSims (p5.js simulations)
• 10 quiz questions for self-assessment
• 22 glossary terms with precise definitions
• 225,000+ words (~900 equivalent printed pages)

Generated using Claude AI skills and the intelligent textbook framework, this open-source project demonstrates how AI can augment educational content creation while maintaining pedagogical quality and rigor.

All content follows Bloom's Taxonomy (2001) for learning outcomes and includes detailed explanations, worked examples, and practice exercises.

🌐 Explore the full textbook: https://dmccreary.github.io/claude-skills/

#AI #GenAI #GenerativeAI #Education #EdTech #OpenEducation #OER #ELearning #Textbook #InteractiveTextbook #MicroSims #Visualizations #Quizzes #Geometry #Mathematics #MkDocs #ClaudeAI #LMS #CurriculumDesign #STEMeducation

Medium-Length Announcement Example

📚 Just published: An AI-generated interactive textbook on Geometry for high school students!

This intelligent textbook uses MkDocs Material, learning graphs, and interactive p5.js MicroSims to make geometry engaging and accessible.

Key features:
• 13 comprehensive chapters
• 200 concepts with dependency mapping
• 5 interactive simulations
• 225,000+ words of content
• Open source and freely available

Built using Claude AI and the intelligent textbook framework - demonstrating how AI can enhance educational content while maintaining quality.

Explore it here: https://dmccreary.github.io/claude-skills/

#AI #GenAI #Education #EdTech #OpenEducation #Textbook #MicroSims #Geometry #Mathematics #ClaudeAI #STEMeducation

Concise Announcement Example

🎓 New open educational resource: Interactive Geometry textbook for high school!

✨ 13 chapters | 200 concepts | 5 MicroSims | 225K words

AI-generated using Claude and MkDocs Material. Free and open source.

📖 https://dmccreary.github.io/claude-skills/

#Education #EdTech #Geometry #AI #OpenEducation #Textbook

Customization Options

The skill can be customized to:

1. Adjust tone:

  • Academic (formal, research-focused)
  • Casual (friendly, conversational)
  • Promotional (marketing-focused)
  • Technical (developer-focused)

2. Target different audiences:

  • Educators and teachers
  • Students and learners
  • Instructional designers
  • Software developers
  • Educational technology leaders

3. Emphasize different aspects:

  • AI/technology innovation
  • Open source/open education
  • Interactive elements
  • Comprehensive coverage
  • Pedagogical approach

4. Include additional context:

  • Author background
  • Development timeline
  • Use cases and testimonials
  • Research backing
  • Awards or recognition

Supporting Scripts

The skill can optionally include a Python script to automate metric extraction:

scripts/linkedin-metrics-extractor.py

#!/usr/bin/env python3
"""Extract metrics from book-metrics.md for LinkedIn announcements."""

import re
import yaml

def extract_book_metrics(metrics_file):
    """Parse book-metrics.md and return dictionary of metrics."""
    # Implementation: Parse markdown table
    pass

def extract_site_config(mkdocs_file):
    """Parse mkdocs.yml and return site metadata."""
    # Implementation: Load YAML and extract site_name, site_url, etc.
    pass

def format_number(n):
    """Format numbers for readability (e.g., 225182 -> 225,000)."""
    # Implementation: Round and format large numbers
    pass

# Usage:
# python linkedin-metrics-extractor.py docs/learning-graph/book-metrics.md mkdocs.yml

Quality Standards

A high-quality LinkedIn announcement should:

  • Be accurate (all metrics verified)
  • Be engaging (compelling hook and narrative)
  • Be transparent (acknowledge AI involvement)
  • Be professional (appropriate tone for LinkedIn)
  • Be actionable (clear call to action)
  • Be discoverable (relevant hashtags)
  • Be concise (under 2000 characters)
  • Be valuable (provides useful information to community)

Troubleshooting

Issue: Metrics not found in book-metrics.md

Solution: Run the book-metrics-generator skill first to create the metrics file

Issue: Site URL not available

Solution: Ask user for the deployed site URL or GitHub Pages link

Issue: Announcement too long (> 3000 characters)

Solution: Use the medium or concise variation instead

Issue: Not sure which hashtags to use

Solution: Focus on the subject domain (e.g., #Mathematics for math textbooks) and general education tags

Related Skills

  • book-metrics-generator - Generates the metrics file used by this skill
  • readme-generator - Creates GitHub README with similar content
  • intelligent-textbook - The workflow that creates the textbook itself

Resources

平台分布

Claude Code

28.9%
按下载量换算103

OpenCode

24.54%
按下载量换算87

Cursor

17.84%
按下载量换算64

trae

14.36%
按下载量换算51

Gemini CLI

8.72%
按下载量换算31

Codex

3.8%
按下载量换算14

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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