mcpbeat Sign in

Linkedin Announcement Generator Skill for Claude

This skill generates professional LinkedIn announcement text for intelligent textbooks by analyzing book metrics, chapter content, and learning resources to create engaging posts with key statistics, hashtags, and links to the published site. Use this skill when you need to create social media announcements about textbook completion or major milestones.

4k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
275
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/nicepkg/ai-workflow --skill linkedin-announcement-generator

The instruction itself

25 sections, as written by the author

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:

  • 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
  • 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:

  • Copy and paste directly into LinkedIn
  • Customize with personal touches if desired
  • Add optional media (screenshots, videos)
  • 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

  • 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

Other skills for the same job

different authors, same section of the catalogue
XLSX
by anthropics
vendor ×15

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

5k tokens scripts
XLSX
by w95
×7

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

3k tokens
Raffle Winner Picker
by frostant
×5

Picks random winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests. Ensures fair, unbiased selection with transparency.

949 tokens
Fda Database
by christophacham
×4

Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.

32k tokens scripts
Matlab
by christophacham
×4

MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.

25k tokens
Umap Learn
by ComeOnOliver
×4

UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.

14k tokens
D3 Viz
by chrisvoncsefalvay
×3

Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.

20k tokens
Alphafold Database
by christophacham
×3

Access AlphaFold 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.

7k tokens

How to use it

Copy the folder

Take nicepkg/linkedin-announcement-generator from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.