Agent skill

Linkedin Announcement Generator

by nicepkg in nicepkg/ai-workflow

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…

MITAuto-check passedProduct & Project Management

Install Linkedin Announcement Generator

skills CLI
$ npx skills add nicepkg/ai-workflow --skill linkedin-announcement-generator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install nicepkg/ai-workflow linkedin-announcement-generator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/nicepkg/ai-workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/workflows/content-creator-workflow/.claude/skills/linkedin-announcement-generator .claude/skills/linkedin-announcement-generator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
linkedin-announcement-generator
GitHub stars
285
Token cost
~4.4k tokens
SKILL.md length
1,318 words
Files
1
Skills in repo
61
Repo updated
First seen
Licence
MIT

At a glance

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…

  • Works in 10 steps: Gather Book Metadata → Analyze Book Metrics → Determine Textbook Completeness → …
  • You need to create social media announcements about textbook completion
  • SKILL.md covers Overview, When to Use This Skill, Prerequisites and Workflow, plus 7 more sections
  • Reaches dmccreary.github.io and username.github.io

What it does

Linkedin Announcement Generator is an agent skill from nicepkg/ai-workflow. 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.

Its SKILL.md is about 4.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Product & Project Management, covering Project management and Statistics. It works with LinkedIn and GitHub. The repository describes itself as: 🚀 170+ pre-built skills for Claude Code, Cursor, Codex & 14+ AI tools. Stop re-teaching your AI the same things. One command → instant domain expertise. Marketing, SEO, Trading… The licence is MIT.

When your agent uses it

  • You need to create social media announcements about textbook completion
  • Major milestones

Example prompts

  • “/linkedin-announcement-generator”

Workflow steps

10 steps, taken from the step headings in SKILL.md.

  1. Gather Book Metadata
  2. Analyze Book Metrics
  3. Determine Textbook Completeness
  4. Craft the Announcement Structure
  5. Apply Tone and Style Guidelines
  6. Generate Multiple Variations
  7. Add Optional Enhancements
  8. Format and Present Output
  9. Validate Announcement Quality
  10. Deliver the Announcement

What it can do on your machine

Read from SKILL.md and the folder at commit d167b41. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml, markdown and python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • dmccreary.github.io
    • username.github.io

    Also links to:

    • linkedin.com
    • oercommons.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Linkedin Announcement Generator loads about 4.4k tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 1,318 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~97
When it runs · the whole SKILL.md, loaded when a task matches
~4.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from nicepkg/ai-workflow at commit d167b41, republished under its MIT licence (© nicepkg). 1,318 words, ~4,352 tokens.

Download SKILL.mdSave it as .claude/skills/linkedin-announcement-generator/SKILL.md (or your agent's skills folder).
name
linkedin-announcement-generator
description
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.
license
MIT

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

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

Example extraction:

yaml
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
Show full SKILL.md (560 more words)Show less
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:

markdown
## 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

python
#!/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

© nicepkg, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in workflows/content-creator-workflow/.claude/skills/linkedin-announcement-generator of nicepkg/ai-workflow.

Open the folder on GitHubat commit d167b41

Compare with similar skills

Linkedin Announcement Generator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Linkedin Announcement Generator compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Linkedin Announcement Generator this skillnicepkg/ai-workflow285—~4.4kAutomated safety check: PassMIT
Linkedin Announcement Generatordmccreary/ibook-skills105—~5kAutomated safety check: PassCC-BY-NC-4.0
Book Publisherdmccreary/ibook-skills105—~1.3kAutomated safety check: PassCC-BY-NC-4.0
CCPM Project Managementautomazeio/ccpm8.4k—~1.1kAutomated safety check: PassMIT
Project Managerpwrdrvr/openclaw-codex-app-server265—~1.5kAutomated safety check: PassMIT
Find Project Anomaliespenpot/penpot61k—~1.2kAutomated safety check: PassMPL-2.0

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Works with

Questions about Linkedin Announcement Generator

What does Linkedin Announcement Generator do?

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…. Linkedin Announcement Generator is an agent skill from nicepkg/ai-workflow. 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.

When should I use Linkedin Announcement Generator?

Linkedin Announcement Generator fits situations like: you need to create social media announcements about textbook completion; major milestones.

How do I install Linkedin Announcement Generator in Claude Code?

Run `npx skills add nicepkg/ai-workflow --skill linkedin-announcement-generator -a claude-code`. Or copy the skill folder (workflows/content-creator-workflow/.claude/skills/linkedin-announcement-generator in nicepkg/ai-workflow) into .claude/skills/linkedin-announcement-generator in your project. Claude Code loads it when a task matches its description.

How do I install Linkedin Announcement Generator in Codex?

Run `npx skills add nicepkg/ai-workflow --skill linkedin-announcement-generator -a codex`. Or copy the skill folder (workflows/content-creator-workflow/.claude/skills/linkedin-announcement-generator in nicepkg/ai-workflow) into .agents/skills/linkedin-announcement-generator in your project. Codex loads it when a task matches its description.

Can I use Linkedin Announcement Generator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add nicepkg/ai-workflow --skill linkedin-announcement-generator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/linkedin-announcement-generator, .gemini/skills/linkedin-announcement-generator, .github/skills/linkedin-announcement-generator and .opencode/skills/linkedin-announcement-generator in your project.

What does Linkedin Announcement Generator need to run?

SKILL.md names no scripts, command-line tools or credentials: Linkedin Announcement Generator is instructions for the agent only.

Does Linkedin Announcement Generator access the network?

SKILL.md names 4 domains. In commands or code: dmccreary.github.io and username.github.io; the agent is likely to contact these when it follows the instructions. As links in the text: linkedin.com and oercommons.org. This is read from the text; nothing was executed.

Is Linkedin Announcement Generator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Linkedin Announcement Generator use?

Linkedin Announcement Generator is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Linkedin Announcement Generator use?

About 4.4k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Linkedin Announcement Generator?

Skills that share tags, products or a category with Linkedin Announcement Generator: Linkedin Announcement Generator (dmccreary/ibook-skills, 105 stars), Book Publisher (dmccreary/ibook-skills, 105 stars), CCPM Project Management (automazeio/ccpm, 8.4k stars) and Project Manager (pwrdrvr/openclaw-codex-app-server, 265 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Linkedin Announcement Generator?

nicepkg (a GitHub organization) maintains it in nicepkg/ai-workflow, which has 285 GitHub stars. The repository holds 61 skills in this directory. The repository was last updated on January 20, 2026.

Source: nicepkg/ai-workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.