chatgpt-linkedin-skill

Generate LinkedIn-style engineering articles from notable technical work and save them as markdown files.

1|Updated Jun 1, 2026
One-click install
npx skills add https://github.com/D1ssolve/craft-agents --skill chatgpt-linkedin-skill-d1ssolve
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: chatgpt-linkedin-skill
Source: https://github.com/D1ssolve/craft-agents/tree/main/skills/chatgpt-linkedin-skill
Command: npx skills add https://github.com/D1ssolve/craft-agents --skill chatgpt-linkedin-skill-d1ssolve

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Turning meaningful engineering work into shareable LinkedIn articles is time-consuming, and most engineers skip documenting lessons learned from debugging, migrations, or architecture decisions. ## Core Features & Use Cases - Trigger-Based Article Generation: Activates when work involves non-default implementations, workarounds, technical insights, architecture decisions, or reusable debugging lessons. - Quality Gate Enforcement: Refuses to generate content unless a real insight, concrete change, and transferable lesson all exist. - Structured Writing Templates: Provides reference patterns for founder stories, engineering case studies, framework articles, and myth-busting posts. - Use Case: After refactoring a slow database query and discovering a non-obvious indexing fix, use this Skill to produce a first-person LinkedIn article saved to .ai/linkedin/<date>-<slug>.md. ## Quick Start Write a LinkedIn article about the caching workaround we just implemented and save it as a markdown file.

Frequently Asked Questions about chatgpt-linkedin-skill

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I write a LinkedIn article about my engineering work?

Describe the technical work you completed, such as a bug fix, migration, or architecture decision, and the Skill generates a first-person article following a hook-problem-solution-lessons structure. The result is saved as a markdown file in the .ai/linkedin directory.

What makes a good engineering LinkedIn post?

Effective posts use a strong hook, first-person narrative, concrete technical details, and a transferable lesson. The Skill enforces this through a quality gate requiring real insight, actual change, and reusable learning before generating content.

When should I not generate a LinkedIn article from my work?

Skip article generation when the work was routine or default, when no concrete change happened, or when there is no transferable lesson for readers. The Skill's quality gate blocks output in these cases to avoid generic content.

Where are the generated LinkedIn articles saved?

Articles are saved as standalone markdown files in the .ai/linkedin directory, named with the date and a slug derived from the topic. Each article is a self-contained file ready for review and publishing.

Can the Skill generate images for LinkedIn posts?

No, the Skill does not generate images. It can embed an image prompt placeholder in the article using [IMAGE_PROMPT] tags, which you can use separately with an image generation tool.