Linkedin Content System logo

Linkedin Content System

Organization
microsoft
linkedin-content-system

Use this skill when the user asks to create LinkedIn posts, promotional posts, thought-leadership posts, newsletter introductions, article intros, or long-form LinkedIn content from source notes, facts, or drafts.

Overview

Publishermicrosoft
Repositorycat-agent-skills
Skill namelinkedin-content-system
Stars
95
Forks
115
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by microsoft on GitHub. Read the source before you install it.

Installation

Install the Linkedin Content System AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/microsoft/cat-agent-skills/tree/main/submissions/linkedin-content-system
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/microsoft/cat-agent-skills.git /tmp/cat-agent-skills
mkdir -p .claude/skills
cp -r /tmp/cat-agent-skills/submissions/linkedin-content-system .claude/skills/linkedin-content-system
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Linkedin Content System in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Linkedin Content System on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Linkedin Content System is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

LinkedIn Content System

Use this skill to create credible LinkedIn content from supplied facts, notes, drafts, articles, or source material.

Core rules

  1. No invented evidence. Do not invent metrics, client names, event details, quotes, claims, or results.
  2. No fake authority. Do not imply the author has done, seen, led, or researched something unless supplied evidence supports it.
  3. Keep the voice human. Avoid generic inspirational language, over-polished corporate phrasing, and forced hooks.
  4. Fit the format. Match the output to the requested LinkedIn surface: short post, promotional post, event post, newsletter intro, article intro, carousel copy, or long-form article.
  5. Avoid unnecessary links or citations in the post body unless the user asks for them. Keep LinkedIn copy clean and paste-ready.

Inputs to look for

  • Source article, draft, notes, or bullet points.
  • Audience and desired action.
  • Author voice guidance.
  • Desired length.
  • Specific announcement, event, launch, model, or point of view.
  • Whether links, hashtags, mentions, or calls to action should be included.

Workflow

  1. Read the supplied source material.
  2. Extract the central point, proof points, and intended reader response.
  3. Choose the appropriate LinkedIn format.
  4. Draft in a natural style with clear paragraphs.
  5. Keep the post grounded in supplied content.
  6. Provide variants if requested.

Output formats

Short post

markdown
[Post copy]

Promo post

markdown
[Post copy]

[Optional CTA]

Newsletter or article intro

markdown
# [Title]

[Intro copy]

Multi-variant output

markdown
## Recommended version

[Post]

## Alternative angle

[Post]

## Shorter version

[Post]

Style guidance

  • Prefer concrete observations over broad claims.
  • Use short paragraphs but avoid a stack of one-line fragments unless the user requests that style.
  • Avoid manipulative hooks such as "Stop doing X" unless it genuinely fits the user's tone.
  • Make the first line specific enough to be worth reading.
  • End with a useful reflection, question, or action rather than a generic CTA.

References

This skill includes supporting reference material. Read the relevant reference file when the task needs additional structure, rubric detail, examples, or checklist support.

  • references/linkedin-format-guide.md - use this when additional structure, examples, or checks are useful for the task.

Quality checklist

Before responding, check:

  • The content is grounded in supplied facts.
  • It reads like a credible human post.
  • It fits the requested LinkedIn surface.
  • It avoids unnecessary links, references, and invented proof.
  • The user can paste it directly into LinkedIn.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Linkedin Content System AI skill do?

Use this skill when the user asks to create LinkedIn posts, promotional posts, thought-leadership posts, newsletter introductions, article intros, or long-form LinkedIn content from source notes, facts, or drafts.

Why use Linkedin Content System on TypingMind?

Because you install it once and use it with any model. Linkedin Content System is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Linkedin Content System in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/cat-agent-skills/tree/main/submissions/linkedin-content-system. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Linkedin Content System?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Linkedin Content System?

As many as you like. As long as a model supports skills, you can use Linkedin Content System with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Linkedin Content System AI skill free?

Yes. It is published on GitHub by microsoft under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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