Linkedin Post

Organization

langchain-ai

linkedin-post

Write a LinkedIn post based on research findings or a given topic. Use this skill when asked to create LinkedIn content, professional posts, or thought leadership pieces.

Overview

Publisher	langchain-ai
Repository	`langgraph-101`
Skill name	`linkedin-post`
Stars	682
Forks	160
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by langchain-ai on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/langchain-ai/langgraph-101/tree/main/agents/deep_agent/skills/linkedin-post
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/langchain-ai/langgraph-101/tree/main/agents/deep_agent/skills/linkedin-post

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/langchain-ai/langgraph-101.git /tmp/langgraph-101
mkdir -p .claude/skills
cp -r /tmp/langgraph-101/agents/deep_agent/skills/linkedin-post .claude/skills/linkedin-post

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Linkedin Post 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 Post 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 Post 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 Post Skill

Format

Hook: Start with a bold opening line that grabs attention (this appears before the "see more" cut)
Body: 3-5 short paragraphs, each 1-2 sentences
Use line breaks between paragraphs for readability
Include 1-2 relevant emojis per paragraph (don't overdo it)
End with a call-to-action or question to drive engagement
Add 3-5 relevant hashtags at the bottom

Tone

Professional but conversational
Share insights, not just information
Use "I" statements and personal perspective where appropriate
Avoid jargon unless the audience expects it

Length

Ideal: 150-300 words
LinkedIn truncates after ~210 characters, so the first line must hook the reader

Template


[Bold hook / surprising stat / question]

[Context -- why this matters]

[Key insight 1]

[Key insight 2]

[Key insight 3 or personal takeaway]

[Call to action / question for engagement]

#hashtag1 #hashtag2 #hashtag3

Example


Most AI agents fail not because of the model -- but because of context management.

After researching the latest agent frameworks, one pattern keeps emerging:
the best agents treat their context window like a scarce resource.

Here's what separates good agents from great ones:

1. They offload intermediate results to a filesystem instead of keeping everything in context
2. They delegate to subagents for isolation -- the main agent only sees summaries
3. They use progressive disclosure -- loading instructions only when relevant

The shift from "bigger context window" to "smarter context management" is where
the real breakthroughs are happening.

What patterns have you seen work best in your agent architectures?

#AIAgents #LangChain #LangGraph #ContextEngineering

Frequently asked questions

What does the Linkedin Post AI skill do?

Write a LinkedIn post based on research findings or a given topic. Use this skill when asked to create LinkedIn content, professional posts, or thought leadership pieces.

Why use Linkedin Post on TypingMind?

Because you install it once and use it with any model. Linkedin Post 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 Post in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/langchain-ai/langgraph-101/tree/main/agents/deep_agent/skills/linkedin-post. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Linkedin Post?

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 Post?

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

Is the Linkedin Post AI skill free?

Yes. It is published on GitHub by langchain-ai 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

LinkedIn Post Skill

Format

Tone

Length

Template

Example

Frequently asked questions

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