Twitter Post logo

Twitter Post

Organization
langchain-ai
twitter-post

Write a Twitter/X post or thread based on research findings or a given topic. Use this skill when asked to create tweets, X posts, or social media threads.

Overview

Publisherlangchain-ai
Repositorylanggraph-101
Skill nametwitter-post
Stars
682
Forks
160
Bundled files
Instructions only
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.

  • 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 Twitter Post 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/langchain-ai/langgraph-101/tree/main/agents/deep_agent/skills/twitter-post
  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/langchain-ai/langgraph-101.git /tmp/langgraph-101
mkdir -p .claude/skills
cp -r /tmp/langgraph-101/agents/deep_agent/skills/twitter-post .claude/skills/twitter-post
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Twitter 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 Twitter 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 Twitter 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.

Twitter/X Post Skill

Single Tweet Format

  • Maximum 280 characters
  • Lead with the most compelling point
  • Use numbers or data when possible
  • End with a link placeholder or call-to-action
  • 1-2 hashtags max (optional)

Thread Format (for longer content)

  • Tweet 1: Hook + preview of what's coming (e.g., "A thread on X:" or "Here's what I found:")
  • Tweets 2-N: One idea per tweet, numbered (1/, 2/, 3/)
  • Final tweet: Summary + call-to-action + link
  • Keep each tweet self-contained (people share individual tweets)
  • 4-8 tweets is the sweet spot for engagement

Tone

  • Concise and punchy
  • Opinionated takes perform better than neutral summaries
  • Use plain language -- no corporate speak
  • Contrarian or surprising angles get more engagement

Tips

  • Front-load the value (no throat-clearing or preambles)
  • Use line breaks within tweets for readability
  • Avoid hashtags in threads (they look spammy) -- save them for single tweets
  • Numbers and lists catch the eye in a feed

Example Single Tweet

AI agents that manage their context window well outperform those with 10x more tools.

The secret isn't more capabilities -- it's smarter context engineering.

Example Thread

Thread: What makes AI agents actually work in production? 🧵

1/ It's not the model size. It's context management.

The best agents treat their context window like RAM -- offloading to filesystem, summarizing aggressively, loading info on demand.

2/ Subagents are the key to scaling.

Instead of one agent doing everything, delegate to specialists. The main agent only sees the summary, not 50 intermediate tool calls.

3/ Skills > giant system prompts.

Progressive disclosure: load detailed instructions only when the task needs them. Your agent's prompt stays clean until it matters.

4/ Memory needs structure.

Semantic (facts), episodic (experiences), procedural (rules) -- route them to different backends so they persist appropriately.

5/ The takeaway: the best agent architectures are about information flow, not raw capability.

What patterns are you using? Reply with your favorite agent architecture trick.

Frequently asked questions

What does the Twitter Post AI skill do?

Write a Twitter/X post or thread based on research findings or a given topic. Use this skill when asked to create tweets, X posts, or social media threads.

Why use Twitter Post on TypingMind?

Because you install it once and use it with any model. Twitter 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 Twitter 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/twitter-post. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Twitter 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 Twitter Post?

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

Is the Twitter 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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