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Crosspost

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YuxiaoWang-520
crosspost

Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

Overview

PublisherYuxiaoWang-520
Repositoryharness-craft
Skill namecrosspost
Stars
73
Forks
5
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

    Published by YuxiaoWang-520 on GitHub. Read the source before you install it.

Installation

Install the Crosspost 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/YuxiaoWang-520/harness-craft/tree/main/skills/crosspost
  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/YuxiaoWang-520/harness-craft.git /tmp/harness-craft
mkdir -p .claude/skills
cp -r /tmp/harness-craft/skills/crosspost .claude/skills/crosspost
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Crosspost 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 Crosspost 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 Crosspost 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.

Crosspost

Distribute content across multiple social platforms with platform-native adaptation.

When to Use

  • User wants to post content to multiple platforms
  • Publishing announcements, launches, or updates across social media
  • Repurposing a post from one platform to others
  • User says "crosspost", "post everywhere", "share on all platforms", or "distribute this"

How It Works

Core Rules

  1. Never post identical content cross-platform. Each platform gets a native adaptation.
  2. Primary platform first. Post to the main platform, then adapt for others.
  3. Respect platform conventions. Length limits, formatting, link handling all differ.
  4. One idea per post. If the source content has multiple ideas, split across posts.
  5. Attribution matters. If crossposting someone else's content, credit the source.

Platform Specifications

PlatformMax LengthLink HandlingHashtagsMedia
X280 chars (4000 for Premium)Counted in lengthMinimal (1-2 max)Images, video, GIFs
LinkedIn3000 charsNot counted in length3-5 relevantImages, video, docs, carousels
Threads500 charsSeparate link attachmentNone typicalImages, video
Bluesky300 charsVia facets (rich text)None (use feeds)Images

Workflow

Step 1: Create Source Content

Start with the core idea. Use content-engine skill for high-quality drafts:

  • Identify the single core message
  • Determine the primary platform (where the audience is biggest)
  • Draft the primary platform version first

Step 2: Identify Target Platforms

Ask the user or determine from context:

  • Which platforms to target
  • Priority order (primary gets the best version)
  • Any platform-specific requirements (e.g., LinkedIn needs professional tone)

Step 3: Adapt Per Platform

For each target platform, transform the content:

X adaptation:

  • Open with a hook, not a summary
  • Cut to the core insight fast
  • Keep links out of main body when possible
  • Use thread format for longer content

LinkedIn adaptation:

  • Strong first line (visible before "see more")
  • Short paragraphs with line breaks
  • Frame around lessons, results, or professional takeaways
  • More explicit context than X (LinkedIn audience needs framing)

Threads adaptation:

  • Conversational, casual tone
  • Shorter than LinkedIn, less compressed than X
  • Visual-first if possible

Bluesky adaptation:

  • Direct and concise (300 char limit)
  • Community-oriented tone
  • Use feeds/lists for topic targeting instead of hashtags

Step 4: Post Primary Platform

Post to the primary platform first:

  • Use x-api skill for X
  • Use platform-specific APIs or tools for others
  • Capture the post URL for cross-referencing

Step 5: Post to Secondary Platforms

Post adapted versions to remaining platforms:

  • Stagger timing (not all at once — 30-60 min gaps)
  • Include cross-platform references where appropriate ("longer thread on X" etc.)

Examples

Source: Product Launch

X version:

We just shipped [feature].

[One specific thing it does that's impressive]

[Link]

LinkedIn version:

Excited to share: we just launched [feature] at [Company].

Here's why it matters:

[2-3 short paragraphs with context]

[Takeaway for the audience]

[Link]

Threads version:

just shipped something cool — [feature]

[casual explanation of what it does]

link in bio

Source: Technical Insight

X version:

TIL: [specific technical insight]

[Why it matters in one sentence]

LinkedIn version:

A pattern I've been using that's made a real difference:

[Technical insight with professional framing]

[How it applies to teams/orgs]

#relevantHashtag

API Integration

Batch Crossposting Service (Example Pattern)

If using a crossposting service (e.g., Postbridge, Buffer, or a custom API), the pattern looks like:

python
import os
import requests

resp = requests.post(
    "https://api.postbridge.io/v1/posts",
    headers={"Authorization": f"Bearer {os.environ['POSTBRIDGE_API_KEY']}"},
    json={
        "platforms": ["twitter", "linkedin", "threads"],
        "content": {
            "twitter": {"text": x_version},
            "linkedin": {"text": linkedin_version},
            "threads": {"text": threads_version}
        }
    },
    timeout=30
)
resp.raise_for_status()

Manual Posting

Without Postbridge, post to each platform using its native API:

  • X: Use x-api skill patterns
  • LinkedIn: LinkedIn API v2 with OAuth 2.0
  • Threads: Threads API (Meta)
  • Bluesky: AT Protocol API

Quality Gate

Before posting:

  • Each platform version reads naturally for that platform
  • No identical content across platforms
  • Length limits respected
  • Links work and are placed appropriately
  • Tone matches platform conventions
  • Media is sized correctly for each platform

Related Skills

  • content-engine — Generate platform-native content
  • x-api — X/Twitter API integration

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 Crosspost AI skill do?

Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

Why use Crosspost on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/YuxiaoWang-520/harness-craft/tree/main/skills/crosspost. 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 Crosspost?

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 Crosspost?

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

Is the Crosspost AI skill free?

It is published on GitHub by YuxiaoWang-520. Check the repository for licensing terms. 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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