crosspost
Distribute content across multiple social platforms, automatically adapting to each platform's native format and content guidelines. AI Agent Skill to boost efficiency and automation.
npx skills add affaan-m/everything-claude-code --skill crosspostBefore / After Comparison
1 组Manually adjusting the format, character limits, and media specifications for the same content on each social platform, logging in and publishing platform by platform, is time-consuming and often leads to inconsistencies across platform versions.
Create content once, and it automatically adapts to the native format requirements of multiple platforms. Character counts, tags, and media specifications are intelligently adjusted according to platform guidelines, completing full-platform distribution in a single operation.
crosspost
Crosspost
Distribute content across multiple social platforms with platform-native adaptation.
When to Activate
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User wants to post content to multiple platforms
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Publishing announcements, launches, or updates across social media
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Repurposing a post from one platform to others
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User says "crosspost", "post everywhere", "share on all platforms", or "distribute this"
Core Rules
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Never post identical content cross-platform. Each platform gets a native adaptation.
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Primary platform first. Post to the main platform, then adapt for others.
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Respect platform conventions. Length limits, formatting, link handling all differ.
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One idea per post. If the source content has multiple ideas, split across posts.
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Attribution matters. If crossposting someone else's content, credit the source.
Platform Specifications
Platform Max Length Link Handling Hashtags Media
X 280 chars (4000 for Premium) Counted in length Minimal (1-2 max) Images, video, GIFs
LinkedIn 3000 chars Not counted in length 3-5 relevant Images, video, docs, carousels
Threads 500 chars Separate link attachment None typical Images, video
Bluesky 300 chars Via 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
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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:
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Which platforms to target
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Priority order (primary gets the best version)
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Any platform-specific requirements (e.g., LinkedIn needs professional tone)
Step 3: Adapt Per Platform
For each target platform, transform the content:
X adaptation:
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Open with a hook, not a summary
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Cut to the core insight fast
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Keep links out of main body when possible
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Use thread format for longer content
LinkedIn adaptation:
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Strong first line (visible before "see more")
-
Short paragraphs with line breaks
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Frame around lessons, results, or professional takeaways
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More explicit context than X (LinkedIn audience needs framing)
Threads adaptation:
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Conversational, casual tone
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Shorter than LinkedIn, less compressed than X
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Visual-first if possible
Bluesky adaptation:
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Direct and concise (300 char limit)
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Community-oriented tone
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Use feeds/lists for topic targeting instead of hashtags
Step 4: Post Primary Platform
Post to the primary platform first:
-
Use
x-apiskill 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:
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Stagger timing (not all at once — 30-60 min gaps)
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Include cross-platform references where appropriate ("longer thread on X" etc.)
Content Adaptation 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:
import os
import requests
resp = requests.post(
"https://your-crosspost-service.example/api/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-apiskill patterns -
LinkedIn: LinkedIn API v2 with OAuth 2.0
-
Threads: Threads API (Meta)
-
Bluesky: AT Protocol API
Quality Gate
Before posting:
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Each platform version reads naturally for that platform
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No identical content across platforms
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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
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