content-machine

Generate platform-specific social media posts, newsletters, and marketing copy.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/Darshit-Vaghani/swasau_website --skill content-machine-darshit-vaghani
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: content-machine
Source: https://github.com/Darshit-Vaghani/swasau_website/tree/main/.local/secondary_skills/content-machine
Command: npx skills add https://github.com/Darshit-Vaghani/swasau_website --skill content-machine-darshit-vaghani

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It removes the guesswork of writing marketing and social content that actually fits each platform’s mechanics, formats, and truncation behavior.

Core Features & Use Cases

  • Voice-calibrated writing: Analyzes your existing posts (or pulls references) to match sentence rhythm, POV, emoji density, and signature phrasing.
  • Platform mechanics optimization: Produces content sized and structured for real 2025–2026 feed behavior (e.g., LinkedIn mobile truncation, X hook rules, Instagram caption visibility, Story safe-zone layout).
  • Repurposing across channels: Converts one long-form idea into a consistent multi-asset campaign (blog, X thread, LinkedIn post/carousel, newsletter section, Instagram feed/Stories, TikTok/Reels).
  • Hook frameworks and validation: Applies named hook patterns (contrarian, curiosity gap, specificity signal, etc.) and checks platform constraints like char limits and CTA rules.

Quick Start

Ask it to generate a LinkedIn post and matching X thread from your topic, using a voice reference from 3 of your previous posts.

Frequently Asked Questions about content-machine

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I repurpose long-form content into platform-specific social media posts?

Repurposing long-form content into platform-specific social media posts involves converting a single idea into a multi-asset campaign with calibrated hooks, character limits, and CTA placement for LinkedIn, X, Instagram, and TikTok. The process applies named hook frameworks and enforces feed behavior constraints to ensure visibility and engagement across different social channels.

What is platform mechanics optimization for social media copy?

Platform mechanics optimization for social media copy is the process of sizing and structuring posts to match real feed behavior, such as LinkedIn mobile truncation windows, X hook rules, and Instagram Story safe-zone layout requirements. It ensures content fits each platform's specific truncation behavior, format rules, and visibility constraints rather than relying on generic writing.

Can I match my brand's writing voice when generating marketing copy across different platforms?

Matching your brand's writing voice during marketing copy generation requires analyzing existing posts to extract sentence rhythm, point of view, emoji density, and signature phrasing. By using voice references from previous content, the generated copy maintains a consistent brand identity across LinkedIn, X, Instagram, and newsletters while adhering to platform-specific constraints.

How do I write social media hooks that prevent content truncation on mobile feeds?

Writing social media hooks that prevent content truncation on mobile feeds requires applying specific hook frameworks like contrarian, curiosity gap, and specificity signal patterns. You must enforce platform-specific constraints such as hook length limits, character counts, and safe-zone requirements before finalizing the copy to ensure the opening lines capture attention within the truncation window.

Does this approach work for generating both LinkedIn carousels and X threads from one topic?

Generating both LinkedIn carousels and X threads from one topic is supported through multi-platform repurposing, which converts a single long-form idea into a consistent multi-asset campaign. The process applies platform-specific structure rules, validation checklists, and CTA placement guidelines to ensure the output meets the distinct formatting and feed behavior requirements of each channel.

What are the limitations of using generic content generation for multi-platform publishing?

The limitation of using generic content generation for multi-platform publishing is that it ignores platform-specific constraints like truncation windows, character limits, and safe-zone requirements, leading to poorly formatted posts. Without enforcing a validation checklist and platform mechanics optimization, generic copy fails to account for feed behavior, reducing visibility and engagement across LinkedIn, X, and Instagram.