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Generate Social Media Captions

ASecurity

Draft platform-appropriate social captions using a specific audience, message, voice, and call to action.

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  • Added October 22, 2026
ai-agentspythongofastapidjangogitapibackendperformance

Works with

  • cursor
  • cli
  • api

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A100/100

Scanned October 22, 2026

npx -y skills add alivirgo/Major-AI-Skills --skill generate-social-media-captions --agent claude-code

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SKILL.md
---
name: generate-social-media-captions
description: "Draft platform-appropriate social captions using a specific audience, message, voice, and call to action."
category: common-sense
risk: safe
source: self
source_type: self
date_added: "2026-08-26"
tags: ["social-media", "copywriting", "linkedin", "twitter-x", "instagram", "marketing", "prompt-engineering"]
tools: ["claude", "cursor", "gemini", "codex", "chatgpt"]
---

# Generate Social Media Captions (Platform-Native Copywriting) (AI Skill)

## Overview
Default AI social media copy is instantly recognizable and easily ignored: it is loaded with excessive emoji spam (πŸš€ πŸ”₯ ✨), generic motivational filler (*"Thrilled to announce..."*), and 25 irrelevant hashtags.

The **Platform-Native Copywriting Protocol** instructs the model to adhere to the exact typography, character limits, whitespace rhythm, and conversational norms of each specific social network.

---

## Platform Typography & Engagement Matrix

```
β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚                 Platform Format Specifications              β”‚
β”‚                                                             β”‚
β”‚  [ LINKEDIN ]: Thought leadership, 1-line hook, generous    β”‚
β”‚                line breaks, career/business lesson, 0-2 tagsβ”‚
β”‚                                                             β”‚
β”‚  [ X / TWITTER ]: Punchy, ultra-concise, under 280 chars,   β”‚
β”‚                   candid opinion or data chart, 0 hashtags  β”‚
β”‚                                                             β”‚
β”‚  [ INSTAGRAM ]: Casual visual storytelling, relatable voice,β”‚
β”‚                 clean caption + 3-5 niche tags at bottom    β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
```

---

## Master Platform-Specific Prompt Templates

### Pattern 1: The Multi-Platform Announcement Matrix
Use when launching a product, sharing an article, or announcing a milestone:

```markdown
I want to announce [NEWS / MILESTONE / LESSON LEARNED].
Core Message: [INSERT CORE DETAILS & KEY METRIC].

Generate 2 distinct platform-native versions:

### 1. LinkedIn Post (Story-Driven)
- Opening: Punchy, contrarian 1-line hook.
- Structure: Short 1-2 sentence paragraphs with whitespace.
- Content: The human story, the initial struggle/failure, and the key business takeaway.
- Tone: Candid, professional, humble, zero cheesy corporate buzzwords.
- Banned: No "Thrilled to announce", "humbled", "game-changer", or rocket emojis.

### 2. X / Twitter Post (High-Velocity)
- Length: Under 250 characters.
- Tone: Direct, punchy, like an engineer or founder sharing notes.
- Format: Hook + 2 bullet points + 1 link placeholder. Zero hashtags.
```

---

## Real-World Case Study

### Scenario: Announcing an Open-Source Developer Tool

#### Cheesy AI Default Output (Zero Engagement)
> *"πŸš€ Big news! πŸŽ‰ We are thrilled to announce that our groundbreaking new caching tool is now live on GitHub! πŸ’» It will revolutionize your backend performance and take your app to the next level! πŸ”₯ Check it out today! #coding #tech #innovation #ai #developer #software #programming #webdev"*
> 
> ❌ *(Looks like automated spam; zero developers will click).*

#### Platform-Native Crafted Output

#### LinkedIn Version
> Most Redis cache wrappers require 40 lines of boilerplate just to handle connection retries and fallback serialization.
> 
> When our API went down for 12 minutes last month because of a Redis connection pool leak, we decided to fix the problem permanently.
> 
> We built **FastCache**: a zero-config, thread-safe cache engine for Python that automatically handles reconnects and cuts memory overhead by 30%.
> 
> Today, we're making it 100% open source on GitHub.
> 
> If you're running FastAPI or Django in production, give it a spin: `[GITHUB_LINK]`
> 
> What caching strategies has your team found most reliable under load?

#### X (Twitter) Version
> We just open-sourced FastCache: a zero-config Python caching library that eliminates Redis connection pool leaks.
> 
> β€’ Automatic exponential backoff retries
> β€’ 30% lower memory footprint
> β€’ Native async/await support
> 
> GitHub link: `[LINK]`

---

## 3 Anti-Patterns to Ban in Prompts
1. **The "Thrilled/Humbled" Opener**: Ban *"I am thrilled/excited/humbled to share..."*. Start on the problem or insight immediately.
2. **Hashtag Spamming**: Ban more than 2-3 hashtags on LinkedIn and ban them completely on X.
3. **Emoji Overkill**: Limit to maximum 1-2 functional emojis (e.g. πŸ‘‰ for links or β€’ for bullets).

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