platform-mastery

Platform-by-platform algorithm knowledge, best practices, and content adaptation rules for YouTube, LinkedIn, Twitter/X, Reddit, Instagram, GitHub, Threads, and StackOverflow. Use when optimizing content for a specific platform or adapting cross-platform content.

Platform Mastery Skill

Deep algorithm knowledge and content optimization rules for each social platform. Ensures content is native to each platform rather than cross-posted generically.

Platform Quick Reference

| Platform | Algorithm Priority | Content Sweet Spot | Tone | |----------|-------------------|-------------------|------| | YouTube | Watch time + CTR | 8-15 min long-form | Educational, personality-driven | | LinkedIn | Comments > reactions | 1200-1500 chars + image | Professional, insight-driven | | Twitter/X | Engagement rate | 200-280 chars + media | Concise, opinionated | | Reddit | Upvote ratio + authenticity | Text posts, genuine value | Authentic, humble, no marketing | | Instagram | Saves + shares | Carousel (10 slides) | Visual-first, aspirational | | GitHub | Stars + community engagement | README quality + releases | Technical, precise | | Threads | Conversation + reposts | 300-500 chars | Conversational, casual | | StackOverflow | Answer quality score | Canonical answers | Technical, helpful, factual |

YouTube

Algorithm Signals (Priority Order)

  1. Click-through rate (CTR): Thumbnail + title combination. Target >5% CTR.
  2. Average view duration: Percentage of video watched. Target >50%.
  3. Session time: Does your video lead to more YouTube watching? Playlists help.
  4. Engagement rate: Likes, comments, shares — comments weighted highest.
  5. Upload consistency: Regular schedule signals reliability to algorithm.

Content Rules

Optimal Format

youtube:
  length: 8-15 minutes (sweet spot for ad revenue + algorithm)
  title_length: "<60 chars"
  description: "first 150 chars critical (shown in search)"
  tags: 10-15
  thumbnail: "1280x720, high contrast, face + text"
  chapters: "minimum 3, start at 0:00"
  end_screen: "last 20s, 1-2 elements"
  posting_time: "weekdays 2-4 PM viewer timezone"

Anti-Patterns

LinkedIn

Algorithm Signals (Priority Order)

  1. Comments (especially long comments): Highest weight signal
  2. Dwell time: Time spent reading your post
  3. Reactions: Likes and other reactions (comments > reactions)
  4. Shares/reposts: Signal virality to algorithm
  5. Profile authority: SSI score, connection relevance

Content Rules

Post Format

[Hook line — bold claim, counterintuitive take, or personal story opener]

[blank line — critical for mobile]

[2-3 short paragraphs, each 1-2 sentences]

[Key insight or framework — optionally use bullet points]

• Point 1
• Point 2
• Point 3

[Personal reflection or lesson learned]

[Question to drive comments]

#[hashtag1] #[hashtag2] #[hashtag3]

Optimal Format

linkedin:
  length: 1200-1500 chars (sweet spot)
  hashtags: 3-5 (more looks spammy)
  images: 1 (native upload, not link preview)
  links: "in first comment, never in post body"
  posting_time: "Tue-Thu 8-10 AM viewer timezone"
  format: "short paragraphs, line breaks between"
  hook: "first 210 chars (before ...see more)"

Anti-Patterns

Twitter/X

Algorithm Signals (Priority Order)

  1. Engagement rate: Replies + retweets + likes relative to impressions
  2. Media attachments: Images/video boost distribution
  3. Recency: Tweets decay fast — timing matters
  4. Thread completion: Full thread reads signal quality
  5. Profile engagement history: Algorithm favors accounts you interact with

Content Rules

Tweet Formats

# Single tweet (high-impact)
[Bold statement or hot take]

[Supporting evidence or example in 1 sentence]

[Optional: image/screenshot]

# Thread format
🧵 [Hook — why should I read this thread?]

1/ [First point — must stand alone as a tweet]

2/ [Second point — builds on first]

[...]

n/ [Conclusion + CTA — follow, bookmark, retweet]

Optimal Format

twitter:
  tweet_length: 200-280 chars (near limit performs well)
  thread_length: 5-12 tweets
  media: "1 image or 1 short video per tweet"
  hashtags: 0-2 (hashtags less important than on other platforms)
  posting_time: "weekdays 9-11 AM or 1-3 PM"
  reply_strategy: "reply to own tweet with link, add context"
  quote_tweet: "add 1-2 sentences of commentary"

Anti-Patterns

Reddit

Algorithm Signals (Priority Order)

  1. Upvote-to-downvote ratio in first hour: Critical window
  2. Comment volume and quality: Active discussion signals value
  3. Community fit: Content matching subreddit culture
  4. Account karma + age: Spam filtering mechanism
  5. Report ratio: Low reports = trusted content

Content Rules (CRITICAL: Reddit is Anti-Marketing)

Post Format

# Title: [Specific, descriptive, no clickbait — subreddit convention]

[Context: Why you're sharing this. Personal experience preferred.]

[The actual value: step-by-step, findings, data, analysis]

[What you learned or what surprised you]

[Open question: "Has anyone else experienced this?" or "What would you do differently?"]

Optimal Format

reddit:
  title: "descriptive, follows subreddit conventions"
  length: "varies by subreddit — check top posts for norm"
  tone: "authentic, casual, humble"
  self_promotion: "max 10% of activity"
  posting_time: "Sun-Mon morning (US timezones)"
  images: "imgur links for image posts (subreddit dependent)"
  flair: "always use if subreddit requires it"
  crosspost: "use native crosspost, not duplicate posts"

Anti-Patterns

Instagram

Algorithm Signals (Priority Order)

  1. Saves: Strongest signal — content worth returning to
  2. Shares (DMs): Content worth sharing privately
  3. Comments: Engagement depth
  4. Reach to non-followers: Explore page potential
  5. Reel completion rate: For video content

Content Rules

Optimal Format

instagram:
  post_types:
    carousel: "highest engagement, 10 slides, educational"
    reel: "highest reach, 15-30s, trending audio"
    story: "community building, 3-7/day, interactive stickers"
    static: "brand aesthetic, quotes, announcements"
  caption_length: "150-300 chars (before ...more)"
  hashtags: 5-15 in caption or first comment
  image_ratio: "1:1 (feed), 9:16 (reels/stories), 4:5 (portrait)"
  posting_time: "weekdays 11 AM-1 PM or 7-9 PM"
  alt_text: "always include, descriptive"

Anti-Patterns

GitHub

Algorithm Signals (Visibility)

  1. Stars: Primary popularity metric
  2. Forks: Community adoption signal
  3. Contributor count: Active community
  4. README quality: First impression, determines stars
  5. Release frequency: Active maintenance signal
  6. Issue response time: Community health

Content Rules

README Format

# Project Name

[One-line description]

[Badges: CI status, version, license, downloads]

## Quick Start

[3-5 lines to get running — must be copy-pasteable]

## Features

[Bullet list of key features]

## Installation

[Step-by-step, multiple methods if applicable]

## Documentation

[Link to full docs]

## Contributing

[Link to CONTRIBUTING.md]

## License

[License type]

Optimal Format

github:
  readme: "hero + badges + quickstart + features + install"
  releases: "semantic versioning, categorized changelog"
  issues: "templates for bug reports, feature requests"
  discussions: "enabled, categories for Q&A and ideas"
  topics: "5-10 relevant topics/tags"
  social_preview: "1280x640 image"
  license: "always include"

Threads

Algorithm Signals

  1. Reposts: Highest distribution signal
  2. Replies: Conversation depth
  3. Likes: Engagement signal
  4. Cross-posted from Instagram: Slight boost for connected accounts
  5. Recency: Fast-moving feed

Content Rules

Optimal Format

threads:
  length: 300-500 chars
  tone: "casual, conversational, authentic"
  hashtags: 0-2 (platform culture is minimal hashtags)
  images: "optional, less visual than Instagram"
  posting_time: "mirrors Instagram timing"
  cross_post: "from Instagram for additional reach"

StackOverflow

Algorithm Signals

  1. Answer score: Upvotes - downvotes on answers
  2. Accepted answer: Marked by question asker
  3. Answer age + activity: Canonical answers that stay updated
  4. User reputation: Higher rep = more privileges + trust

Content Rules

Optimal Format

stackoverflow:
  answer_structure: "direct answer → code → explanation → docs link"
  tone: "technical, factual, helpful, no opinions"
  code: "always include, tested, minimal reproduction"
  links: "official docs preferred"
  edits: "keep answers current as APIs change"
  questions: "include version, error message, minimal reproduction"

Anti-Patterns

Cross-Platform Adaptation Framework

When adapting content across platforms, transform — don't copy-paste:

adaptation:
  source_platform: "[original platform]"
  target_platform: "[target platform]"
  transformations:
    tone: "[adjust formality level]"
    length: "[compress or expand]"
    format: "[restructure for platform norms]"
    visuals: "[add/remove visual elements]"
    cta: "[platform-appropriate action]"
    hashtags: "[platform-specific strategy]"

Cross-Platform Content Matrix

| Source | → LinkedIn | → Twitter/X | → Reddit | → Instagram | |--------|-----------|-------------|----------|-------------| | Blog post | Extract key insight + personal angle | Thread or key quote tweet | Summarize findings, ask for discussion | Carousel with key points | | Video | Key takeaway + behind-scenes | Clip + hook | Text summary of findings | Reel (15-30s clip) | | Data/research | Professional analysis post | Data point tweet + image | Deep analysis post | Infographic carousel | | Product update | Feature benefit story | Quick announcement + screenshot | "We built X because Y" story | Before/after carousel |

Platform Algorithm Updates

Algorithm knowledge requires periodic updates. When referencing algorithm behavior: