Platform Mastery

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

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

• Hook in first 5 seconds — no intros, logos, or "hey guys welcome back"
• Retention triggers every 60-90 seconds (pattern interrupts, open loops)
• Chapters (3+ timestamps starting at 0:00) — improves search + UX
• End screens in last 20 seconds — link to related content
• Thumbnail: 3-5 words max, readable at 100px width, face + emotion
• Title: <60 chars, front-load keyword, curiosity gap

Optimal Format

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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

• Asking to "smash that like button" before delivering value
• Thumbnails with >5 words of text
• First 30 seconds of logos, channel intros, sponsor reads
• Generic tags ("tutorial", "how to")

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

• First 3 lines are everything — hook before "...see more" truncation
• Line breaks after every 1-2 sentences (mobile readability)
• End with a question — drives comments (algorithm's top signal)
• Personal stories outperform corporate content 3-5x
• Images increase engagement 2x (single image > carousel on LinkedIn)
• Native documents (PDF carousels) get high dwell time
• No external links in post body — put links in first comment

Post Format

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[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

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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

• Starting with "I'm excited to announce..."
• Wall of text without line breaks
• External links in post body (kills reach)
• Hashtag stuffing (>5 hashtags)
• Corporate jargon ("synergy", "leverage", "disrupt")

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

• One idea per tweet — don't cram multiple concepts
• Strong opening — first 7 words determine if people read
• Threads for long-form: Tweet 1 is the hook, each tweet is self-contained
• Media boosts reach: Image, screenshot, or short video
• Quote tweets with commentary outperform plain retweets
• Reply to your own tweet with additional context or links

Tweet Formats

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# 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

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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

• Hashtag stuffing (Twitter isn't Instagram)
• Threads that could be a single tweet
• Starting tweets with "1/" without a hook
• Posting only links without commentary
• Engagement bait ("Like if you agree")

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)

• NO marketing speak — Reddit users detect and punish self-promotion
• Value-first, brand-never: Share knowledge, not products
• Read subreddit rules before posting — each sub has specific requirements
• Authentic tone: Write like a human, not a brand
• Text posts outperform links in most subreddits
• Respond to every comment on your posts (signals engagement)
• The 10:1 rule: 10 genuine community interactions per 1 self-promotional post

Post Format

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# 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

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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

• Sounding like a press release
• Using marketing buzzwords ("game-changer", "revolutionary")
• Posting the same content to multiple subreddits without adaptation
• Not reading subreddit rules before posting
• Ignoring comments on your posts
• New account with only self-promotional posts

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

• Visual-first — text is secondary to visual impact
• Carousels get highest engagement (10 slides, save-worthy)
• Reels for reach, carousels for engagement, Stories for community
• Caption structure: Hook line → value → CTA → hashtags
• Hashtag strategy: 5-15 relevant hashtags, mix of sizes
• Stories: 3-7 per day, use polls/questions for engagement
• Alt text: Always add for accessibility + SEO

Optimal Format

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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

• Text-heavy images (Instagram is visual-first)
• Using all 30 hashtags (looks spammy)
• Ignoring Stories and Reels (feed-only strategy is dead)
• Cross-posting Twitter screenshots
• No alt text on images

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 is your landing page — treat it like a conversion page
• Structured README: Badge bar → hero → install → quickstart → docs link
• Release notes: Detailed, categorized (Added, Changed, Fixed, Removed)
• Discussions: Use for community engagement, not just Issues
• Contributing guide: Lower barrier to contribution
• Issue templates: Structured bug reports and feature requests

README Format

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# 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

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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

• Conversational tone — Threads is casual, not professional
• Shorter than Twitter — 300-500 chars sweet spot
• No hashtags (minimal hashtag culture)
• Cross-post from Instagram for connected reach
• Early-adopter advantage — algorithm still favoring content

Optimal Format

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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

• Answer the question directly first — explanation after
• Code examples are mandatory for programming questions
• Cite documentation — link to official sources
• Edit and improve — update answers as languages/frameworks evolve
• No opinions — factual, documented, reproducible answers
• Formatting matters — code blocks, headers, lists

Optimal Format

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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

• Opinion-based answers without documentation backing
• Link-only answers
• "Did you try googling?" responses
• Answering without code examples
• Not including version numbers

Cross-Platform Adaptation Framework

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

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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

Platform Algorithm Updates

Algorithm knowledge requires periodic updates. When referencing algorithm behavior:

• State the general principle (durable) separately from specific weights (temporal)
• Note that exact algorithm weights change frequently
• Focus on user behavior signals — these are more stable than algorithm internals
• Test assumptions with data rather than relying on hearsay