x-twitter-growth

name	x-twitter-growth
description	X/Twitter growth engine for building audience, crafting viral content, and analyzing engagement. Use when the user wants to grow on X/Twitter, write tweets or threads, analyze their X profile, research competitors on X, plan a posting strategy, or optimize engagement. Complements social-content (generic multi-platform) with X-specific depth: algorithm mechanics, thread engineering, reply strategy, profile optimization, and competitive intelligence via web search.
compatibility	opencode

X/Twitter Growth Engine

X-specific growth skill. For general social media content across platforms, see social-content. For social strategy and calendar planning, see social-media-manager. This skill goes deep on X.

When to Use This vs Other Skills

Need	Use
Write a tweet or thread	This skill
Plan content across LinkedIn + X + Instagram	social-content
Analyze engagement metrics across platforms	social-media-analyzer
Build overall social strategy	social-media-manager
X-specific growth, algorithm, competitive intel	This skill

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Step 1 — Profile Audit

Before any growth work, audit the current X presence. Run scripts/profile_auditor.py with the handle, or manually assess:

Bio Checklist

• Clear value proposition in first line (who you help + how)
• Specific niche — not "entrepreneur | thinker | builder"
• Social proof element (followers, title, metric, brand)
• CTA or link (newsletter, product, site)
• No hashtags in bio (signals amateur)

Pinned Tweet

• Exists and is less than 30 days old
• Showcases best work or strongest hook
• Has clear CTA (follow, subscribe, read)

Recent Activity (last 30 posts)

• Posting frequency: minimum 1x/day, ideal 3-5x/day
• Mix of formats: tweets, threads, replies, quotes
• Reply ratio: >30% of activity should be replies
• Engagement trend: improving, flat, or declining

Run: python3 scripts/profile_auditor.py --handle @username

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Step 2 — Competitive Intelligence

Research competitors and successful accounts in your niche using web search.

Process

1. Search site:x.com "topic" min_faves:100 via Brave to find high-performing content
2. Identify 5-10 accounts in your niche with strong engagement
3. For each, analyze: posting frequency, content types, hook patterns, engagement rates
4. Run: python3 scripts/competitor_analyzer.py --handles @acc1 @acc2 @acc3

What to Extract

• Hook patterns — How do top posts start? Question? Bold claim? Statistic?
• Content themes — What 3-5 topics get the most engagement?
• Format mix — Ratio of tweets vs threads vs replies vs quotes
• Posting times — When do their best posts go out?
• Engagement triggers — What makes people reply vs like vs retweet?

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Step 3 — Content Creation

Tweet Types (ordered by growth impact)

1. Threads (highest reach, highest follow conversion)

Structure:
- Tweet 1: Hook — must stop the scroll in <7 words
- Tweet 2: Context or promise ("Here's what I learned:")
- Tweets 3-N: One idea per tweet, each standalone-worthy
- Final tweet: Summary + explicit CTA ("Follow @handle for more")
- Reply to tweet 1: Restate hook + "Follow for more [topic]"

Rules:
- 5-12 tweets optimal (under 5 feels thin, over 12 loses people)
- Each tweet should make sense if read alone
- Use line breaks for readability
- No tweet should be a wall of text (3-4 lines max)
- Number the tweets or use "↓" in tweet 1

2. Atomic Tweets (breadth, impression farming)

Formats that work:
- Observation: "[Thing] is underrated. Here's why:"
- Listicle: "10 tools I use daily:\n\n1. X — for Y"
- Contrarian: "Unpopular opinion: [statement]"
- Lesson: "I [did X] for [time]. Biggest lesson:"
- Framework: "[Concept] explained in 30 seconds:"

Rules:
- Under 200 characters gets more engagement
- One idea per tweet
- No links in tweet body (kills reach — put link in reply)
- Question tweets drive replies (algorithm loves replies)

3. Quote Tweets (authority building)

Formula: Original tweet + your unique take
- Add data the original missed
- Provide counterpoint or nuance
- Share personal experience that validates/contradicts
- Never just say "This" or "So true"

4. Replies (network growth, fastest path to visibility)

Strategy:
- Reply to accounts 2-10x your size
- Add genuine value, not "great post!"
- Be first to reply on accounts with large audiences
- Your reply IS your content — make it tweet-worthy
- Controversial/insightful replies get quote-tweeted (free reach)

Run: python3 scripts/tweet_composer.py --type thread --topic "your topic" --audience "your audience"

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Step 4 — Algorithm Mechanics

What X rewards (2025-2026)

Signal	Weight	Action
Replies received	Very high	Write reply-worthy content (questions, debates)
Time spent reading	High	Threads, longer tweets with line breaks
Profile visits from tweet	High	Curiosity gaps, tease expertise
Bookmarks	High	Tactical, save-worthy content (lists, frameworks)
Retweets/Quotes	Medium	Shareable insights, bold takes
Likes	Low-medium	Easy agreement, relatable content
Link clicks	Low (penalized)	Never put links in tweet body — use reply

What kills reach

• Links in tweet body (put in first reply instead)
• Editing tweets within 30 min of posting
• Posting and immediately going offline (no early engagement)
• More than 2 hashtags
• Tagging people who don't engage back
• Threads with inconsistent quality (one weak tweet tanks the whole thread)

Optimal Posting Cadence

Account size	Tweets/day	Threads/week	Replies/day
< 1K followers	2-3	1-2	10-20
1K-10K	3-5	2-3	5-15
10K-50K	3-7	2-4	5-10
50K+	2-5	1-3	5-10

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Step 5 — Growth Playbook

Week 1-2: Foundation

1. Optimize bio and pinned tweet (Step 1)
2. Identify 20 accounts in your niche to engage with daily
3. Reply 10-20 times per day to larger accounts (genuine value only)
4. Post 2-3 atomic tweets per day testing different formats
5. Publish 1 thread

Week 3-4: Pattern Recognition

1. Review what formats got most engagement
2. Double down on top 2 content formats
3. Increase to 3-5 posts per day
4. Publish 2-3 threads per week
5. Start quote-tweeting relevant content daily

Month 2+: Scale

1. Develop 3-5 recurring content series (e.g., "Friday Framework")
2. Cross-pollinate: repurpose threads as LinkedIn posts, newsletter content
3. Build reply relationships with 5-10 accounts your size (mutual engagement)
4. Experiment with spaces/audio if relevant to niche
5. Run: python3 scripts/growth_tracker.py --handle @username --period 30d

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Step 6 — Content Calendar Generation

Run: python3 scripts/content_planner.py --niche "your niche" --frequency 5 --weeks 2

Generates a 2-week posting plan with:

• Daily tweet topics with hook suggestions
• Thread outlines (2-3 per week)
• Reply targets (accounts to engage with)
• Optimal posting times based on niche

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Scripts

Script	Purpose
scripts/profile_auditor.py	Audit X profile: bio, pinned, activity patterns
scripts/tweet_composer.py	Generate tweets/threads with hook patterns
scripts/competitor_analyzer.py	Analyze competitor accounts via web search
scripts/content_planner.py	Generate weekly/monthly content calendars
scripts/growth_tracker.py	Track follower growth and engagement trends

Common Pitfalls

1. Posting links directly — Always put links in the first reply, never in the tweet body
2. Thread tweet 1 is weak — If the hook doesn't stop scrolling, nothing else matters
3. Inconsistent posting — Algorithm rewards daily consistency over occasional bangers
4. Only broadcasting — Replies and engagement are 50%+ of growth, not just posting
5. Generic bio — "Helping people do things" tells nobody anything
6. Copying formats without adapting — What works for tech Twitter doesn't work for marketing Twitter

Related Skills

• social-content — Multi-platform content creation
• social-media-manager — Overall social strategy
• social-media-analyzer — Cross-platform analytics
• content-production — Long-form content that feeds X threads
• copywriting — Headline and hook writing techniques