x-twitter-growth
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.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/alirezarezvani/claude-skills --skill x-twitter-growth- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads x-twitter-growth automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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 |
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
Step 2 — Competitive Intelligence
Research competitors and successful accounts in your niche using web search.
Process
- Search
site:x.com "topic" min_faves:100via Brave to find high-performing content - Identify 5-10 accounts in your niche with strong engagement
- For each, analyze: posting frequency, content types, hook patterns, engagement rates
- 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?
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"
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 |
Step 5 — Growth Playbook
Week 1-2: Foundation
- Optimize bio and pinned tweet (Step 1)
- Identify 20 accounts in your niche to engage with daily
- Reply 10-20 times per day to larger accounts (genuine value only)
- Post 2-3 atomic tweets per day testing different formats
- Publish 1 thread
Week 3-4: Pattern Recognition
- Review what formats got most engagement
- Double down on top 2 content formats
- Increase to 3-5 posts per day
- Publish 2-3 threads per week
- Start quote-tweeting relevant content daily
Month 2+: Scale
- Develop 3-5 recurring content series (e.g., "Friday Framework")
- Cross-pollinate: repurpose threads as LinkedIn posts, newsletter content
- Build reply relationships with 5-10 accounts your size (mutual engagement)
- Experiment with spaces/audio if relevant to niche
- Run:
python3 scripts/growth_tracker.py --handle @username --period 30d
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
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
- Posting links directly — Always put links in the first reply, never in the tweet body
- Thread tweet 1 is weak — If the hook doesn't stop scrolling, nothing else matters
- Inconsistent posting — Algorithm rewards daily consistency over occasional bangers
- Only broadcasting — Replies and engagement are 50%+ of growth, not just posting
- Generic bio — "Helping people do things" tells nobody anything
- Copying formats without adapting — What works for tech Twitter doesn't work for marketing Twitter
Related Skills
social-content— Multi-platform content creationsocial-media-manager— Overall social strategysocial-media-analyzer— Cross-platform analyticscontent-production— Long-form content that feeds X threadscopywriting— Headline and hook writing techniques
FAQ
What does the x-twitter-growth skill do?
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.
How do I install x-twitter-growth?
Run npx skills add https://github.com/alirezarezvani/claude-skills --skill x-twitter-growth in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/x-twitter-growth/ (personal) or .claude/skills/x-twitter-growth/ (project).
Which AI agents can use x-twitter-growth?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is x-twitter-growth safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains x-twitter-growth?
It is published by alirezarezvani in alirezarezvani/claude-skills. It has 705 recorded installs.
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