Twitter Cultivate

Twitter Account Cultivation Skill

Systematic approach to growing Twitter presence based on the open-source algorithm analysis.

Prerequisites

• Twikit installed (pip install twikit)
• Twitter cookies exported to: ~/crawlee-social-scraper/twitter_cookies.json (or wherever your Twikit setup lives — set TWIKIT_DIR env var)
• Your Twitter handle configured in state file

Core Metrics to Track

Workflow: Full Health Check

Step 1: Analyze Account

cd ~/crawlee-social-scraper
source venv/bin/activate
python twitter_cultivate.py analyze <YOUR_USERNAME>

Step 2: Check Shadowban Status

python twitter_cultivate.py shadowban <YOUR_USERNAME>

Or manually check: shadowban.yuzurisa.com

Step 3: Analyze Following List

python twitter_cultivate.py unfollow-recs <YOUR_USERNAME> --limit 50

Recommends accounts to unfollow based on:

• No tweets in 90+ days (inactive)
• Never interacted with you (no value)
• Low follower count + high following (likely bots)
• No mutual engagement

Step 4: Find Engagement Opportunities

python twitter_cultivate.py opportunities --niche "AI,startup,founder"

Finds:

• Rising tweets in your niche to reply to
• Accounts similar to yours to engage with
• Trending topics you can contribute to

Step 5: Generate Weekly Report

python twitter_cultivate.py report

Account Health Scoring

Based on Twitter's open-source algorithm:

TweepCred Estimation

Score = PageRank × (1 / max(1, following/followers))

Unfollow Strategy

Priority 1: Inactive Accounts

• No tweets in 90+ days
• Safe to unfollow, no relationship loss

Priority 2: Non-Engagers

• Never liked/replied to your tweets
• One-way relationship

Priority 3: Low-Value Follows

• High following/low followers (bot-like)
• No content in your niche

Execution Plan

Week 1: Unfollow 30 inactive accounts
Week 2: Unfollow 30 non-engagers
Week 3: Unfollow 30 low-value follows
Week 4: Evaluate ratio improvement

Target: Get ratio below 2.0, ideally below 0.6

Content Strategy (Algorithm-Optimized)

Tweet Types by Algorithm Weight

Content Mix

• 40% Value content (insights, tips, frameworks)
• 30% Engagement bait (questions, polls, hot takes)
• 20% Build-in-public (progress updates, wins, losses)
• 10% Promotion (with value attached)

Media Requirements

Every tweet should have ONE of:

• Image (infographic, screenshot, meme)
• Video (< 2:20, hook in first 3 sec)
• Poll
• Thread (7-10 tweets)

NEVER post text-only tweets

Posting Schedule

Optimal Times (General)

First 10 Minutes Protocol

1. Post at optimal time
2. Immediately self-reply with additional insight
3. Reply to ANY comment within 10 minutes
4. Have 2-3 "pod" members ready to RT

Frequency

• Minimum: 1 tweet/day
• Optimal: 3-5 tweets/day
• Gap: 30-60 min between tweets

Engagement Tactics

Reply Strategy (Most Important)

The algorithm gives +75 weight when you reply to replies on your tweets.

Someone comments on your tweet
    ↓
Reply within 30 minutes (CRITICAL)
    ↓
Algorithm sees author engagement
    ↓
Tweet gets boosted to more feeds

Quote Tweet Strategy

Find viral tweet in your niche
    ↓
Quote with your unique take
    ↓
Add value, not just "great point"
    ↓
Post during optimal hours

Thread Formula

1/ Hook (curiosity gap or bold claim)
2-6/ Individual points with specifics
7/ Summary
8/ CTA: Question or "follow for more"

Real-time Monitor & Auto-Reply

Monitor target accounts and auto-generate contextual replies for maximum engagement.

cd ~/crawlee-social-scraper

# Interactive mode (recommended) - approve before posting
./start_monitor.sh

# Monitor only - just watch, no replies
./start_monitor.sh monitor

Customize Targets

./venv/bin/python3 twitter_monitor.py --interactive --targets "levelsio,marc_lou,thedankoe"

How It Works

1. Polls target accounts every 60 seconds
2. Detects new tweets
3. Generates contextual reply
4. Shows you the suggestion
5. You approve/edit/skip

CLI Reference

cd ~/crawlee-social-scraper
source venv/bin/activate

# Full health check
python twitter_cultivate.py analyze <username>

# Check shadowban
python twitter_cultivate.py shadowban <username>

# Get unfollow recommendations
python twitter_cultivate.py unfollow-recs <username> --limit 50

# Find engagement opportunities
python twitter_cultivate.py opportunities --niche "AI,startup"

# Weekly report
python twitter_cultivate.py report

# Execute unfollow (with confirmation)
python twitter_cultivate.py unfollow <username> --execute

Weekly Routine

Daily (15 min)

• Post 1-3 tweets with media
• Reply to ALL comments on your tweets
• Engage with 5-10 tweets in your niche
• Check notifications and respond

Weekly (Saturday)

• Run full health check
• Review what content performed best
• Unfollow 10-20 low-value accounts
• Plan next week's content themes

Monthly

• Full ratio review (target < 2.0)
• Shadowban check
• Content audit (media %, link %)
• Milestone check (follower goals)

Recovery Plan (Low Follower Count)

Phase 1: Emergency Ratio Fix (Week 1-2)

If your ratio is > 5.0 (following >> followers):

• Unfollow 100+ inactive/non-engaging accounts
• Target: ratio < 5.0 as first milestone

Phase 2: Content Upgrade (Week 2-4)

If you have 0% media tweets:

• Add image/video to EVERY tweet
• Use Canva/Figma for quick graphics
• Screenshot interesting data/insights

Phase 3: Engagement Building (Week 3-6)

• Reply to 20+ tweets/day in your niche
• Quote tweet viral content with your take
• Join relevant Twitter communities
• DM potential collaborators

Phase 4: Consistency (Ongoing)

• 3-5 tweets/day
• Reply to 100% of comments
• Weekly analysis and adjustment