# Twitter Cultivate

> Twitter/X account cultivation and growth system. Checks account health (TweepCred, shadowban), analyzes tweets, finds engagement opportunities, recommends unfollows, and tracks progress. Triggers on "/twitter-cultivate", "check my twitter", "twitter health", "grow my twitter", "twitter maintenance", "fix my twitter reach".

- Skill: `phy041/twitter-cultivate` (Agent Skill)
- Install (CLI): `npx skillmds@latest add phy041/twitter-cultivate`
- Raw SKILL.md: https://api.skillmd.com/api/skills/phy041/twitter-cultivate/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Marketing & Growth
- Author: PHY041 (https://skillmd.com/u/phy041)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/phy041/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

| Metric | Healthy Range | Impact |
|--------|---------------|--------|
| Following/Follower Ratio | **< 0.6** | TweepCred score |
| Avg Views/Tweet | 20-40% of followers | Algorithm favor |
| Media Tweet % | **> 50%** | 10x engagement |
| Link Tweet % | **< 20%** | Avoid algorithm penalty |
| Reply Rate | Reply to 100% of comments | +75 weight boost |

---

## Workflow: Full Health Check

### Step 1: Analyze Account

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

### Step 2: Check Shadowban Status

```bash
python twitter_cultivate.py shadowban <YOUR_USERNAME>
```

Or manually check: [shadowban.yuzurisa.com](https://shadowban.yuzurisa.com)

### Step 3: Analyze Following List

```bash
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

```bash
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

```bash
python twitter_cultivate.py report
```

---

## Account Health Scoring

Based on Twitter's open-source algorithm:

### TweepCred Estimation

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

| Ratio | Estimated TweepCred | Algorithm Treatment |
|-------|---------------------|---------------------|
| < 0.6 | 65+ (healthy) | All tweets considered |
| 0.6 - 2.0 | 40-65 | Limited consideration |
| 2.0 - 5.0 | 20-40 | Severe penalty |
| > 5.0 | < 20 | **Only 3 tweets max** |

---

## 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

| Type | Weight | Recommendation |
|------|--------|----------------|
| Tweet that gets author reply | **+75** | ALWAYS reply to comments |
| Tweet with replies | +13.5 | Ask questions |
| Tweet with profile clicks | +12.0 | Be intriguing |
| Tweet with long dwell time | +10.0 | Use threads |
| Retweet | +1.0 | Low value |
| Like | +0.5 | Lowest value |

### 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)

| Day | Best Time | Second Best |
|-----|-----------|-------------|
| Tuesday | 9-10 AM | 1-2 PM |
| Wednesday | 9-10 AM | 3-4 PM |
| Thursday | 10-11 AM | 2-3 PM |

### 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.

```bash
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

```bash
./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

```bash
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