twitter-cultivate
SKILL.md
Twitter Account Cultivation Skill
Systematic approach to growing Twitter presence based on the open-source algorithm analysis.
Prerequisites
- rnet installed (
pip install "rnet>=3.0.0rc20" --pre) - rnet_twitter.py — the lightweight GraphQL client included in this repo
- Twitter cookies exported to:
twitter_cookies.jsonFormat:[{"name": "auth_token", "value": "..."}, {"name": "ct0", "value": "..."}] - Your Twitter handle configured
Getting Cookies
- Open Chrome → go to
x.com→ log in - DevTools → Application → Cookies →
https://x.com - Copy
auth_tokenandct0values - Save to
twitter_cookies.json(seetwitter_cookies.example.json) - Cookies last ~2 weeks. Refresh when you get 403 errors.
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
import asyncio
from rnet_twitter import RnetTwitterClient
async def analyze(username: str):
client = RnetTwitterClient()
client.load_cookies("twitter_cookies.json")
# Get user profile
user = await client.get_user_by_screen_name(username)
followers = user.get("followers_count", 0)
following = user.get("friends_count", 0)
ratio = following / max(followers, 1)
# Get recent tweets for content analysis
tweets = await client.get_user_tweets(user["rest_id"], count=20)
return {
"username": username,
"followers": followers,
"following": following,
"ratio": round(ratio, 2),
"tweet_count": user.get("statuses_count", 0),
"recent_tweets": len(tweets),
}
asyncio.run(analyze("YOUR_USERNAME"))
Step 2: Check Shadowban Status
Manual check: shadowban.yuzurisa.com
Step 3: Analyze Following List
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
Use search_tweets to find trending conversations:
async def find_opportunities(niche_keywords: list[str]):
client = RnetTwitterClient()
client.load_cookies("twitter_cookies.json")
opportunities = []
for keyword in niche_keywords:
tweets = await client.search_tweets(
f"{keyword} lang:en -filter:replies",
count=50,
product="Top"
)
# Filter for high-engagement, recent tweets
for t in tweets:
if t["favorite_count"] >= 50 and t["reply_count"] < 20:
opportunities.append(t)
return sorted(opportunities, key=lambda t: t["favorite_count"], reverse=True)
Step 5: Generate Weekly Report
Compile metrics from Steps 1-4 into a structured report.
Account Health Scoring
Based on Twitter's open-source algorithm:
TweepCred Estimation
Score = PageRank x (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"
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
Weekly Installs
2
Repository
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