twitter-cultivate

Twitter Account Cultivation Skill

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

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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.json Format: [{"name": "auth_token", "value": "..."}, {"name": "ct0", "value": "..."}]
• Your Twitter handle configured

Getting Cookies

1. Open Chrome → go to x.com → log in
2. DevTools → Application → Cookies → https://x.com
3. Copy auth_token and ct0 values
4. Save to twitter_cookies.json (see twitter_cookies.example.json)
5. Cookies last ~2 weeks. Refresh when you get 403 errors.

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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

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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"))