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twitter-cli-skill

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Updated 10-16 06:18

About this skill

twitter-cli

Skill by ara.so — Devtools Skills collection.

Overview

twitter-cli is a Python-based terminal CLI for Twitter/X that works without API keys. It uses browser cookie authentication to read timelines (For You, Following), bookmarks, search results, user profiles, and post/delete tweets. All commands support structured output (--json, --yaml) for AI agent pipelines.

Key capabilities:

  • Read: feed, bookmarks, search, tweet detail, article, list timeline, user lookup
  • Write: post, reply, quote, delete, like, retweet, bookmark
  • Auth: browser cookie extraction (Arc/Chrome/Edge/Firefox/Brave) or env vars
  • Anti-detection: TLS fingerprinting, full cookie forwarding, request jitter
  • Output: rich tables (default), JSON, YAML, Markdown (articles)

Installation

# Recommended: uv tool (fast, isolated)
uv tool install twitter-cli

# Alternative: pipx
pipx install twitter-cli

# Upgrade to latest
uv tool upgrade twitter-cli

From source:

git clone git@github.com:jackwener/twitter-cli.git
cd twitter-cli
uv sync

Authentication

Priority order:

  1. Environment variables: TWITTER_AUTH_TOKEN + TWITTER_CT0
  2. Browser cookies (auto-extracted from Arc/Chrome/Edge/Firefox/Brave)

Browser cookie extraction (recommended):

# Auto-detect browser and extract all Twitter cookies
twitter feed

# Specify browser explicitly
TWITTER_BROWSER=chrome twitter feed

# Chrome multi-profile
TWITTER_CHROME_PROFILE="Profile 2" twitter feed

Manual environment variables:

export TWITTER_AUTH_TOKEN="your_auth_token"
export TWITTER_CT0="your_ct0_token"
twitter feed

Proxy support:

export TWITTER_PROXY=http://127.0.0.1:7890
# or
export TWITTER_PROXY=socks5://127.0.0.1:1080

Core Commands

Read Timeline

# For You feed (default)
twitter feed

# Following feed
twitter feed -t following

# Limit results
twitter feed --max 20

# Full text (no truncation)
twitter feed --full-text

# Structured output for agents
twitter feed --json
twitter feed --yaml

# With ranking filter
twitter feed --filter --max 50

# Pagination cursor
twitter feed --cursor "DAABCgABGdE..."

Search

# Basic search
twitter search "AI agent"

# Search type: Top, Latest, Photos, Videos
twitter search "machine learning" -t Latest

# Full text + JSON output
twitter search "python" --full-text --json

# Advanced filters
twitter search "climate" --from scientist --lang en --since 2026-01-01
twitter search "news" --exclude retweets --has links

# Save to file
twitter search "trending" -o results.json

# Apply ranking filter
twitter search "tech" --filter

Bookmarks

# List bookmarks
twitter bookmarks

# Limit + full text
twitter bookmarks --max 30 --full-text

# Export as YAML
twitter bookmarks --yaml

Tweet Detail (tweet + replies)

# By tweet ID
twitter tweet 1234567890

# By URL
twitter tweet https://x.com/user/status/1234567890

# Full text in reply table
twitter tweet 1234567890 --full-text

# Structured output
twitter tweet 1234567890 --json

Show Command (open tweet by index)

# After running `twitter feed` or `twitter search`:
twitter show 2                    # Open tweet #2 from last list
twitter show 2 --full-text
twitter show 2 --json

Twitter Article (fetch and export as Markdown)

# By article ID
twitter article 1234567890

# By URL
twitter article https://x.com/user/article/1234567890

# Export as Markdown
twitter article 1234567890 --markdown
twitter article 1234567890 --output article.md

# JSON output
twitter article 1234567890 --json

List Timeline

# Fetch tweets from a Twitter List
twitter list 1539453138322673664

# Pagination
twitter list 1539453138322673664 --cursor "DAABCgABGdE..."

# Full text
twitter list 1539453138322673664 --full-text

User Lookup

# Profile
twitter user elonmusk

# User tweets
twitter user-posts elonmusk --max 20
twitter user-posts elonmusk --full-text -o tweets.json

# User likes (own account only, private since Jun 2024)
twitter likes elonmusk --max 30

# Followers
twitter followers elonmusk --max 50

# Following
twitter following elonmusk --max 50

Write Operations

Post Tweet

# Simple tweet
twitter post "Hello from twitter-cli!"

# Tweet with image (up to 4)
twitter post "Hello!" --image photo.jpg
twitter post "Gallery" -i a.png -i b.jpg -i c.webp

# Structured output
twitter post "Hello from twitter-cli!" --json

Reply

# Reply to tweet
twitter post "Nice!" --reply-to 1234567890

# Reply with image
twitter reply 1234567890 "Great!" -i screenshot.png

Quote Tweet

# Quote with text
twitter quote 1234567890 "Check this out"

# Quote with image
twitter quote 1234567890 "Look at this chart" -i chart.png

Delete Tweet

twitter delete 1234567890

Like / Unlike

twitter like 1234567890
twitter like 1234567890 --yaml
twitter unlike 1234567890

Retweet / Unretweet

twitter retweet 1234567890
twitter unretweet 1234567890

Bookmark / Unbookmark

twitter bookmark 1234567890
twitter unbookmark 1234567890

Follow / Unfollow

twitter follow elonmusk --json
twitter unfollow elonmusk

Configuration

Create config.yaml in your working directory:

fetch:
  count: 50

filter:
  mode: "topN"          # "topN" | "score" | "all"
  topN: 20
  minScore: 50
  lang: []
  excludeRetweets: false
  weights:
    likes: 1.0
    retweets: 3.0
    replies: 2.0
    bookmarks: 5.0
    views_log: 0.5

rateLimit:
  requestDelay: 2.5     # base delay (randomized ×0.7–1.5)
  maxRetries: 3
  retryBaseDelay: 5.0
  maxCount: 200

Scoring formula:

score = likes_w * likes
      + retweets_w * retweets
      + replies_w * replies
      + bookmarks_w * bookmarks
      + views_log_w * log10(max(views, 1))

Filter modes:

  • topN: Keep highest N tweets by score
  • score: Keep tweets where score >= minScore
  • all: Return all tweets sorted by score

AI Agent Usage

All commands support --json or --yaml for structured output. Non-TTY stdout defaults to YAML.

Example: Fetch and parse timeline

import subprocess
import yaml

result = subprocess.run(
    ["twitter", "feed", "--max", "10", "--yaml"],
    capture_output=True,
    text=True,
    check=True
)
data = yaml.safe_load(result.stdout)
for tweet in data["tweets"]:
    print(f"{tweet['author']['username']}: {tweet['text']}")

Example: Post tweet from Python

import subprocess
import json

result = subprocess.run(
    ["twitter", "post", "Hello from Python!", "--json"],
    capture_output=True,
    text=True,
    check=True
)
response = json.loads(result.stdout)
print(f"Tweet ID: {response['tweetId']}")

Example: Search and filter

# Get top 10 AI tweets from today as JSON
twitter search "AI agent" --since 2026-05-17 --filter --max 10 --json

Structured output contract: See SCHEMA.md

Common Patterns

Export bookmarks to file

twitter bookmarks --max 100 --json > bookmarks.json

Monitor user tweets

# Fetch latest 5 tweets from user
twitter user-posts elonmusk --max 5 --yaml

Search and rank by engagement

# Top 10 tweets about "AI" by score
twitter search "AI" --filter --max 10 --full-text

Post with multiple images

twitter post "My photo gallery" -i img1.jpg -i img2.png -i img3.webp

Reply to tweet with image

twitter reply 1234567890 "Here's the screenshot" -i screenshot.png

Extract article as Markdown

twitter article 1234567890 --markdown --output ~/articles/ai-safety.md

Use proxy for all requests

export TWITTER_PROXY=http://127.0.0.1:7890
twitter feed --max 20

Troubleshooting

No Twitter cookies found

Solution:

  1. Log in to x.com in a supported browser (Arc/Chrome/Edge/Firefox/Brave)
  2. Or set TWITTER_AUTH_TOKEN and TWITTER_CT0 manually
  3. Run with -v for diagnostics: 
    twitter -v feed

Cookie expired (HTTP 401/403)

Solution: Re-login to x.com and retry.

Keychain access denied (macOS)

SSH sessions:

security unlock-keychain ~/Library/Keychains/login.keychain-db

Local terminal:

  • Open Keychain Access → search for "<Browser> Safe Storage"
  • Access Control → add Terminal app → Save Changes
  • Or click "Always Allow" when prompted

Twitter API error 404

Solution: Retry command. The client attempts a live queryId fallback when GraphQL IDs rotate.

Invalid tweet JSON file

Solution: Regenerate using:

twitter feed --json > tweets.json

Windows: no pipe output in AI agent subprocess

Issue: ConPTY intercepts pipe output from network commands.

Fix:

  1. Use Git Bash as terminal shell
  2. Set "windowsEnableConpty": false in terminal settings
  3. Standard subprocess.run(capture_output=True) works correctly

Rate limiting (HTTP 429)

Solution:

  • Use --max to limit requests
  • Set TWITTER_PROXY to avoid direct IP exposure
  • Increase rateLimit.requestDelay in config.yaml
  • Use residential proxies instead of datacenter IPs

Best Practices

  1. Use a proxy — set TWITTER_PROXY to avoid direct IP exposure
  2. Keep request volumes low — prefer --max 20 over --max 500
  3. Don't run too frequently — each startup fetches x.com to initialize headers
  4. Use browser cookie extraction — provides full cookie fingerprint
  5. Avoid datacenter IPs — residential proxies are safer
  6. Upgrade regularly — uv tool upgrade twitter-cli to avoid outdated API handling

Output Modes

  • Rich table (default): Interactive reading in terminal
  • --full-text: Show full tweet text in tables
  • --yaml: Structured output for agents (default for non-TTY)
  • --json: Strict JSON for parsers
  • -c / --compact: Token-efficient compact output
  • -o FILE: Save to file

Development

# Install dev dependencies
uv sync --extra dev

# Lint
uv run ruff check .

# Tests
uv run pytest -q

Project Structure

twitter_cli/
├── cli.py           # Command-line interface
├── client.py        # HTTP client + anti-detection
├── graphql.py       # GraphQL query IDs, URL building
├── parser.py        # Tweet/User/Media parsing
├── auth.py          # Cookie extraction
├── config.py        # Configuration loading
├── filter.py        # Ranking/scoring logic
├── formatter.py     # Rich table formatting
├── output.py        # JSON/YAML serialization
└── models.py        # Data models (Tweet, User, Media)

Example Workflows

Daily AI news digest

# Search AI tweets from today, rank by engagement, export as JSON
twitter search "AI" --since 2026-05-17 --filter --max 20 --json > ai_digest.json

Bookmark analysis

import subprocess
import yaml
from collections import Counter

result = subprocess.run(
    ["twitter", "bookmarks", "--max", "200", "--yaml"],
    capture_output=True, text=True, check=True
)
data = yaml.safe_load(result.stdout)

# Extract hashtags
hashtags = []
for tweet in data["tweets"]:
    hashtags.extend([h["text"] for h in tweet.get("hashtags", [])])

print(Counter(hashtags).most_common(10))

Post with automated image

import subprocess

# Generate chart, then post with image
subprocess.run(["python", "generate_chart.py"], check=True)
subprocess.run([
    "twitter", "post",
    "Daily metrics update",
    "-i", "chart.png",
    "--json"
], check=True)

Monitor user and alert on keyword

#!/bin/bash
# Cron job: check user tweets for keyword
tweets=$(twitter user-posts elonmusk --max 5 --yaml)
if echo "$tweets" | grep -q "Mars"; then
  echo "Alert: New Mars tweet from @elonmusk"
fi

Related Projects

License: Apache-2.0
Repository: https://github.com/jackwener/twitter-cli
PyPI: https://pypi.org/project/twitter-cli/