Xbot

xbot — X (Twitter) Assistant

Post, search, reply, and monitor your X presence from chat. Uses the user's own developer app credentials (pay-per-use).

Script Location

SP_DIR="$HOME/.linggen/skills/xbot/scripts"
[ -d "$SP_DIR" ] || SP_DIR="$PWD/.linggen/skills/xbot/scripts"

Core Workflows

1. Check Status

bash "$SP_DIR/status.sh"

2. Setup / Configure

Important: Do NOT ask the user to paste API keys into chat and do NOT read credential files. Just tell the user how to create/edit the file themselves.

Show the user these steps:

1. Register at developer.x.com and create an App
2. Buy credits under Billing → Credits ($5 minimum — X API is pay-per-use)
3. Set User authentication permissions to Read and Write
4. In Keys and Tokens tab, copy your Consumer Key and Consumer Secret
5. Under Access Token, click Generate to get Access Token and Access Token Secret
6. Run:

mkdir -p ~/.linggen/skills/xbot/credentials
touch ~/.linggen/skills/xbot/credentials/x.env

7. Open ~/.linggen/skills/xbot/credentials/x.env in your editor and add:

X_API_KEY="<Consumer Key>"
X_API_SECRET="<Consumer Secret>"
X_ACCESS_TOKEN="<Access Token>"
X_ACCESS_TOKEN_SECRET="<Access Token Secret>"

8. Tell me when done — I'll verify with status.sh

3. Post a Tweet

bash "$SP_DIR/post-x.sh" "Your message here"

Or use Python for better Unicode/quoting support:

python3 "$SP_DIR/x_api.py" && python3 -c "
import sys; sys.path.insert(0, '$SP_DIR')
from x_api import api_post
status, data = api_post('/tweets', {'text': '''MESSAGE_HERE'''})
print(data)
"

4. Search Tweets

Find recent tweets about a topic:

python3 "$SP_DIR/search.py" "AI coding agent" 10

Use this to:

• Find relevant conversations to join
• Research what people say about competitors
• Discover trending topics in your space

5. Reply to a Tweet

python3 "$SP_DIR/reply.py" "https://x.com/user/status/123456" "Your reply text"

Accepts either a tweet URL or a tweet ID.

6. Check Mentions

See who's mentioning or replying to you:

python3 "$SP_DIR/mentions.py" 10

7. View My Tweets + Engagement

See your recent tweets with likes, retweets, replies, and views:

python3 "$SP_DIR/my_tweets.py" 10

8. Summarize and Post

When the user says something like "summarize today and post to X":

1. Read the current session's conversation history
2. Draft a concise, engaging tweet (under 280 chars)
3. Show the draft to the user for approval
4. Once approved, post

9. Scout and Engage

When the user says "find conversations about ":

1. Run search.py with the topic
2. Show the most relevant/engaging tweets
3. Suggest which ones to reply to
4. Draft a helpful, non-spammy reply for each
5. Post replies only after user approval

10. Release Announcement

When the user says "announce release" or "post about release":

1. Check recent git log or changelog for what's new
2. Draft a tweet with key highlights
3. Include the project URL
4. Suggest relevant hashtags
5. Post after approval

Smart Behaviors

• Scout mode: When searching, prioritize tweets from users with more followers and tweets with high engagement — those are better conversations to join
• Reply tone: Be helpful and genuine, never promotional. Add value to the conversation. Mention the project only if directly relevant.
• Thread support: For longer content, suggest splitting into a thread (post first tweet, then reply to it with continuations)
• Hashtag suggestions: For dev tools, suggest tags like #opensource #ai #rust #coding #devtools when relevant

Limits

• 280 characters per tweet
• $0.01 per post, search is cheaper ($0.001/request)
• No media uploads via API

Important Rules

• Always show the draft to the user before posting or replying — never auto-post
• If text exceeds 280 chars, warn and suggest trimming
• If credentials are missing, run status.sh and guide user through setup
• Never spam — replies should add genuine value to the conversation