OpenClaw Recipes: Building an Automated Twitter AI News Pipeline

Original author: sitin (@sitinme) · Original tweet · WeChat article

OpenClaw comes with dozens of built-in skills. I originally planned to write a roundup of skill use cases, but the bird skill alone turned out to have so many practical applications that it deserves its own article.

Bird is essentially a Twitter CLI tool — it can read tweets, search, browse timelines, check trending topics, and even post. Combined with OpenClaw’s scheduled tasks and Lark/Feishu webhooks, you can build a complete Twitter news automation pipeline.

Quick note: bird requires setting up Twitter cookies for authentication on first run — just follow the prompts.

Here are a few setups I’m currently using.

Case 1: Daily AI Trending Tweets Digest

The most basic and practical setup: receive a daily morning summary of trending AI tweets without manually scrolling through Twitter.

You can ask something like:

“Collect tweets from tech bloggers with 20k+ followers on Twitter. I want to see the latest trending AI tweets.”

Since bird CLI can’t fetch follower counts, I recommend maintaining a curated list manually. An easier approach is using Twitter Lists — create one for AI influencers (or find an existing one), and bird can read the list’s timeline directly.

“Focus on these users’ tweets daily, but filter for original posts with high engagement — say, 10k+ impressions. Automatically add new trending content or quality accounts.”

Set up details like time range, deduplication, and “no content, no push” rules. Then configure a scheduled task — say, 9 AM daily — to push the digest via Lark webhook.

Results? I’ve configured several AI news scraping rules, and the content coming back is basically exactly what I want with minimal noise.

Case 2: Continuous Topic Tracking

Scraping trending content is just the basics. When a topic blows up, you can have it continuously tracked:

“OpenClaw is trending lately — track this topic for a week, compile new discussions and use cases daily.”

This approach is perfect for following a trending event’s full lifecycle without manual searching every day.

Case 3: Official Account Monitoring + Auto-Translation

A lot of first-hand information lives on Twitter, especially from major AI companies’ official accounts. You can have bird watch these accounts and translate new updates:

“Monitor @AnthropicAI @OpenAI and similar official accounts — translate new tweets to Chinese and push them to me.”

I’d recommend adding filter conditions: only push on major events like model updates or new feature launches, otherwise you’ll be flooded with routine tweets.

Once configured, you’ll be among the first to know about new model releases and feature launches. These past few days, with OpenAI Codex 5.3 dropping and Claude Code’s Opus 4.6 going live, every piece of news was pushed to my Lark group in real time.

Case 4: Content Research

Bird can also be used for content creation research. It supports Twitter advanced search syntax — min_faves:500 for high-engagement filtering, from:username for specific users, since:2026-02-01 for date ranges — enabling very precise tweet scraping:

“Use bird to search AI tweets from the past week with 500+ likes, analyze their topics and opening hooks, save to Notion.”

For Notion integration, you’ll need to set up the Notion API:

1. Create an Integration at https://notion.so/my-integrations → copy the API Key
2. Save the key: mkdir -p ~/.config/notion && echo "YOUR_API_KEY" > ~/.config/notion/api_key
3. Authorize: open your target Notion page/database → click … → Connect to → select your Integration

Lark’s multidimensional tables also work well for this, especially for team collaboration.

For those building international products, the same approach works for competitor monitoring — tracking competitor accounts, user feedback, and PR moves.

You can also combine bird with the summarize skill to extract summaries from linked articles in trending tweets, significantly increasing information density.

Important Notes

• Bird supports posting tweets, but there’s an account suspension risk — test with a secondary account
• Don’t set scraping frequency too high — once per hour is sufficient to avoid Twitter rate limiting
• Bird CLI can’t fetch follower counts — maintain influencer lists manually or use the Twitter List approach
• Add deduplication and “no content, no push” logic to scheduled tasks to avoid notification spam