X Bookmarks

Turn X/Twitter bookmarks from a graveyard of good intentions into actionable work.

Core philosophy: Don't just summarize — propose actions the agent can execute.

Prerequisites

• •bird CLI: npm install -g bird-cli (v0.8+)
• •Auth (one of):
  • •--chrome-profile <name> — auto-extracts cookies from Chrome (recommended)
  • •--firefox-profile <name> — Firefox equivalent
  • •Manual: --auth-token <token> --ct0 <token> from browser dev tools
  • •Config: ~/.config/bird/config.json5 with { chromeProfile: "Default" }
• •See references/auth-setup.md for detailed setup guide

Fetching Bookmarks

# Latest 20 bookmarks (default)
bird bookmarks --json

# Specific count
bird bookmarks -n 50 --json

# All bookmarks (paginated)
bird bookmarks --all --json

# With thread context
bird bookmarks --include-parent --thread-meta --json

# With Chrome cookie auth
bird --chrome-profile "Default" bookmarks --json

# With manual tokens
bird --auth-token "$AUTH_TOKEN" --ct0 "$CT0" bookmarks --json

If user has a .env.bird file or env vars AUTH_TOKEN/CT0, source them first: source .env.bird

JSON Output Format

Each bookmark returns:

{
  "id": "tweet_id",
  "text": "tweet content",
  "createdAt": "Wed Feb 11 01:00:06 +0000 2026",
  "replyCount": 46,
  "retweetCount": 60,
  "likeCount": 801,
  "author": { "username": "handle", "name": "Display Name" },
  "media": [{ "type": "photo|video", "url": "..." }],
  "quotedTweet": { ... }
}

Core Workflows

1. Action-First Digest (Primary Use Case)

The key differentiator: don't just summarize, propose actions the agent can execute.

1. •Fetch bookmarks: bird bookmarks -n <count> --json
2. •Parse and categorize by topic (auto-detect: crypto, AI, marketing, tools, personal, etc.)
3. •For EACH category, propose specific actions:
   • •Tool/repo bookmarks → "I can test this, set it up, or analyze the code"
   • •Strategy/advice bookmarks → "Here are the actionable steps extracted — want me to implement any?"
   • •News/trends → "This connects to [user's work]. Here's the angle for content"
   • •Content ideas → "This would make a great tweet/video in your voice. Here's a draft"
   • •Questions/discussions → "I can research this deeper and give you a summary"
4. •Flag stale bookmarks (>2 weeks old) — "Use it or lose it"
5. •Deliver categorized digest with actions

Format output as:

📂 CATEGORY (count)
• Bookmark summary (@author)
→ 🤖 I CAN: [specific action the agent can take]

2. Scheduled Digest (Cron)

Set up a recurring bookmark check. Suggest this cron config to the user:

Schedule: daily or weekly
Payload: "Check my X bookmarks for new saves since last check.
  Fetch bookmarks, compare against last digest, summarize only NEW ones.
  Categorize and propose actions. Deliver to me."

Track state by saving the most recent bookmark ID processed. Store in workspace: memory/bookmark-state.json → { "lastSeenId": "...", "lastDigestAt": "..." }

3. Content Recycling

When user asks for content ideas from bookmarks:

1. •Fetch recent bookmarks
2. •Identify high-engagement tweets (>500 likes) with frameworks, tips, or insights
3. •Rewrite key ideas in the user's voice (if voice data available)
4. •Suggest posting times based on the bookmark's original engagement

4. Pattern Detection

When user has enough bookmark history:

1. •Fetch all bookmarks (--all)
2. •Cluster by topic/keywords
3. •Report: "You've bookmarked N tweets about [topic]. Want me to go deeper?"
4. •Suggest: research reports, content series, or tools based on patterns

5. Bookmark Cleanup

For stale bookmarks:

1. •Identify bookmarks older than a threshold (default: 30 days)
2. •For each: extract the TL;DR and one actionable takeaway
3. •Present: "Apply it today or clear it"
4. •User can unbookmark via: bird unbookmark <tweet-id>

Error Handling

Tips

• •Start with -n 20 for quick digests, --all for deep analysis
• •Use --include-parent to get thread context for replies
• •Bookmark folders are supported via --folder-id <id>
• •Add --sort-chronological for time-ordered output