X Bookmarks Digest

Fetch, analyse, and digest your X/Twitter bookmarks into actionable insights.

When to Use

Activate this skill when the user says anything like:

• "digest x bookmarks"
• "check my bookmarks"
• "review my x bookmarks"
• "what's interesting in my bookmarks?"
• "bookmark digest"
• "any good stuff in my twitter bookmarks?"

Prerequisites Check

Before running the workflow, verify xurl authentication:

xurl whoami

If 401/Unauthorized: Tell the user to set up xurl authentication:

xurl auth apps add <app-name> --client-id <id> --client-secret <secret>

Then run xurl auth default <app-name> to set it as default. Do NOT proceed until auth works. Stop and report the issue.

Workflow — Step by Step

Step 1: Check Rate Limit

Read the state file to check when the last run was:

cat {baseDir}/state.json 2>/dev/null || echo '{"last_bookmark_id": null, "last_run_ts": null, "processed_count": 0}'

If last_run_ts is less than 1 hour ago, warn the user:

"Last digest was run at {time}. Free tier allows max 1 run/hour. Use --force to override."

Only proceed if:

• No previous run exists, OR
• More than 1 hour has elapsed, OR
• User explicitly says to force/override

Step 2: Fetch Bookmarks

Run the fetch script to get new bookmarks:

python3 {baseDir}/scripts/fetch_bookmarks.py --count 50

Options:

• --count N — number of bookmarks to fetch (default 50, max 100)
• --force — skip rate limit check
• --all — fetch all (ignore last-checked ID, reprocess everything)

Output: JSON array of bookmark objects to stdout. Side effect: Updates {baseDir}/state.json with new watermark.

If the output is empty or [], report: "No new bookmarks since last check."

Step 3: Analyse Bookmarks

Pipe the fetched bookmarks through the analyser:

python3 {baseDir}/scripts/fetch_bookmarks.py --count 50 | python3 {baseDir}/scripts/analyse_bookmarks.py

Or if you saved fetch output to a variable, pass it via file:

python3 {baseDir}/scripts/analyse_bookmarks.py --file /tmp/bookmarks.json

Output: Structured JSON with categories and relevance scores:

{
  "summary": {"total": 50, "new": 12, "high": 4, "medium": 5, "low": 3},
  "bookmarks": [
    {
      "id": "123",
      "text": "...",
      "author": "@user",
      "category": "tool",
      "relevance": 5,
      "urls": ["https://github.com/..."],
      "github_repos": ["user/repo"],
      "keywords": ["python", "cli"]
    }
  ]
}

Step 4: Generate Digest

Using the structured analysis output, write a digest following this format:

# X Bookmarks Digest — {date}

## Summary
- {total} bookmarks checked, {new} new since last run
- {high} high-value, {medium} medium, {low} low

## High Value (relevance 4-5)

### [{category}] {title or key topic}
@{author}: "{first 100 chars of text}..."
- URL: {extracted url}
- Why: {1-line explanation of value}
- Action: {specific next step}