X Bookmarks Digest

Automatically review X/Twitter bookmarks for useful tools, projects, repos, products, and ideas. Fetches via xurl, analyses for value, and outputs an actiona...

Security Scan

The skill's code, instructions, and requirements are coherent with its stated purpose of fetching and analysing X/Twitter bookmarks via the xurl CLI and producing a local digest; it does not request unrelated credentials or install arbitrary third-party code.

Purpose & Capability

The skill needs python3 and xurl and uses them to fetch bookmarks, categorise them, and output a digest. Required binaries, local state.json usage, and proposed actions (git clone, brew install, clawhub install) are consistent with the described purpose.

Instruction Scope

SKILL.md and scripts limit actions to: checking xurl auth, invoking xurl to fetch bookmarks, analysing the fetched JSON, and updating a local state.json. The instructions do not read unrelated system files or environment variables, nor do they transmit data to external endpoints other than the X API via the xurl CLI. The skill explicitly requires user confirmation before executing proposed actions (no automatic installs).

Install Mechanism

There is no install spec; this is instruction/code-only and relies on system python3 and xurl. No downloads or remote installs are performed by the skill itself, minimizing install-time risk.

Credentials

The skill declares no required environment variables or credentials. It delegates X API auth to the xurl CLI (which manages tokens). The only persistent file is a local state.json storing bookmark watermark and timestamps — consistent with the stated rate-limiting behavior.

Persistence & Privilege

always is false and the skill writes only its own state.json in its base directory. It does not modify other skills or system-wide agent settings. Autonomous invocation is allowed by default (platform normal) but not inherently excessive here.

Assessment

This skill appears to do what it says: it calls the locally-installed xurl CLI, fetches bookmarks, runs local Python scripts to categorise them, and updates a local state.json file. Before installing, consider: 1) Ensure you trust the xurl CLI and its authentication method (xurl will manage any X tokens). 2) The skill will create/update state.json in the skill directory (only IDs/timestamps are stored). 3) The agent will propose actions like git clone, brew install, or clawhub install but the SKILL.md explicitly says not to auto-execute — only proceed with those actions after you review and confirm. 4) If you prefer more control, run the included scripts manually (they are provided) rather than allowing autonomous execution. If you want extra assurance, review the three scripts (fetch_bookmarks.py, analyse_bookmarks.py, digest_runner.sh) yourself — they are small and readable.

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}

## Medium Value (relevance 3)
{same format, briefer}

## Proposed Actions
1. [ ] {action 1}
2. [ ] {action 2}
...

Step 5: Decide on Actions

For each high-value bookmark, decide:

Bookmark Type	Action
GitHub repo / tool	Propose git clone or brew install
Clawhub-compatible skill	Propose clawhub install <slug>
Interesting project to build	Propose scaffolding a new skill in skills/
Useful article/thread	Propose saving to Obsidian vault
Tip/technique	Propose saving to OpenClaw memory

Ask the user which actions to execute. Do not auto-execute without confirmation.

Step 6: Update State

After successful digest, verify state was updated:

cat {baseDir}/state.json

Should show updated last_bookmark_id and last_run_ts.

Error Handling

Problem	Action
xurl not found	Tell user: brew install xurl
xurl 401	Guide user through xurl auth apps add setup
xurl 429 (rate limit)	Report rate limit hit. Suggest waiting 15 mins.
Empty bookmarks	Report "No bookmarks found" — user may need to bookmark posts first
No new bookmarks	Report "No new bookmarks since {last_run_ts}"
state.json missing	First run — create fresh state after fetch
Python error	Print stderr, check Python 3.10+ installed

Test Commands

Quick test (dry run, no state update):

# Test xurl auth
xurl whoami

# Test fetch (small batch)
python3 {baseDir}/scripts/fetch_bookmarks.py --count 5 --force

# Test analyse (with sample data)
echo '[{"id":"1","text":"Check out this amazing CLI tool https://github.com/user/repo","author_username":"devuser","created_at":"2026-03-19T10:00:00Z"}]' | python3 {baseDir}/scripts/analyse_bookmarks.py

# Full pipeline test
python3 {baseDir}/scripts/fetch_bookmarks.py --count 10 --force | python3 {baseDir}/scripts/analyse_bookmarks.py

Or just say: "digest x bookmarks" to run the full workflow.

Configuration

All config is in {baseDir}/state.json:

• last_bookmark_id — watermark for incremental fetches
• last_run_ts — rate limit enforcement
• processed_count — running total of processed bookmarks

No additional configuration files needed. xurl manages its own auth.