Engagement Tracker

Engagement Tracker Skill

Closed-loop analytics for all social media activity. Scrapes engagement metrics 24h after posting, stores structured data, and produces weekly insights.

Core Principle

You can't optimize what you don't measure. Every post gets tracked. Every week gets analyzed. Decisions come from data, not vibes.

Configuration

Set your Twitter handle:

export TWITTER_HANDLE="yourhandle"

Point to your Twikit directory:

export TWIKIT_DIR="~/crawlee-social-scraper"  # wherever you have twikit + cookies

Daily Engagement Check (runs at 07:00 your TZ)

Step 1: Find Yesterday's Posts

Read memory/YYYY-MM-DD.md for yesterday's date. Extract all posted URLs from the log tables.

Reddit comment URLs look like:

https://www.reddit.com/r/{subreddit}/comments/{post_id}/comment/{comment_id}/

Twitter reply URLs look like:

https://x.com/{username}/status/{tweet_id}

Step 2: Scrape Reddit Comment Metrics

For each Reddit comment URL, fetch engagement data via AppleScript Chrome:

osascript -l JavaScript -e '
var chrome = Application("Google Chrome");
var tab = chrome.windows[0].activeTab;
tab.execute({javascript: "(" + function() {
    var commentId = "COMMENT_ID";
    fetch("/api/info.json?id=t1_" + commentId, {credentials: "include"})
        .then(r => r.json())
        .then(d => {
            var c = d.data.children[0].data;
            document.title = "METRICS:" + JSON.stringify({
                id: c.name,
                score: c.score,
                ups: c.ups,
                num_replies: c.num_comments || 0,
                permalink: c.permalink,
                subreddit: c.subreddit,
                body: c.body.substring(0, 100)
            });
        });
} + ")();"});
'
sleep 2
osascript -e 'tell application "Google Chrome" to return title of active tab of first window'

Multi-profile Chrome fallback: Use System Events + Console pattern (see reddit-cultivate skill).

Rate limiting: Wait 2+ seconds between each comment check.

Step 3: Scrape Twitter Reply Metrics

cd $TWIKIT_DIR
source venv/bin/activate
python3 -c "
import asyncio, json
from twikit import Client

async def check():
    client = Client('en-US')
    client.load_cookies('twitter_cookies.json')
    user = await client.get_user_by_screen_name('$TWITTER_HANDLE')
    tweets = await client.get_user_tweets(user.id, tweet_type='Replies', count=20)
    results = []
    for t in tweets:
        results.append({
            'id': t.id,
            'text': t.text[:100],
            'created_at': str(t.created_at),
            'likes': t.favorite_count,
            'retweets': t.retweet_count,
            'replies': t.reply_count,
            'views': t.view_count,
            'in_reply_to': t.in_reply_to_tweet_id,
            'url': f'https://x.com/$TWITTER_HANDLE/status/{t.id}'
        })
    print(json.dumps(results, indent=2))

asyncio.run(check())
"

Step 4: Store Metrics

Append to memory/analytics/engagement-log.json:

{
  "entries": [
    {
      "id": "reddit-2026-01-01-001",
      "date": "2026-01-01",
      "platform": "reddit",
      "type": "comment",
      "subreddit": "SideProject",
      "post_title": "Post title here",
      "url": "https://www.reddit.com/r/SideProject/comments/abc/comment/xyz/",
      "checked_at": "2026-01-02T07:00:00+08:00",
      "hours_since_post": 22,
      "metrics": {
        "upvotes": 12,
        "replies": 3
      }
    }
  ]
}

Step 5: Daily Summary

Report only if there's notable engagement:

Engagement Check (24h metrics)

Reddit (3 comments yesterday):
  r/ClaudeAI "your post topic" — 12 upvotes, 3 replies
  r/SideProject "your post topic" — 8 upvotes, 1 reply

Twitter (2 replies yesterday):
  @somebody — 5 likes, 1500 views
  @someone — 2 likes, 800 views

Top performer: Reddit r/ClaudeAI comment (12 upvotes)
Needs attention: 3 replies on ClaudeAI comment — consider responding!

If no notable engagement (all zeros): Reply HEARTBEAT_OK, no notification.

If replies detected: Flag them for response (author replies = +75 algo weight on Reddit).

Weekly Analysis (runs Sunday)

Reads ALL entries from memory/analytics/engagement-log.json for the current week.

Metrics Computed

Per-Subreddit (Reddit):

Hit Rate = % of posts with upvotes > 5 (adjustable threshold).

Per-Target Account (Twitter):

Actionable Recommendations

Weekly Insights:

1. SHIFT WEIGHT: r/indiehackers has 2.4x better engagement than r/SideProject.
   → Recommend: 2 comments/day in indiehackers, 1 in SideProject

2. SWEET SPOT: Higher quality score comments get 1.75x more upvotes.
   → Recommend: Raise quality bar

3. TIMING: Morning posts outperform evening by 40%.
   → Consider: Add midday posting batch

4. REPLIES UNANSWERED: 7 Reddit replies went unanswered this week.
   → Action: Respond within 24h for algo boost (+75 weight).

Weekly Summary Format

Weekly Engagement Report

REDDIT
  Posts: 21 | Avg upvotes: 7.3 | Best: 23 (r/indiehackers)
  Karma delta: +53
  Hit rate: 62% (>5 upvotes)

TWITTER
  Replies: 18 | Avg likes: 2.8 | Best: 12
  Followers delta: +7
  Avg views: 1,340

TOP 3 POSTS THIS WEEK:
  1. r/indiehackers "auth rebuild" — 23 upvotes, 5 replies
  2. @founder "reply" — 12 likes, 3,200 views
  3. r/ClaudeAI "setup" — 15 upvotes, 4 replies

RECOMMENDATIONS:
  → Shift Reddit weight to r/indiehackers (+2.4x ROI)
  → 7 unanswered replies — respond today!

Data Schema

engagement-log.json (append-only)

{
  "entries": [
    {
      "id": "string (platform-date-seq)",
      "date": "YYYY-MM-DD",
      "platform": "reddit | twitter | linkedin | xhs",
      "type": "comment | reply | original_post",
      "subreddit": "string (reddit only)",
      "target_account": "string (twitter only)",
      "post_title": "string",
      "url": "string",
      "checked_at": "ISO8601",
      "hours_since_post": "number",
      "metrics": {
        "upvotes": "number",
        "likes": "number",
        "retweets": "number",
        "replies": "number",
        "views": "number"
      }
    }
  ]
}

Integration with Other Skills

Feeds Into:

• Weekly Review — reads weekly summary for its report
• Content Multiply — uses performance data to find winners worth repurposing

Reads From:

• memory/YYYY-MM-DD.md — daily logs with posted URLs
• Reddit API (via AppleScript Chrome)
• Twitter API (via Twikit)

Troubleshooting