Content Audit

Content Audit Skill

Identify what content has worked best for the user so future posts double down on winning topics, formats, and timing.

Required Apify Actors

Confirm the user has Apify connected and the following actors available before scraping. Each actor bills independently — point the user to the Store links if any are missing.

Medium and Substack are publicly accessible — use web_fetch on the archive URL directly.

Step 1 — Identify Platforms to Audit

Ask which platforms to audit and collect handles for each.

Step 2 — Scrape Engagement Data via Apify

Trigger each platform's actor in parallel where possible. For each post, extract:

• Post text (title or first line as identifier)
• Engagement numbers: likes / upvotes / claps / comments / shares / retweets
• Date and time posted
• Post format: long-form / short take / list / question / story / thread

Minimum target: 20–30 posts per platform.

Scraping targets per platform:

X/Twitter (apidojo/tweet-scraper):

• Input: user profile URL https://x.com/{username}
• Sort by: most liked / most retweeted
• Extract: text, likes, retweets, replies, timestamp

Reddit (trudax/reddit-scraper):

• Input: https://www.reddit.com/user/{username}/submitted/?sort=top
• Extract: title, body, upvotes, comments, subreddit, timestamp

Instagram (apify/instagram-scraper):

• Input: username or profile URL
• Extract: caption, likes, comments, timestamp

Facebook (apify/facebook-posts-scraper):

• Input: public page or profile URL
• Extract: text, reactions, comments, shares, timestamp

LinkedIn (harvestapi/linkedin-profile-scraper):

• Input: profile URL
• Extract: posts, reactions (note: LinkedIn limits public engagement data)

Medium (web_fetch):

• URL: https://medium.com/@{username}
• Extract: article titles, clap counts, response counts

Substack (web_fetch):

• URL: author archive URL
• Extract: post titles, like counts, comment counts

If any actor fails or returns empty, skip and move to manual input for that platform.

Step 3 — Manual Input for Failed / Closed Platforms

For any platform where scraping failed:

"For [platform], could you share your top 5–10 posts with the most engagement? Paste the post text and give me rough numbers — even ballpark figures work."

Step 4 — Rank and Cluster Posts

Sort all posts by engagement. Identify the Top 10 Posts overall, noting:

• Platform, topic, format, engagement numbers, date + day + time

Then cluster into Topic Buckets:

• Group posts by theme (e.g., "career advice", "industry hot takes", "personal stories")
• For each cluster: post count, average engagement, highest single post engagement

Step 5 — Timing Analysis

From posts with timestamps:

• Best days of week (rank Mon–Sun by average engagement)
• Best time of day (morning / midday / evening / night)
• Posting frequency patterns (consistent weeks vs sporadic)

Step 6 — Generate the Audit Report

## [Name]'s Content Audit Report
Platforms audited: [list]
Total posts analyzed: [n]

### 🏆 Top 10 Posts
1. [Platform] — "[Post snippet]" — [engagement] — [date]
...

### 📦 Topic Clusters (ranked by avg engagement)
1. [Cluster name] — [n posts] — avg [x] engagements
...

### 📅 Best Times to Post (from your data)
- Best days: [e.g., Tuesday, Thursday]
- Best times: [e.g., 8–10am, 6–8pm]

### 💡 Key Patterns
- [Insight 1]
- [Insight 2]

### ⚠️ What's Not Working
- [Underperforming topic or format]

Step 7 — Save and Hand Off

Save via mimiq-memory:

python3 ~/.claude/skills/mimiq-memory/scripts/save_audit.py \
  --platform "[platform]" \
  --data '<audit JSON>' \
  --best-times "[summary]" \
  --topic-clusters "[summary]"

Then ask:

"Does this match your experience? Anything missing?"