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Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.
Based on SOC occupation classification
| name | apify-content-analytics |
| description | Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok. |
| risk | unknown |
| source | community |
Track and analyze content performance using Apify Actors to extract engagement metrics from multiple platforms.
(No need to check it upfront)
.env file with APIFY_TOKEN--env-file support)mcpc CLI tool: npm install -g @apify/mcpcCopy this checklist and track progress:
Task Progress:
- [ ] Step 1: Identify content analytics type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analytics script
- [ ] Step 5: Summarize findings
Select the appropriate Actor based on analytics needs:
| User Need | Actor ID | Best For |
|---|---|---|
| Post engagement metrics | apify/instagram-post-scraper | Post performance |
| Reel performance | apify/instagram-reel-scraper | Reel analytics |
| Follower growth tracking | apify/instagram-followers-count-scraper | Growth metrics |
| Comment engagement | apify/instagram-comment-scraper | Comment analysis |
| Hashtag performance | apify/instagram-hashtag-scraper | Branded hashtags |
| Mention tracking | apify/instagram-tagged-scraper | Tag tracking |
| Comprehensive metrics | apify/instagram-scraper | Full data |
| API-based analytics | apify/instagram-api-scraper | API access |
| Facebook post performance | apify/facebook-posts-scraper | Post metrics |
| Reaction analysis | apify/facebook-likes-scraper | Engagement types |
| Facebook Reels metrics | apify/facebook-reels-scraper | Reels performance |
| Ad performance tracking | apify/facebook-ads-scraper | Ad analytics |
| Facebook comment analysis | apify/facebook-comments-scraper | Comment engagement |
| Page performance audit | apify/facebook-pages-scraper | Page metrics |
| YouTube video metrics | streamers/youtube-scraper | Video performance |
| YouTube Shorts analytics | streamers/youtube-shorts-scraper | Shorts performance |
| TikTok content metrics | clockworks/tiktok-scraper | TikTok analytics |
Fetch the Actor's input schema and details dynamically using mcpc:
export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content"
Replace ACTOR_ID with the selected Actor (e.g., apify/instagram-post-scraper).
This returns:
Before running, ask:
Quick answer (display in chat, no file):
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT'
CSV:
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT' \
--output YYYY-MM-DD_OUTPUT_FILE.csv \
--format csv
JSON:
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT' \
--output YYYY-MM-DD_OUTPUT_FILE.json \
--format json
After completion, report:
APIFY_TOKEN not found - Ask user to create .env with APIFY_TOKEN=your_token
mcpc not found - Ask user to install npm install -g @apify/mcpc
Actor not found - Check Actor ID spelling
Run FAILED - Ask user to check Apify console link in error output
Timeout - Reduce input size or increase --timeout
Optimize pull requests for quick approval and merging by ensuring clean diffs, comprehensive self-reviews, and structured documentation.
Frontend design entry point: direction, design system, visual philosophy. Use whenever building or touching the look of any web UI (components, pages, dashboards, React/Vue/HTML-CSS) or when the user says "make this look better", "fix the spacing/layout", or mentions styling, color, type, or polish.
Render the UI and prove it's balanced + usable: a deterministic layout audit (centroid / optical-center / pixel-oracle balance via explicit math + annotated screenshot) plus a vision-judged Nielsen usability audit by a separate fresh-eyes judge. The measurement layer taste-only design skills lack.
Automated visual tuning: a vision or video model rates rendered variants in a loop. Render several labeled variants into one artifact, ask the model to rate them and suggest better values, render the suggestions, ask it to pick the best, repeat until good — the model is the eye, you run the loop.
Human-in-the-loop web studio to tune AI-generated output by eye. Stand up a local interactive studio (sliders, pickers, drag handles) or an inline edit/highlight/comment annotation studio for prose & media, instead of guessing values or shipping a static comparison grid.
macOS screen recorder that captures the main display PLUS system audio via ScreenCaptureKit — no BlackHole/loopback driver, no sudo, just the standard Screen Recording permission. CLI-driven; fills the headless-screen-recording-with-system-sound gap QuickTime and `screencapture -v` can't.