apify-content-analytics
Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.
How do I install this agent skill?
npx skills add https://github.com/apify/agent-skills --skill apify-content-analyticsIs this agent skill safe to install?
- Gen Agent Trust Hubwarn
The skill facilitates social media analytics via the Apify platform. It requires access to sensitive local environment files (.env) for authentication and depends on external packages and command-line tools. These behaviors are consistent with its primary purpose but represent a security surface that requires user trust in the Apify platform and the local script files referenced.
- Socketpass
No alerts
- Snykwarn
Risk: MEDIUM · No issues
- Runlayerfail
1/2 files flagged
What does this agent skill do?
Content Analytics
Track and analyze content performance using Apify Actors to extract engagement metrics from multiple platforms.
Prerequisites
(No need to check it upfront)
.envfile withAPIFY_TOKEN- Node.js 20.6+ (for native
--env-filesupport) mcpcCLI tool:npm install -g @apify/mcpc
Workflow
Copy 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
Step 1: Identify Content Analytics Type
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 |
Step 2: Fetch Actor Schema
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:
- Actor description and README
- Required and optional input parameters
- Output fields (if available)
Step 3: Ask User Preferences
Before running, ask:
- Output format:
- Quick answer - Display top few results in chat (no file saved)
- CSV - Full export with all fields
- JSON - Full export in JSON format
- Number of results: Based on character of use case
Step 4: Run the Script
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
Step 5: Summarize Findings
After completion, report:
- Number of content pieces analyzed
- File location and name
- Key performance insights
- Suggested next steps (deeper analysis, content optimization)
Error Handling
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
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/apify/agent-skills/apify-content-analytics">View apify-content-analytics on skillZs</a>