ef285b5c97
* fix: stabilize validation and tests on Windows * test: add Windows smoke coverage for skill activation * refactor: make setup_web script CommonJS * fix: repair aegisops-ai frontmatter * docs: add when-to-use guidance to core skills * docs: add when-to-use guidance to Apify skills * docs: add when-to-use guidance to Google and Expo skills * docs: add when-to-use guidance to Makepad skills * docs: add when-to-use guidance to git workflow skills * docs: add when-to-use guidance to fp-ts skills * docs: add when-to-use guidance to Three.js skills * docs: add when-to-use guidance to n8n skills * docs: add when-to-use guidance to health analysis skills * docs: add when-to-use guidance to writing and review skills * meta: sync generated catalog metadata * docs: add when-to-use guidance to Robius skills * docs: add when-to-use guidance to review and workflow skills * docs: add when-to-use guidance to science and data skills * docs: add when-to-use guidance to tooling and automation skills * docs: add when-to-use guidance to remaining skills * fix: gate bundle helper execution in Windows activation * chore: drop generated artifacts from contributor PR * docs(maintenance): Record PR 457 sweep Document the open issue triage, PR supersedence decision, local verification, and source-only cleanup that prepared PR #457 for re-running CI. --------- Co-authored-by: sickn33 <sickn33@users.noreply.github.com>
128 lines
4.5 KiB
Markdown
128 lines
4.5 KiB
Markdown
---
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name: apify-content-analytics
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description: Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.
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risk: unknown
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source: community
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---
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# Content Analytics
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Track and analyze content performance using Apify Actors to extract engagement metrics from multiple platforms.
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## When to Use
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- You need engagement, growth, or ROI metrics for posts, reels, videos, ads, or hashtags.
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- The task is to use Apify Actors to collect cross-platform content performance data.
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- You need exported analytics results and a concise interpretation of what content is performing best.
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## Prerequisites
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(No need to check it upfront)
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- `.env` file with `APIFY_TOKEN`
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- Node.js 20.6+ (for native `--env-file` support)
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- `mcpc` CLI tool: `npm install -g @apify/mcpc`
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## Workflow
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Copy this checklist and track progress:
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```
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Task Progress:
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- [ ] Step 1: Identify content analytics type (select Actor)
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- [ ] Step 2: Fetch Actor schema via mcpc
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- [ ] Step 3: Ask user preferences (format, filename)
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- [ ] Step 4: Run the analytics script
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- [ ] Step 5: Summarize findings
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```
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### Step 1: Identify Content Analytics Type
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Select the appropriate Actor based on analytics needs:
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| User Need | Actor ID | Best For |
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|-----------|----------|----------|
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| Post engagement metrics | `apify/instagram-post-scraper` | Post performance |
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| Reel performance | `apify/instagram-reel-scraper` | Reel analytics |
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| Follower growth tracking | `apify/instagram-followers-count-scraper` | Growth metrics |
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| Comment engagement | `apify/instagram-comment-scraper` | Comment analysis |
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| Hashtag performance | `apify/instagram-hashtag-scraper` | Branded hashtags |
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| Mention tracking | `apify/instagram-tagged-scraper` | Tag tracking |
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| Comprehensive metrics | `apify/instagram-scraper` | Full data |
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| API-based analytics | `apify/instagram-api-scraper` | API access |
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| Facebook post performance | `apify/facebook-posts-scraper` | Post metrics |
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| Reaction analysis | `apify/facebook-likes-scraper` | Engagement types |
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| Facebook Reels metrics | `apify/facebook-reels-scraper` | Reels performance |
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| Ad performance tracking | `apify/facebook-ads-scraper` | Ad analytics |
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| Facebook comment analysis | `apify/facebook-comments-scraper` | Comment engagement |
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| Page performance audit | `apify/facebook-pages-scraper` | Page metrics |
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| YouTube video metrics | `streamers/youtube-scraper` | Video performance |
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| YouTube Shorts analytics | `streamers/youtube-shorts-scraper` | Shorts performance |
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| TikTok content metrics | `clockworks/tiktok-scraper` | TikTok analytics |
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### Step 2: Fetch Actor Schema
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Fetch the Actor's input schema and details dynamically using mcpc:
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```bash
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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"
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```
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Replace `ACTOR_ID` with the selected Actor (e.g., `apify/instagram-post-scraper`).
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This returns:
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- Actor description and README
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- Required and optional input parameters
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- Output fields (if available)
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### Step 3: Ask User Preferences
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Before running, ask:
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1. **Output format**:
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- **Quick answer** - Display top few results in chat (no file saved)
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- **CSV** - Full export with all fields
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- **JSON** - Full export in JSON format
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2. **Number of results**: Based on character of use case
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### Step 4: Run the Script
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**Quick answer (display in chat, no file):**
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```bash
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node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
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--actor "ACTOR_ID" \
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--input 'JSON_INPUT'
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```
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**CSV:**
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```bash
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node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
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--actor "ACTOR_ID" \
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--input 'JSON_INPUT' \
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--output YYYY-MM-DD_OUTPUT_FILE.csv \
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--format csv
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```
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**JSON:**
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```bash
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node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
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--actor "ACTOR_ID" \
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--input 'JSON_INPUT' \
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--output YYYY-MM-DD_OUTPUT_FILE.json \
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--format json
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```
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### Step 5: Summarize Findings
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After completion, report:
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- Number of content pieces analyzed
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- File location and name
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- Key performance insights
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- Suggested next steps (deeper analysis, content optimization)
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## Error Handling
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`APIFY_TOKEN not found` - Ask user to create `.env` with `APIFY_TOKEN=your_token`
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`mcpc not found` - Ask user to install `npm install -g @apify/mcpc`
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`Actor not found` - Check Actor ID spelling
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`Run FAILED` - Ask user to check Apify console link in error output
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`Timeout` - Reduce input size or increase `--timeout`
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