Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tmolavi/mcp-agent-skills-hub/apify-content-analytics)<a href="https://agentmods.dev/skills/tmolavi/mcp-agent-skills-hub/apify-content-analytics"><img src="https://agentmods.dev/badge/skills/tmolavi/mcp-agent-skills-hub/apify-content-analytics/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tmolavi/mcp-agent-skills-hub/apify-content-analytics"><img src="https://agentmods.dev/badge/skills/tmolavi/mcp-agent-skills-hub/apify-content-analytics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00030 | $0.01221 |
| Opus 5 | $0.00015 | $0.00611 |
| Sonnet 5 | $0.00006 | $0.00244 |
| Haiku 4.5 | $0.00003 | $0.00122 |
Grade A, and why
apify-content-analytics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
97% identical to apify-content-analytics — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Analytics
Track and analyze content performance using Apify Actors to extract engagement metrics from multiple platforms.
When to Use
- You need engagement, growth, or ROI metrics for posts, reels, videos, ads, or hashtags.
- The task is to use Apify Actors to collect cross-platform content performance data.
- You need exported analytics results and a concise interpretation of what content is performing best.
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 |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 132 lines · 30 tokens per session scan A 587582a8e19a
apify-content-analytics is a skill published in the GitHub repository tmolavi/mcp-agent-skills-hub (8 stars, last pushed 16d ago), licensed MIT. It adds 30 tokens to every session and 1,221 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to apify-content-analytics, differing in 3 lines, and is treated as a copy.
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