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-brand-reputation-monitoring)<a href="https://agentmods.dev/skills/tmolavi/mcp-agent-skills-hub/apify-brand-reputation-monitoring"><img src="https://agentmods.dev/badge/skills/tmolavi/mcp-agent-skills-hub/apify-brand-reputation-monitoring/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-brand-reputation-monitoring"><img src="https://agentmods.dev/badge/skills/tmolavi/mcp-agent-skills-hub/apify-brand-reputation-monitoring.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 | $0.00025 | $0.01239 |
| Opus 5 | $0.00013 | $0.00620 |
| Sonnet 5 | $0.00005 | $0.00248 |
| Haiku 4.5 | $0.00003 | $0.00124 |
Grade A, and why
apify-brand-reputation-monitoring 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
95% identical to apify-brand-reputation-monitoring — 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brand Reputation Monitoring
Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.
When to Use
- You need to monitor reviews, ratings, or brand mentions across social, travel, or map platforms.
- The task is to select and run an Apify Actor for brand sentiment or reputation tracking.
- You need exported monitoring results and a summary of reputation signals.
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: Determine data source (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the monitoring script
- [ ] Step 5: Summarize results
Step 1: Determine Data Source
Select the appropriate Actor based on user needs:
| User Need | Actor ID | Best For |
|---|---|---|
| Google Maps reviews | compass/crawler-google-places |
Business reviews, ratings |
| Google Maps review export | compass/Google-Maps-Reviews-Scraper |
Dedicated review scraping |
| Booking.com hotels | voyager/booking-scraper |
Hotel data, scores |
| Booking.com reviews | voyager/booking-reviews-scraper |
Detailed hotel reviews |
| TripAdvisor reviews | maxcopell/tripadvisor-reviews |
Attraction/restaurant reviews |
| Facebook reviews | apify/facebook-reviews-scraper |
Page reviews |
| Facebook comments | apify/facebook-comments-scraper |
Post comment monitoring |
| Facebook page metrics | apify/facebook-pages-scraper |
Page ratings overview |
| Facebook reactions | apify/facebook-likes-scraper |
Reaction type analysis |
| Instagram comments | apify/instagram-comment-scraper |
Comment sentiment |
| Instagram hashtags | apify/instagram-hashtag-scraper |
Brand hashtag monitoring |
| Instagram search | apify/instagram-search-scraper |
Brand mention discovery |
| Instagram tagged posts | apify/instagram-tagged-scraper |
Brand tag tracking |
| Instagram export | apify/export-instagram-comments-posts |
Bulk comment export |
| Instagram comprehensive | apify/instagram-scraper |
Full Instagram monitoring |
| Instagram API | apify/instagram-api-scraper |
API-based monitoring |
| YouTube comments | streamers/youtube-comments-scraper |
Video comment sentiment |
| TikTok comments | clockworks/tiktok-comments-scraper |
TikTok sentiment |
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 · 133 lines · 25 tokens per session scan A c7b33e79dc0c
apify-brand-reputation-monitoring is a skill published in the GitHub repository tmolavi/mcp-agent-skills-hub (8 stars, last pushed 16d ago), licensed MIT. It adds 25 tokens to every session and 1,239 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to apify-brand-reputation-monitoring, differing in 3 lines, and is treated as a copy.
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