Review Weakness Miner
Surface a rival's recurring failures from their angriest reviews across Google and Facebook
https://apidirect.io/mcp?token=YOUR_API_KEY
Find {competitor}'s biggest recurring complaints in {city} from their worst reviews
review-weakness-miner.
Any agent can also call get_skill(skill_id="review-weakness-miner") to pull these steps on demand.
What it does
A competitor's worst reviews are a free, honest product-gap audit. Sorting to the lowest-ranked reviews and corroborating across two sources isolates the failures that repeat, not the one-off rants.
Who it's for: Product teams, local marketers, and competitive positioning leads
Inputs
| Input | Required | Description | Example |
|---|---|---|---|
competitor |
Yes | The rival business name to locate on Google Maps and Facebook | Equinox |
city |
Yes | The city or market to scope the place search to | Austin |
How your agent runs it
-
1
search_places(query="{competitor} {city}")Grab the place_id of the rival's location(s) with the most reviews.
-
2
place_reviews(place_id=<place_id>, sort_by=lowest_ranking, get_sentiment=true)Keep 1-2 star reviews and cluster recurring failure themes (wait times, billing, staff).
-
3
search_facebook_pages(query={competitor})Find the rival's official Facebook page url for a second review source.
-
4
facebook_page_details(url=<page_url>)Resolve the page_id required for the reviews endpoint.
-
5
facebook_page_reviews(page_id=<page_id>, get_sentiment=true)Keep recommend=false reviews and confirm which weaknesses repeat across both platforms.
Tools used
The full playbook
This is exactly what the MCP returns to your agent (via the review-weakness-miner prompt or get_skill tool), with your inputs filled in.
SKILL: Review Weakness Miner
A competitor's worst reviews are a free, honest product-gap audit. Sorting to the lowest-ranked reviews and corroborating across two sources isolates the failures that repeat, not the one-off rants.
You are running this skill on API Direct via its MCP tools. Execute the steps below yourself by calling the named tools in order — values in <angle brackets> come from a previous step. Then deliver the result described at the end.
INPUTS:
- competitor (required): <competitor — ASK THE USER>
- city (required): <city — ASK THE USER>
STEPS:
1. Tool `search_places` — search_places(query="<competitor> <city>")
Grab the place_id of the rival's location(s) with the most reviews.
2. Tool `place_reviews` — place_reviews(place_id=<place_id>, sort_by=lowest_ranking, get_sentiment=true)
Keep 1-2 star reviews and cluster recurring failure themes (wait times, billing, staff).
3. Tool `search_facebook_pages` — search_facebook_pages(query=<competitor>)
Find the rival's official Facebook page url for a second review source.
4. Tool `facebook_page_details` — facebook_page_details(url=<page_url>)
Resolve the page_id required for the reviews endpoint.
5. Tool `facebook_page_reviews` — facebook_page_reviews(page_id=<page_id>, get_sentiment=true)
Keep recommend=false reviews and confirm which weaknesses repeat across both platforms.
DELIVER: A ranked weakness map of the rival's top recurring complaints, evidenced by quoted 1-star reviews from Google and Facebook
Note: each underlying tool call is billed at its normal endpoint price; get_sentiment adds a small per-page surcharge. Page through results as needed but stop once you have enough to deliver the outcome.