High-Reach Detractor Radar
Catch only the angry brand mentions and rank them by the size of the audience that saw them
https://apidirect.io/mcp?token=YOUR_API_KEY
Scan X for angry posts about {brand} and rank them by how many people could see them
high-reach-detractor-radar.
Any agent can also call get_skill(skill_id="high-reach-detractor-radar") to pull these steps on demand.
What it does
Most negative tweets are harmless; the dangerous ones come from big accounts. Filtering mentions to anger/disgust and then weighting by the author's follower count turns raw backlash into a prioritized blast-radius triage list.
Who it's for: PR and social crisis teams who need to triage backlash fast
Inputs
| Input | Required | Description | Example |
|---|---|---|---|
brand |
Yes | Brand, product, or handle to monitor for backlash | Ryanair |
How your agent runs it
-
1
search_twitter(query={brand}, pages=10, sort_by=most_recent, get_sentiment=true)Keep only tweets with negative polarity or dominant_emotion in anger/disgust.
-
2
twitter_user_profile(username=<angry_author>)Pull followers_count and verified status to estimate each detractor's blast radius.
-
3
twitter_tweet_details(tweet_id=<angry_tweet_id>, get_sentiment=true)Confirm the top high-reach complaints' engagement and emotional intensity.
-
4
twitter_tweet_comments(tweet_id=<angry_tweet_id>, get_sentiment=true)Check whether the reply thread is piling on or defending, then rank a triage list by followers times engagement.
Tools used
The full playbook
This is exactly what the MCP returns to your agent (via the high-reach-detractor-radar prompt or get_skill tool), with your inputs filled in.
SKILL: High-Reach Detractor Radar
Most negative tweets are harmless; the dangerous ones come from big accounts. Filtering mentions to anger/disgust and then weighting by the author's follower count turns raw backlash into a prioritized blast-radius triage list.
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:
- brand (required): <brand — ASK THE USER>
STEPS:
1. Tool `search_twitter` — search_twitter(query=<brand>, pages=10, sort_by=most_recent, get_sentiment=true)
Keep only tweets with negative polarity or dominant_emotion in anger/disgust.
2. Tool `twitter_user_profile` — twitter_user_profile(username=<angry_author>)
Pull followers_count and verified status to estimate each detractor's blast radius.
3. Tool `twitter_tweet_details` — twitter_tweet_details(tweet_id=<angry_tweet_id>, get_sentiment=true)
Confirm the top high-reach complaints' engagement and emotional intensity.
4. Tool `twitter_tweet_comments` — twitter_tweet_comments(tweet_id=<angry_tweet_id>, get_sentiment=true)
Check whether the reply thread is piling on or defending, then rank a triage list by followers times engagement.
DELIVER: A prioritized crisis-triage list of negative brand mentions ranked by audience reach and pile-on risk, with each author's follower count and verification status
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.