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Product & Customer Insights
Churn-Intent Saver
Catch 'I'm cancelling / switching' posts and prioritize the loudest accounts for a save.
Run this skill with your agent
1. Connect the MCP server
https://apidirect.io/mcp?token=YOUR_API_KEY
2. Then just say to your agent
Who's threatening to cancel or switch away from {brand} right now, and which ones have the biggest audiences?
In clients that support MCP prompts (Claude Desktop, Claude Code, Cursor) this skill appears as a prompt named
churn-intent-saver.
Any agent can also call get_skill(skill_id="churn-intent-saver") to pull these steps on demand.
What it does
Monitors X for explicit churn intent about your brand, sizes each author's reach, and pulls context so you can intervene before they're gone — biggest megaphones first.
Who it's for: Support, success and social teams doing proactive saves.
Inputs
| Input | Required | Description | Example |
|---|---|---|---|
brand |
Yes | Your brand/product to monitor. | API Direct |
How your agent runs it
-
1
search_twitter(query="(cancelling OR \"switching from\" OR \"done with\") {brand}", get_sentiment=true, sort_by=most_recent)Surface explicit churn-intent posts; keep negative polarity.
-
2
twitter_user_profile(username=<author>)Pull followers_count and verification to size each account's blast radius.
-
3
twitter_user_tweets(username=<author>, get_sentiment=true)Read recent tweets for context on why they're leaving.
Delivers: A prioritized save queue — handle, reach, reason, and a suggested response — highest-reach churners first.
Tools used
The full playbook
This is exactly what the MCP returns to your agent (via the churn-intent-saver prompt or get_skill tool), with your inputs filled in.
SKILL: Churn-Intent Saver
Monitors X for explicit churn intent about your brand, sizes each author's reach, and pulls context so you can intervene before they're gone — biggest megaphones first.
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="(cancelling OR \"switching from\" OR \"done with\") <brand>", get_sentiment=true, sort_by=most_recent)
Surface explicit churn-intent posts; keep negative polarity.
2. Tool `twitter_user_profile` — twitter_user_profile(username=<author>)
Pull followers_count and verification to size each account's blast radius.
3. Tool `twitter_user_tweets` — twitter_user_tweets(username=<author>, get_sentiment=true)
Read recent tweets for context on why they're leaving.
DELIVER: A prioritized save queue — handle, reach, reason, and a suggested response — highest-reach churners first.
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.