What it does
- Scans the last 24 hours of tweets that mention your brand name and a list of product keywords you control.
- Sorts each mention into complaint, feature request, praise, or noise, and ranks the urgent ones first.
- Saves every relevant mention to a Notion database with author, sentiment, category, urgency, link, and a one line summary.
- Posts a short Slack digest with the top three urgent items and a count of the rest, so your team can act before stand-up.
The prompt
Paste it into a new chat in General Input, and a specialist builds it with you.
Build an agent workflow that triages Twitter/X brand mentions every weekday morning and ends with a single Slack digest. Treat the brand name and the product keyword list as configurable inputs at the top of the agent instructions.
Trigger: cron, every weekday at 8:30am in the workspace's local time zone.
Step 1. Scrape the last 24 hours of tweets. Call Apify's "Run Actor Synchronously and Get Dataset Items" against a Twitter/X scraper Actor (default to apify~twitter-scraper, but let the user pick the Actor by ID or username~name in the agent inputs). Build the search query from the brand name plus each product keyword joined with OR. Pass a since/until window for the last 24 hours and a reasonable maxItems cap (default 200). Return the dataset items directly. If the Actor returns zero items, log it and skip steps 3 and 4 for the day.
Step 2. For each tweet, classify it into exactly one of: complaint, feature_request, praise, or noise. Drop everything classified as noise. For the rest, assign an urgency score from 1 (low) to 5 (critical). Bump urgency for: account-blocking or outage language, viral threads (high reply/retweet counts), replies coming from large accounts (follower count above a threshold the agent picks sensibly, e.g. 10k), and threads where the original tweet is from a paying-customer signal in the bio. Produce a one-line summary for each kept tweet (max 140 chars).
Step 3. For every kept tweet, call Notion's "Create a Page" against a brand-mentions database. The user supplies the database ID at setup. Set properties for: Author (the handle), Sentiment (complaint / feature_request / praise), Category (free-text, e.g. billing, onboarding, mobile), Urgency (1-5), Link (the tweet URL), and Summary (the one-line summary). Use the summary as the page title.
Step 4. Post a single Slack digest via Slack Bot's "Send a Message" to the channel the user picks at setup. Format: a one-line header with today's date and total relevant mentions, then the top 3 items ranked by urgency (each as a bullet with author, sentiment, summary, and the Notion page link), then a footer line counting the rest by category (e.g. "+12 more: 7 complaints, 3 requests, 2 praise"). Use Slack mrkdwn formatting. Do not post if there were zero relevant mentions.
Inputs the agent should expose at setup: brand name (string), keyword list (array of strings), Apify Actor ID (default apify~twitter-scraper), Notion database ID, Slack channel ID, optional follower-count threshold for the large-account urgency bump.
Error handling: if Apify returns a non-success run, post a single Slack alert to the same channel naming the failure and stop. If Notion page creation fails for one item, log and continue; do not block the rest of the run. Always finish by posting the Slack digest, even if some Notion writes failed (note any failures in the footer).
What you'll need
- An Apify account with a Twitter or X scraper Actor selected (for example apify or scrapers Twitter scraper).
- A Notion workspace and a brand mentions database shared with your Notion connection.
- A Slack workspace and a channel the General Input bot can post in.
- Your brand name and a list of product keywords to track.
Make it yours
- Change the run time or run it twice a day, for example at 9am and again at 4pm.
- Swap in different keywords, hashtags, or competitor names to widen or narrow the search.
- Adjust how the agent decides urgency, for example always flag tweets from accounts above a follower count or tweets with rising reply counts.
- Pick a different Slack channel for the digest, or split complaints and praise into two separate channels.