Every 15 minutes
Get Slack alerts when your brand is mentioned
Posts naming your brand or a competitor reach Slack within 15 minutes.
- Runs
- Every 15 minutes
- Apps
- X
- AI
- Not needed
- Access
- tweet.read users.read
Send this to your assistant
Create a ClickRuntime automation: every 15 minutes, search X for 'Brightloom' or 'brightloom.io' and post new matches to #brand in Slack.
First time? Adding ClickRuntime to your assistant takes about two minutes.
Why use it
Why teams use this automation
Brand mentions on X move quickly. A customer complains that a delivery went missing, a competitor announces a price cut that mentions you by name, or a journalist writes about your product. If you find out the next morning, the complaint has dozens of likes, the competitor has captured the conversation and the chance for a timely reply has passed.
Every 15 minutes, X's recent search is queried for your brand and competitor keywords, using the last seen post ID so only newer posts are returned. Each match is posted to Slack, and the highest ID is stored for the next pass.
Support, PR and competitive teams in smaller companies use it as a lightweight social listening tool without buying a dedicated platform. Your team sees the post in Slack within a quarter of an hour, with no one watching X.
What you get out of it
Complaints are answered while they matter
A reply to a public complaint within the hour often defuses it, while a reply the next day arrives after the pile-on has already formed. A quick, calm reply can stop a single bad experience from becoming a thread about your brand.
Competitor moves are noticed
Seeing posts that mention a rival by name tells you when they launch, change prices or run into problems, which helps you respond with timing. Knowing when a rival moves lets you answer with an offer or a message while it still matters.
Positive mentions are not wasted
Finding a customer praising you gives you a chance to thank them, share the post and ask permission to use it as a testimonial. A grateful reply to a happy customer costs nothing and builds goodwill in public.
No expensive listening tool
For a company with a few keywords, a polled search into Slack covers the essentials without a platform subscription priced for large enterprises. Small teams get the useful core of social listening without the enterprise price tag.
Only new posts are delivered
The stored last ID means you see each mention once, so the channel does not repeat old posts at every run and stays easy to scan. That keeps the channel readable, so people continue to pay attention to it.
How it works
What happens, step by step
Every 15 minutes, ClickRuntime searches X for new posts that mention your brand or keywords.
It only picks up posts newer than the last one it saw, so you never get the same post twice.
Each match is posted to your Slack channel with the author's handle, what they wrote and a link.
Before it runs live
- Connect X
What you get
Build your own
Need it to work differently?
Your own rules
Conditions, thresholds, filters and exceptions, written the way you'd explain them to a colleague.
Any number of apps
One automation can read from one app and update several others. Over 248 apps are ready, and anything with an API works too.
AI where it helps
Summaries, classification, extraction and drafts use ClickRuntime's built-in AI, with no extra key.
On a schedule or on each event
Runs as often as every 5 minutes, or the moment an app sends an event, and keeps track of what it already handled.
Changes you can ask for
- Act only on the items that match your own rules, and skip the rest
- Add an AI step, for example to summarize, sort or draft a reply
- Add another app, for example also send it to Slack
- Combine it with other X steps into one automation
Under the hood
The code that runs this automation
from clickruntime import on_trigger, report_fetched, state, notify, http, credentials
QUERY = '(Brightloom OR "brightloom.io") -is:retweet'
@on_trigger
def run(event):
auth = {"Authorization": "Bearer " + credentials.connection("x", "main")}
params = {"query": QUERY, "max_results": 100, "expansions": "author_id", "user.fields": "username"}
if state.get("since_id"):
params["since_id"] = state.get("since_id")
data = http.get("https://api.x.com/2/tweets/search/recent", headers=auth, params=params).json()
tweets = data.get("data", [])
report_fetched(len(tweets))
if not tweets:
return {"summary": "No new matches"}
users = {u["id"]: u["username"] for u in data.get("includes", {}).get("users", [])}
for t in reversed(tweets):
notify.slack(f"@{users.get(t['author_id'], '?')}: {t['text']}\nhttps://x.com/i/web/status/{t['id']}", channel="#brand")
state.set("since_id", data["meta"]["newest_id"])
return {"posted": len(tweets)}FAQ
Common questions
Does it find posts that do not tag my handle?
How far back does recent search go?
Can I reduce noise from retweets and unrelated matches?
What permissions does it need?
Does it need AI?
How many runs does it use?
Can I change how it works?
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