Daily
List monday.com mentions you haven't answered
Each morning you see the updates that @mention you where you still haven't replied.
- Runs
- Daily
- Apps
- monday.com
- AI
- Not needed
- Access
- read
Send this to your assistant
Create a ClickRuntime automation: each morning at 8:30, email me monday.com updates from the last 3 days that @mention me and that I haven't replied to yet.
First time? Adding ClickRuntime to your assistant takes about two minutes.
Why use it
Why teams use this automation
Being @mentioned on monday.com is easy to miss. A colleague asks for a decision in an update, the notification sits among forty others, and a day later you cannot remember whether you answered. Teammates wait without saying so, a client-facing item stalls on a question, and the person who asked eventually follows up in chat, which is slower and less tidy than a reply in the thread. Over a week that adds up to a dozen small questions left hanging.
Every day ClickRuntime reads recent updates on your boards, finds the ones that mention you, checks whether you posted a reply after them, and emails you the list of conversations still waiting on you. Each line has the item name, who asked, and a link back to the update.
It works well for managers and account owners who are tagged all day.
What you get out of it
Questions to you stop going unanswered
A colleague who tagged you on Monday gets a response on Tuesday because the item is on your list. That small reliability keeps work from stalling on one person's inbox.
A short list instead of an inbox sweep
Rather than clicking through the notification bell, you read one email of open mentions. You can clear ten of them in the time it takes to find two in the activity feed.
Replies are detected automatically
Once you answer in the thread, the mention drops off the next day's email. The list never nags about conversations you already handled, so you keep trusting it. The list is rebuilt each day from the actual thread, so a reply you posted from your phone counts as well.
Clients wait less
On boards shared with customers, a mention is often a question from them. Surfacing it daily means external requests are answered within a day instead of whenever someone scrolls to it.
Fewer side conversations in chat
When people see replies appear on the board, they stop pinging in chat to ask if you saw it. The record of the decision stays in the item where the next person will look.
How it works
What happens, step by step
Every day, ClickRuntime looks through recent updates and replies on your monday.com boards.
It finds the ones where someone mentioned you and you haven't replied yet.
You get one email listing who mentioned you, on which item, what they said and a link to reply.
Before it runs live
- Connect monday.com
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
- Run it at a different time, more or less often, or only on weekdays
- 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 monday.com steps into one automation
Under the hood
The code that runs this automation
from datetime import datetime, timedelta, timezone
from clickruntime import on_trigger, notify, http, credentials
QUERY = """{ me { id } updates(limit: 200) {
id body text_body created_at creator { name } item { name url } replies { creator_id } } }"""
@on_trigger
def run(event):
data = http.post("https://api.monday.com/v2", headers={"Authorization": credentials.secret("MONDAY_API_TOKEN"), "API-Version": "2024-10"},
json={"query": QUERY}).json()["data"]
me = str(data["me"]["id"])
since = (datetime.now(timezone.utc) - timedelta(days=3)).isoformat()
owed = []
for u in data["updates"]:
mentioned = f'data-mention-id="{me}"' in u["body"]
replied = any(str(r["creator_id"]) == me for r in u["replies"])
if u["created_at"] >= since and mentioned and not replied and u.get("item"):
owed.append(f"{u['creator']['name']} on {u['item']['name']}: {u['text_body'][:200]}\n{u['item']['url']}")
if owed:
notify.email_me(f"{len(owed)} monday.com mentions waiting on you", "\n\n".join(owed))
return {"owed": len(owed)}FAQ
Common questions
Does it see mentions in replies as well as updates?
How far back does it look?
Whose mentions does it track?
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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