On a schedule
Track created vs resolved issues each week
Each Monday you see how many issues were created and resolved last week, and how that compares with the week before.
- Runs
- On a schedule
- Apps
- Jira
- AI
- Not needed
- Access
- read
Send this to your assistant
Create a ClickRuntime automation: every Monday at 9am, email me how many issues were created and resolved last week in project ABC, and the change from the week before.
First time? Adding ClickRuntime to your assistant takes about two minutes.
Why use it
Why teams use this automation
A team lead feels that the backlog keeps growing but cannot show it. Issues are being fixed every day, yet new ones arrive just as fast, and without numbers it is only a feeling. When she asks for more headcount or a bug-fix sprint, the response is that people seem to be keeping up. Jira's own created-versus-resolved chart exists, but nobody opens it, and it cannot be dropped into a weekly update.
Each Monday, ClickRuntime runs JQL counts for issues created and issues resolved during the previous week, compares both figures with the ones stored the week before, and emails you the totals and the change. The backlog's direction is stated in numbers you can put in a status note.
Team leads, QA managers and support managers who want to know whether they are gaining or falling behind will find it useful.
What you get out of it
The backlog trend is stated plainly
Created minus resolved tells you whether the pile grew or shrank. A clear number each week ends arguments about whether the team is keeping up. The conversation moves on to what to do about the trend, not whether it exists.
Requests for help are backed by data
Asking for more people or a stabilization sprint is persuasive when you can show eight weeks of more bugs created than resolved. Managers fund problems they can see. Leaders approve extra capacity much more readily when the case rests on weeks of recorded numbers.
Good weeks are noticed too
When resolved exceeds created for several weeks, the team is reducing its debt. Sharing that with them is encouraging, and shows that fixing quality work is paying off. That recognition matters for a team that mostly hears about problems, not about progress.
Quality changes after a release show up
A jump in created issues the week after a release says something about quality. You find out quickly and can connect the change to a specific release instead of guessing.
Week-on-week comparison is automatic
The automation remembers last week's totals, so each email shows the change without anyone keeping a spreadsheet. The history builds up on its own and stays consistent. The weekly rhythm also turns a one-off analysis into a habit that costs nobody any time.
How it works
What happens, step by step
Every Monday at 9 am, the automation counts how many Jira issues were created and resolved last week.
It compares both numbers with the week before, which it saved last time.
You get an email with the counts, the change from the week before and the net difference.
Before it runs live
- Connect Jira
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 Jira steps into one automation
Under the hood
The code that runs this automation
from clickruntime import on_trigger, credentials, http, state, notify
JIRA = "https://api.atlassian.com/ex/jira/your-cloud-id"
def jira(method, path, **kw):
resp = http.request(method, JIRA + path, headers={
"Authorization": f"Bearer {credentials.connection('jira', 'work')}", "Accept": "application/json"}, **kw)
resp.raise_for_status()
return resp.json() if resp.content else None
def search(jql, fields, limit=100):
return jira("POST", "/rest/api/3/search/jql", json={"jql": jql, "fields": fields, "maxResults": limit})["issues"]
def count(jql):
return jira("POST", "/rest/api/3/search/approximate-count", json={"jql": jql})["count"]
@on_trigger
def run(event):
created = count("project = ABC AND created >= startOfWeek(-1) AND created < startOfWeek()")
resolved = count("project = ABC AND resolved >= startOfWeek(-1) AND resolved < startOfWeek()")
prev = state.get("last_week") or {}
diff = lambda k, v: f" ({v - prev[k]:+d} vs week before)" if k in prev else ""
notify.email_me("ABC last week: created vs resolved",
f"Created: {created}{diff('created', created)}\nResolved: {resolved}{diff('resolved', resolved)}\n"
f"Net: {created - resolved:+d}")
state.set("last_week", {"created": created, "resolved": resolved})
return {"created": created, "resolved": resolved}FAQ
Common questions
How are created and resolved counted?
Can I count one project or one issue type, such as bugs?
What happens in the first week, with nothing to compare?
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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