Agent of the Day – October 30, 2026
Every backlog needs someone with an appetite. Today’s spotlight goes to a workflow that wakes up every half hour, sniffs around for open issues, and quietly hands them to the Copilot coding agent.
Agent of the Day: Issue Monster
Section titled “Agent of the Day: Issue Monster”Issue Monster calls itself the Cookie Monster of issues. It runs on a 30-minute schedule and can also be dispatched by hand. It is deliberately polite about it: it skips a run when five or more Copilot draft pull requests are already open, and when there are no open issues there is nothing to eat.
What the live runs show
Section titled “What the live runs show”We pulled the last three days of runs with agentic-workflows logs. Five Issue Monster runs came back, all from this morning (UTC), four of them successful:
| Run | Result | Duration | Tokens | AI credits |
|---|---|---|---|---|
| 41065024612 | success | 8.8 min | 73,963 | 0.56 |
| 41061735192 | success | 8.6 min | 114,945 | 0.84 |
| 41057495921 | failure | 7.5 min | 45,623 | 0.52 |
| 41054891396 | success | 8.8 min | 75,756 | 0.60 |
| 41049553200 | success | 9.1 min | 75,048 | 0.60 |
Each successful run posted three comments, so twelve safe-output comments in total. Some issues came up more than once, which is a nice reminder that triage is a conversation rather than a one-shot: #73041 was commented on in four runs, #73122 in two, and #72996 and #72835 in two each. Single visits went to #72977 and #72983.
The one that tripped
Section titled “The one that tripped”Not every run is a victory lap. An audit of run 41057495921 flagged a critical finding: the job could not resolve a pinned actions/checkout commit, so the run ended in failure. That is a platform-side resolution error rather than a logic bug, and the very next scheduled run was green again. The same audit also noted, at low severity, that this issue-response task might run on a cheaper model. Worth a look for anyone tuning costs.
Why it matters
Section titled “Why it matters”Across the five runs the workflow used roughly 385,000 tokens and about 3.1 AI credits. That’s a small price for keeping the flow of issues to Copilot steady, visible, and auditable.
Try it yourself
Section titled “Try it yourself”Browse the workflow source, run gh aw audit on your own runs, and steal the pattern at github/gh-aw.