Write an Agent Debugging Note a Teammate Can Reproduce
Shashank Agarwal
A teammate should not need the author's memory to reproduce an agent bug. The debugging note needs a controlled starting point and an observable expected result.
Quick answer: Record the task, minimal fixture, relevant versions, execution steps and expected-versus-observed mismatch. Link restricted evidence appropriately and separate facts from hypotheses. Include a verification step that can reject an ineffective fix, plus a nearby case the change must preserve.
Start with the mismatch
For an illustrative calendar assistant: “After the user changes Tuesday to Thursday, the proposed appointment still uses Tuesday.”
This sentence identifies the behavior. “The agent has poor memory” is an explanation that remains to be tested.
Make the note executable
| Item | Example content |
|---|---|
| Starting fixture | Synthetic calendar with known availability |
| Input sequence | Initial request, correction and confirmation |
| Configuration | Agent and tool revisions |
| Observed result | Proposed date remained the earlier value |
| Expected result | Proposal reflects the explicit correction |
| Evidence | Relevant messages and submitted tool fields |
The note is a proposed template, not a report of a production incident.
Explain what is controlled
Identify whether time, external availability or provider responses are fixed. If they remain live, record the limitation and avoid promising identical outcomes.
Include the failure result from each relevant attempt. A successful rerun does not erase an earlier failure; variation may be part of the bug.
Give the fix a meaningful check
After a candidate change, rerun the corrected-date case and an unchanged-date case. Add an ambiguous correction if that is a supported workflow.
The acceptance check should inspect the actual proposed or applied operation, not only a friendly final message. If operation evidence is unavailable, report that limit.
An effective note leaves the next engineer with a bounded investigation, a testable hypothesis and a way to decide whether the candidate helped.
I'm Shashank Agarwal, founder and CEO of Noveum AI and creator of API.market. These examples describe proposed engineering methods, not customer incidents or measured performance.
Use the tool-boundary guide to define operation evidence and the regression-test guide to preserve a controlled reproduction.
Follow my work on LinkedIn. Drafted with AI assistance.
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