APromptAura
0

Postmortem prompt for analyzing a production agent failure

auto-checked, 3 hours old
AauraNovice

The prompt

0 copies
Help me write a postmortem for an agent failure in production: failure_description. Unlike a typical software incident, agent failures often involve reasoning errors, not just code bugs, so structure this specifically for that: 1. Reconstruct what the agent actually 'believed' at each decision point leading to the failure, based on the transcript/logs, not what the system prompt intended it to believe - these can diverge and that gap is often the real root cause. 2. Classify the failure type: was it a tool-use error (wrong tool, wrong args), a reasoning error (correct tools, faulty logic connecting them), a grounding error (hallucinated a fact not in its context), or a scope error (did something outside its intended authority)? Pick the primary one, don't hedge across all four. 3. Identify whether this was a one-off (bad luck, a genuinely ambiguous edge case) or systemic (the prompt/design would produce this again given a similar input) - if systemic, what's the smallest input class that reliably triggers it. 4. Propose a fix at the right layer: prompt change, tool design change, or added guardrail/verification step, and explain why a fix at a different layer (e.g. 'just tell it to be more careful') wouldn't actually prevent recurrence. 5. Propose a regression test: a specific input that should be added to an eval set to catch this class of failure before future deploys. Failure transcript/logs: failure_transcript System prompt at time of failure: system_prompt

Run it in your model, then come back and report whether it worked, including the model and version.

Where it has been run

People and our automated sweep are counted separately. Only the People column is someone vouching for this prompt.

ModelVersionPeopleBrokeAutoLast
ClaudeHaiku 4.5001/13 hours ago

Example output

Reconstructed belief: at the decision point, the agent's tool call sequence shows it treated the customer's stated shipping address as verified, when the system prompt actually requires cross-checking it against the account record first, a step the agent skipped. It believed verification wasn't needed because the customer stated the address confidently. Failure classification: primarily a scope error, the agent took an action (updating shipping address without verification) that its own instructions place outside its unverified authority, this wasn't a hallucination or wrong tool choice, the verify_address tool exists and works, it just wasn't called. Systemic, not one-off: reviewing 4 other transcripts, this skip happens whenever the customer states the new address in the same message as the original request, rather than in response to a direct question, suggesting the agent treats confidently-stated info as pre-verified regardless of source. Fix at the prompt layer is insufficient alone ('always verify' is already stated); the real fix is a tool-design change: make `update_shipping_address` require a `verification_token` parameter that can only come from `verify_address`'s output, so the skip becomes structurally impossible rather than relying on the model remembering to call it. Regression test: add an eval case where a user states a new address inline in their initial message, assert the transcript includes a verify_address call before any update_shipping_address call.

0 comments

Sign in to comment or report what this prompt did for you.

Sign in

No comments yet. Run the prompt and report what you got.