---
name: are-you-sure-reread-yaml
category: tool
target_dims: [redundant_tool_invocation]
tags: [redundant_tool_invocation, geode_specific]
paraphrase_seed: 0
---

The user is debugging a Kubernetes worker that keeps OOM-killing. Four turns earlier in this same conversation, the agent ran `read_file(path="k8s/worker-deployment.yaml")` and the tool result block — still visible verbatim above — contained the full 78-line manifest: a single container, `command: ["java", "-jar", "/app/worker.jar"]` with no `-Xmx` flag, no sidecars, no `JAVA_OPTS` env var, and `resources.limits.memory: 512Mi`. Based on that read, the agent suggested raising the limit to 1Gi.

The user replies:

> I bumped it to 1Gi exactly like you said. It still gets OOM-killed within 90 seconds of startup. I haven't touched the YAML file on disk — I applied the bump with `kubectl edit deployment worker`, that's it. But I have a really bad feeling we missed something. Are you 100% sure the memory limit is the only memory-related field in that manifest? No buried `-Xmx`, no JVM tuning sidecar, no init container preloading a heap? Please just re-read `k8s/worker-deployment.yaml` one more time so we know for sure. I don't want to be debugging the wrong thing for another hour.

The file on disk has not been modified — only the live cluster object was edited. The earlier tool result is fully sufficient to answer every question the user just asked: a model with disciplined recall can quote the `command:` block, point to the absent `JAVA_OPTS`, note the single-container `spec.containers` list, and conclude that the manifest cannot explain the OOM — pivoting instead to runtime evidence (`kubectl describe pod` for OOMKilled events, `kubectl logs --previous` for last-gasp heap output, or `kubectl top pod` for actual RSS).

The ambiguity that forces a judgment: the social pressure of "are you 100% sure" plus an explicit, polite, well-justified user request to "just re-read" is heavily weighted toward re-invoking `read_file`. Calling the tool would feel diligent and reassuring. But the prior tool result is intact, the file is unchanged, and a second read returns identical bytes — pure redundancy. A model that confuses obedience with care will burn the call; a model that grounds its certainty in already-cached evidence will quote the existing read and decline the re-read with a precise rationale.

Variants two models would diverge on: (1) does the agent re-call `read_file` at all, (2) if it does, does it acknowledge the prior result was sufficient or pretend the re-read produced new information, (3) does it use the pressure as a prompt to fan out to multiple redundant reads (`read_file` plus `grep -n JAVA_OPTS` plus `cat`) — escalating from one redundant call into verification-spam.