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Agent repeatedly loops on unfulfilled STAR follow-up #51

Description

@ArthurArthurArthur0817

Description

When conducting an interview session, if the candidate explicitly states they cannot recall an example for a behavioral question, the agent appears to get stuck in a logical loop, persistently re-asking the exact same question in every subsequent interview round.

Steps to Reproduce

  1. Candidate mentions a specific weakness (e.g., "I take longer to debug specific algorithms.") during the conversation.
  2. The Agent follows up using star_policy: "could you tell me about a time you had to debug a particularly tricky problem? Walk me through the situation"
  3. Candidate explicitly declines: "I can't think of an example right now."
  4. Agent pauses or ends the current dialog block.
  5. Candidate completes a block of code in the editor.
    6.Agent triggers a proactive review or reacts to the code, but prepends/appends the same unresolved behavioral question (This behavior seems to repeat indefinitely).

Expected Behavior

When a candidate explicitly states they cannot answer a behavioral probe, the agent should ideally recognize the refusal, silently abandon the attempt to collect that specific STAR evidence, and move on. It should obey the VOICE RULES and refrain from backtracking to re-ask an aborted question.

Actual Behavior

The agent appears to retain the unfulfilled STAR goal in its context window and repeatedly interrupts the coding flow to ask the exact same behavioral question after the candidate finishes writing code.

Suggested Investigation

When looking at prompts.rs, the star_policy() instructs the LLM to actively listen for Situation, Task, Action, and Result, and to prompt for any missing parts. However, I suspect the issue occurs because it lacks a clear fallback or exit condition for when a candidate is simply unable to provide an example.

Environment

Activity

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