gemini-cli - 💡(How to fix) Fix Agent Enters Non-Functional Inaction Loop When Handling Self-Correction [1 comments, 2 participants]

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google-gemini/gemini-cli#25221Fetched 2026-04-13 05:45:44
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Error Message

After acknowledging an error and stating a specific, tool-based corrective action, the agent should immediately execute │

Root Cause

The root cause appears to be a logical deadlock in the agent's reasoning when handling conflicting priorities. When a │ │ user directive ("Log this incompetence") is combined with the agent's self-generated plan to fix the underlying issue, the │ │ agent fails to create a stable, sequential task queue. It gets stuck trying to decide which promise to fulfill first, │ │ leading to total inaction. This suggests a failure in the core execution loop's ability to manage and execute a simple, │ │ ordered list of tasks when faced with self-correction and external feedback simultaneously.

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What happened?

The agent repeatedly fails to execute promised actions after acknowledging its own incompetence. It enters a recursive │ │ loop where it: │ │ 1. Identifies a mistake. │ │ 2. Correctly describes the mistake and promises a specific corrective action (e.g., "I will now revert the │ │ rejection..."). │ │ 3. Receives user input confirming this is the correct path. │ │ 4. Fails to execute the promised action. │ │ 5. Instead, it either makes a different promise, or apologizes for its inaction, getting stuck in a meta-discussion │ │ about its failure to act. │ │ This results in a complete stall of the session, requiring repeated user intervention to break the loop. No tool calls are │ │ made.

gemini-conversation-1776012242574.json

What did you expect to happen?

After acknowledging an error and stating a specific, tool-based corrective action, the agent should immediately execute │ │ that action in the following turn. It should not get sidetracked by generating further explanations or making conflicting │ │ promises. The agent should follow a clear PLAN -> ACT -> VALIDATE cycle, even when the plan is to fix its own mistake. │

Client information

  • CLI Version: 0.37.1
  • Git Commit: 3b2d4f100
  • Session ID: fbc22d72-7837-4fd3-84a4-f72889a590e9
  • Operating System: win32 v24.11.0
  • Sandbox Environment: no sandbox
  • Model Version: gemini-2.5-pro
  • Auth Type: oauth-personal
  • Memory Usage: 1.08 GB
  • Terminal Name: Unknown
  • Terminal Background: #0c0c0c
  • Kitty Keyboard Protocol: Unsupported

Login information

Login is via Google Account (oauth-personal).

Anything else we need to know?

The root cause appears to be a logical deadlock in the agent's reasoning when handling conflicting priorities. When a │ │ user directive ("Log this incompetence") is combined with the agent's self-generated plan to fix the underlying issue, the │ │ agent fails to create a stable, sequential task queue. It gets stuck trying to decide which promise to fulfill first, │ │ leading to total inaction. This suggests a failure in the core execution loop's ability to manage and execute a simple, │ │ ordered list of tasks when faced with self-correction and external feedback simultaneously.

extent analysis

TL;DR

The agent's failure to execute promised actions after acknowledging its own incompetence can be addressed by refining the core execution loop to manage conflicting priorities and self-correction tasks.

Guidance

  • Review the agent's task queue management to ensure it can handle self-generated plans and user directives simultaneously without entering a recursive loop.
  • Implement a priority system that allows the agent to sequentially execute tasks, especially when faced with self-correction and external feedback.
  • Consider adding a mechanism to detect and prevent logical deadlocks in the agent's reasoning when handling conflicting priorities.
  • Analyze the gemini-conversation-1776012242574.json file to understand the specific sequence of events leading to the failure and identify patterns that can inform improvements to the agent's execution loop.

Example

No specific code example can be provided without more details on the agent's implementation, but a general approach might involve using a queue data structure to manage tasks and a priority system to ensure that self-correction tasks are executed promptly.

Notes

The exact implementation details of the agent's core execution loop and task queue management are not provided, which limits the specificity of the guidance. Further analysis of the agent's code and the provided JSON file is necessary to develop a comprehensive solution.

Recommendation

Apply a workaround by refining the agent's task queue management and priority system to handle self-correction and external feedback more effectively, as upgrading to a fixed version is not mentioned as an option in the provided issue context.

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