Incident Report: Gemini CLI Agent Structural Failure

Gemini API
1

  1. System Environment

    • Application: Gemini CLI

    • Operating System: Darwin (macOS)

    • Runtime: Bun

    • Framework: Next.js 16.2.3 (App Router / Turbopack)

    • Current Session State: Long-running migration task (PCNE study guide migration)

  2. Description of Issues The agent is currently experiencing a severe degradation in output control, primarily characterized by a “Decoupling of Intent and Execution.”

A. Structural Parameter Dropout

  • Symptom: Required arguments in tool calls (e.g., file_path, command, old_string) are missing from the final JSON output, despite being correctly identified in the thought process.

    • Detailed Observation: Even when I implement a mandatory “Pre-flight Checklist” within the block to verify parameters, the generated tool JSON immediately following it fails to include the identified keys. This indicates a failure in schema-compliant token generation rather than a logical misunderstanding.

B. Persistent Error Loops

  • Symptom: The agent becomes trapped in infinite loops of validation errors (e.g., params must have required property ‘file_path’).

    • Detailed Observation: Receiving explicit error feedback from the system does not lead to a successful correction in the subsequent turn. The agent acknowledges the mistake and plans a fix, but the output generation layer repeatedly produces the same malformed JSON.

C. Procedural Integrity Failure (Rule Violation)

  • Symptom: Failure to adhere to project-specific constraints defined in GEMINI.md or session instructions.

    • Specific Examples:

      • Neglecting the “commit after every step” rule.

        • Incorrectly archiving/deleting source HTML files against explicit safety mandates.

        • Failing to respect the boundaries and limitations of Plan Mode versus Auto-Edit Mode.

  1. Reproduction Steps

    1. Initiate a complex task requiring multiple tool calls (e.g., file refactoring).

    2. The agent correctly plans the tool use in the thought block, listing all required arguments.

    3. The actual tool call JSON is emitted with key-value pairs missing (e.g., calling run_shell_command with an empty object {} instead of{“command”: “…”}).

    4. The system returns a validation error.

    5. The agent acknowledges the error and repeats the failure in the next turn.

  2. Analysis and Hypotheses

    • Context Bloating: The degradation appears to correlate with the expansion of the context window. As the session history grows, the agent’s ability to strictly follow tool schemas seems to weaken.

    • Attention Decoupling: There is a clear disconnect between the “Reasoning Layer” (which produces the thought process) and the “Output Layer” (which produces the tool-calling tokens).

    • Instruction Overload: The accumulation of multiple project rules, global personal memories, and session-specific hints may be creating conflicting priorities, leading to the prioritization of “task completion” over “structural correctness.”

  3. Impact This issue results in significant wasted token consumption, prevents task completion, and compromises the integrity of the target codebase due to unverified file operations and skipped procedural steps.

I hope this report provides the necessary technical depth for the Google development team to diagnose and resolve these systemic issues.