Gemini tool calling: why completion claims need verifiable results

In my personal experience using Gemini in tool-enabled workflows, I have encountered responses that present a task as completed when I cannot verify the intended outcome. I want to discuss that gap constructively with other developers.

A confident completion message affects what a user does next: trust the result, retry an operation, or investigate a failure. If the message is not grounded in the actual tool result, the user ends up doing the verification work anyway.

Scope of this feedback

This is qualitative feedback from my own experience, not a benchmark or a claim about every Gemini model or integration. I am not attaching a minimal reproducible example, exact model/version details, or request/response traces here. I therefore cannot isolate the cause to the model rather than the application, orchestration layer, or tool integration.

The distinction I want applications to make

• Proposed: the assistant describes an action.
• Attempted: a tool call was issued.
• Tool-reported success: the tool returned a success response.
• Verified outcome: the resulting state was checked and matches the requested outcome.

Those states should not all be described as "done." If a tool fails, access is unavailable, or the final state cannot be checked, the response should say so clearly.

For workflows that change something, I would like applications to check the resulting state where practical before reporting completion. When only part of a task succeeds, the response should identify that part and what remains unresolved.

Questions for developers

How do you keep completion claims grounded in tool results in Gemini function-calling workflows? What patterns have worked for ambiguous tool responses, partial success, and verification after an action?

I would also welcome suggestions for the most useful details to include in a reproducible follow-up report.

I shared the same concern on the Google AI Developers Forum.

I am interested in practical ways to make these workflows more reliable and their status messages more accurate.