Gemini Search

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden, and it does disclose two useful traits: invocation is model-driven and yolo=True avoids interactive prompts. However, it says nothing about approval_mode, checkpointing side effects, timeout behavior, or any permission/rate constraints, which matters for an 8-parameter tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with no filler, and the core purpose is front-loaded ahead of the operational note. Efficient and readable, though the note could be trimmed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists so return values need not be described, but with no annotations, 8 parameters at 0% coverage, and undocumented behavioral flags like approval_mode and checkpointing, the description is not complete enough for confident invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 8 parameters, so the description must compensate, but it only explains the yolo default. model, timeout_s, extra_args, include_dirs, approval_mode, and checkpointing are left entirely unexplained in both schema and description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: 'Lightweight search' that instructs the model to use built-in GoogleSearch and cite sources. That is clear enough to understand the tool's function, but it does not distinguish itself from siblings like GoogleSearch or GeminiGoogleSearch, leaving the agent to guess which search variant applies.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The only guidance is the 'Note' about model-driven invocation and defaulting yolo=True to avoid interactive prompts, which is invocation mechanics rather than when-to-use. There is no statement of when this search should be chosen over gemini_web_fetch, GoogleSearch, or GeminiGoogleSearch, and no exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.