llm_gemini

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

No annotations are provided, so the description must fully explain behavior. It states the tool runs non-interactively and uses Google One AI Pro subscription, but it does not disclose any side effects, auth requirements, rate limits, error handling, or prerequisites (e.g., local CLI setup). This lack of detail makes it insufficient for an agent to understand behavioral implications.

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?

The description is concise with a few sentences and an argument list. It front-loads the purpose and includes useful context. No redundant information is present.

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?

The tool is simple with two parameters and an output schema, so the description is moderately complete. It explains the purpose, when to use it, and available models. However, it omits details about error conditions, invalid model handling, and the requirement for the local Gemini CLI to be installed.

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%, so the description must add meaning. It lists the available models for the 'model' parameter and mentions the default, which adds value beyond the schema. However, it does not explain the content, format, or constraints for the 'prompt' parameter, nor any validation rules.

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?

The description clearly states the tool routes tasks to the Gemini CLI agent and runs them non-interactively. It mentions use as a fallback for Claude limits, but does not explicitly differentiate from other llm_* siblings like llm_auto or llm_route, so differentiation is somewhat weak.

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 description provides guidance on when to use the tool: 'ideal as a fallback when Claude limits are tight, or for tasks that benefit from Google's Gemini models.' It also notes the subscription usage. However, it does not specify when not to use it or list explicit alternatives.

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