list_gemini_models

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'capabilities and limitations' which hints at behavioral traits, but doesn't specify whether this is a read-only operation, whether it requires authentication, what format the output takes, or if there are rate limits. The description adds some context but leaves important behavioral aspects unspecified.

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 perfectly structured with a clear opening statement followed by three specific bullet points. Every sentence earns its place by providing distinct value: the first establishes purpose, the bullets provide concrete usage scenarios. No wasted words or redundancy.

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?

Given zero parameters and no output schema, the description provides adequate purpose and usage guidance. However, for a tool with no annotations, it should ideally mention whether this is a read operation, what the output format looks like (list of models with metadata), and any authentication requirements. The current description is complete enough for basic understanding but lacks operational details.

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?

The tool has zero parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't discuss parameters since none exist, maintaining focus on the tool's purpose and usage. This earns a baseline 4 for zero-parameter tools.

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's purpose with specific verb ('List') and resource ('available Gemini AI models and their capabilities'). It distinguishes from sibling tools count_gemini_tokens (token counting) and query_gemini (model querying) by focusing on model discovery and capability assessment.

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 explicitly provides three bullet points detailing when to use this tool: to discover models, understand capabilities/limitations, and choose appropriate models for tasks. This gives clear guidance on its intended context and distinguishes it from alternatives like query_gemini which would be used after model selection.

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