list_models_with_limits

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

No annotations are provided, so the description carries the full burden. It discloses the tool's behavior as a read-only listing operation with sorting by token limit and explains the rationale (proxy for capacity). However, it lacks details on potential limitations like rate limits, error conditions, or data freshness, which would be valuable for a tool with no annotation coverage.

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 two concise sentences with zero waste: the first states the core action and sorting, the second explains the utility. It is front-loaded with the main purpose, making it easy to scan and understand quickly.

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 the tool's simplicity (0 parameters, no annotations, but with an output schema), the description is mostly complete. It explains what the tool does and why, but could benefit from mentioning the output format or any behavioral constraints. The presence of an output schema reduces the need to detail return values, keeping it adequate.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately adds no parameter details, focusing instead on the tool's purpose and output behavior. A baseline of 4 is applied as it efficiently handles the zero-parameter case without redundancy.

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 specific action ('Lists available Gemini models') and resource ('Gemini models'), with explicit sorting criteria ('sorted by input token limit'). It distinguishes from siblings by focusing on model listing with capacity metrics, unlike notification, code reading/writing, or terminal execution tools.

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 clear context for usage ('Provides a proxy for capacity since exact quota is not available via API'), indicating this tool is for assessing model capabilities when quota data is inaccessible. However, it does not explicitly state when not to use it or name specific alternatives among siblings.

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