Models Get

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows it is a safe read operation. The description adds behavioral context by specifying that the list is personalized ('available to you') and that it returns model IDs. No contradictory behavior is reported, and the description supplements the annotations with useful detail.

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 sentences long, front-loaded with the main action, and every word earns its place. It provides examples and usage guidance without unnecessary filler.

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 has no parameters, no output schema, and strong annotations, the description fully covers the necessary context. It states what is returned, with examples, and connects to a concrete next step. For a simple read-only list tool, this is complete.

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, so the baseline for parameter semantics is 4. The description compensates by clarifying what the output will be (model IDs) and how to use them, which is not evident from the empty schema. Since there are no params, this is essentially perfect.

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 function: 'List the lipsync models available to you', using a specific verb and resource. It provides concrete examples (lipsync-2, sync-3, react-1) and differentiates from sibling tools by focusing on models rather than assets, generations, or voices.

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 gives explicit downstream context: 'Use a returned model id as the `model` in generate_create-generation.' This tells the agent when to use the tool (before generating a lipsync) and how the result is consumed. It does not explicitly state exclusions or alternatives, but the guidance is clear enough.

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