list_available_models

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

No annotations are supplied, so the description carries the full disclosure burden. It does disclose real behavior beyond the name: results come from the IDE with a Gemini REST fallback, and only currently-live models are returned. It does not say whether this makes a network call, what happens if the IDE is unavailable and the fallback fails, or what the response entries look like.

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 sentences, both earning their place: the first establishes what is returned and from where, the second establishes the sequencing rule. The call-to-action is placed where an agent will read it before deciding.

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?

For a zero-parameter, read-only discovery tool with no output schema, the definition covers what the agent needs to decide to call it and what class of values it yields. The only minor gap is not stating the return shape (e.g., a list of model name strings) that the agent will need to pass into dispatch_gemini_agent.

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 takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a no-parameter tool applies. The description correctly adds no fake parameter guidance and instead spends its words on scope and sequencing.

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 states a specific verb and resource ('List the live models') and adds the source scope ('Antigravity IDE or Gemini REST fallback'). It also implicitly separates the tool from the dispatch family by framing it as a discovery step, so an agent can tell what it does without opening the schema.

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?

It names the downstream sibling explicitly ('Call this before dispatch_gemini_agent') and gives the triggering condition ('when you do not already know an exact, currently-live model name'), which also implies the skip case. The only gap is that the when-not case is left implicit rather than stated.

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