antigravity_get_modelRetrieves the default model for bridge tasks. Null indicates the bridge picks its own default, so callers know which model will execute tasks.
Return the default model selected for subsequent bridge tasks. Null means agy chooses its own default.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| error | No | ||
| model | No |
Changes observed during successful MCP inspections.
v0.4.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the safe read-only, non-destructive, closed-world profile, so the bar is lower. The description adds genuinely useful behavior by explaining that a null result means agy falls back to its own default, which is not derivable from the annotations.
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 short sentences, zero filler, with the core purpose front-loaded and the null-handling caveat immediately after. Every clause earns its place.
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?
An output schema exists, so return-value structure need not be documented, and the description still covers the one ambiguous case (null). For a zero-parameter read-only getter, nothing needed to invoke it correctly is missing.
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 the baseline is 4. There is no parameter syntax to clarify, and the sentence about null concerns the return value rather than inputs.
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?
States a specific verb and resource ('Return the default model selected') and clarifies scope with 'for subsequent bridge tasks'. It is distinguishable from antigravity_set_model and antigravity_list_models by the word 'selected', though it does not explicitly name those siblings.
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?
Usage is only implied: an agent can infer this reads the current selection before calling antigravity_set_model, but the description never states when to use it versus antigravity_list_models or antigravity_status. No prerequisites or exclusions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.