Lists configured LLM providers from Antigravity config.json, returning provider names and total count.
List configured LLM providers from Antigravity config.
Reads the providers section from config.json.
{"providers": [{"name": str}], "count": int}
| Name | Required | Description | Default |
|---|---|---|---|
| ctx | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations to carry safety information, the description states the behavior itself: it reads the providers section from config.json and returns a list, implying no mutation. The exact return shape is also given. It doesn't cover auth or error cases, but that is acceptable for a simple read tool.
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 short, front-loaded with the action, and uses a clear Return Format section. Every sentence adds information with no 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?
For a simple no-required-parameter list operation, this is complete: it identifies the source config, the exact providers section, and the return format. An agent has everything needed to invoke it correctly.
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 only parameter is an optional `ctx` with a default null, and neither the schema nor the description explains its meaning. Since there are no required business parameters the practical gap is small, but the description adds no parameter semantics and schema coverage is 0%.
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 opens with a specific verb and resource: 'List configured LLM providers from Antigravity config', and further scopes it to 'the providers section from config.json'. This clearly distinguishes it from the skills/config sibling 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 wording makes the applicable context clear: call it when you need the configured LLM providers. It does not explicitly name alternatives or when-not conditions, but the read-only list scope is unambiguous against the sibling set.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.