Look up known model IDs, effort levels, and manual config paths for each Claude Code and Antigravity harness; use as guidance, since CLIs accept any ID.
Known model ids and effort levels for each harness, plus the paths to change them by hand. Guidance, not a whitelist — the CLIs accept any id.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it does disclose a meaningful behavioral trait: the CLI accepts any id, so these values are advisory rather than enforced. Nothing is said about staleness or sandbox-specific availability, but the key behavioral caveat is present.
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, front-loaded with the return content, followed by the caveat that changes how the output should be treated. 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?
With no output schema, the description must convey the return shape, and it does: model ids, effort levels per harness, and manual-config paths. It is self-contained for a zero-parameter info lookup, though it could note whether results are host-specific.
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?
There are zero parameters, so the baseline is 4. The description adds no parameter detail, and none is needed.
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 resource — known model ids, effort levels per harness, and config paths — which is a clear read-only informational purpose that contrasts implicitly with the mutating sibling agent_set_model. It does not name that sibling, so the differentiation is inferential rather than explicit.
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 implied (consult this before choosing a model) but no alternative is named and no trigger condition is given. The 'Guidance, not a whitelist' caveat is a useful consumption instruction, but it is not a when-to-use versus agent_set_model or agent_limits statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.