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add_antigravity_submit

Finish connecting a Google Antigravity account started with add_antigravity_start.

`code` is the value of `?code=...` on the antigravity.google/oauth-callback page the
user landed on; `state` is what add_antigravity_start returned. Returns
{status, account_id, account_email, requires_project}. By default this also creates
the GCP project in one step (`complete=True`) and adds `project_id`. Pass
`complete=False` to defer and call `complete_antigravity_account(account_id)` later.
If auto-onboarding fails the result keeps `requires_project: true` and carries
`onboard_error`; retry with `complete_antigravity_account(account_id)`. Errors:
"unknown state" (start again) or "google_api_error" (the code was rejected or
already used; start again).

Input Schema

NameRequiredDescriptionDefault
codeYes
stateYes
completeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / complete
      Added value: +{
+  "default": true,
+  "title": "Complete",
+  "type": "boolean"
+}
  2. Added

TDQS

A5/5.0
Behavior5/5

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

With annotations already declaring this is a non-readonly, open-world, non-idempotent write, the description still adds rich context: the return fields, the default one-step GCP project creation, the deferred path, the failure shape with requires_project/onboard_error, and specific error strings. This goes well beyond what the annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the purpose, then parameters, return shape, default behavior, and errors. Despite handling a multi-step OAuth flow, every sentence adds actionable information; the repetitive 'start again' is confined to distinct error cases and is not wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description supplies the return shape and failure modes. Annotations cover safety, so the remaining burden is on behavior and parameters, both of which are complete for an agent to call this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the full parameter burden. It defines `code` as the `?code=...` value from the callback page, `state` as the value returned by add_antigravity_start, and `complete` as controlling immediate GCP project creation vs deferral. All three parameters are explained with enough meaning to invoke correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb+resource ('finish connecting a Google Antigravity account') and immediately ties it to the sibling 'add_antigravity_start' that starts the flow. An agent can distinguish this from both the start and completion tools without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly says when to use this tool ('started with add_antigravity_start'), names the alternative ('complete_antigravity_account') and the condition for using it ('pass complete=False to defer'), and gives recovery instructions for each error. No inference needed.

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

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