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Ask Antigravity (new conversation)

antigravity_ask

Ask a question to Antigravity AI to get an answer. Sends your prompt to a new conversation and returns the final response text. Use for quick tasks and tool-calling.

Instructions

Ask Antigravity (agy CLI, Gemini by default) a question in a NEW conversation.

Uses your existing AI Pro authentication (silent-auth via Windows Credential Manager). Returns the model's final response as text. Good for fast tool-calling and short tasks; for heavier reasoning pick a bigger model or use the host model directly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoOptional model slug to run this conversation on (agy's --model), e.g. "gemini-3.1-pro-high" or "claude-sonnet-4-6". Omit to use the model set in agy's settings.json (gemini-3.6-flash-high by default). Must be one of `agy models` — an unknown slug is rejected up front (agy would otherwise silently ignore it and fall back to the default). agy 1.1.5 replaced the old human labels ("Gemini 3.1 Pro (High)") with these slugs and 1.1.6 added the gemini-3.6-flash family; the old form is no longer accepted. See antigravity_status / `agy models` for the valid slugs.
watchNoIf true, open a live "watch" view in your browser that streams agy's steps (narration + the real commands it runs) as it works. agy still runs headless; the same final text is returned. Best- effort and cross-platform — if the browser can't open, the run completes normally. Default false.
promptYesQuestion or instruction for Antigravity.
timeout_sNoMax seconds to wait for agy to complete. Default 180.
workspaceNoWorking directory for the conversation. Defaults to cwd. Choose an existing project dir for context-aware responses.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations provide readOnlyHint=false, openWorldHint=true, idempotentHint=false. Description adds authentication method (silent-auth), return type (text), and a note on use cases. Does not contradict annotations.

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?

Three concise sentences: purpose, auth, return and guidance. Front-loaded with purpose, no wasted words.

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

Completeness4/5

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

Covers purpose, usage, auth, return type, and model guidance. With output schema present, return values need not be detailed. Slightly lacking on side effects of opening a new conversation, but sufficient for effective selection.

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

Parameters4/5

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

Schema coverage is 100% with parameter descriptions. Description adds extra context for the model parameter ('for heavier reasoning pick a bigger model'), enhancing semantic understanding beyond the schema.

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?

States clearly: 'Ask Antigravity a question in a NEW conversation.' Verb 'Ask', resource 'Antigravity', context 'new conversation', distinguishing it from 'antigravity_continue' which continues an existing conversation.

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?

Explicitly guides: 'Good for fast tool-calling and short tasks; for heavier reasoning pick a bigger `model` or use the host model directly.' Also implies not for continuing conversations by saying 'NEW conversation.'

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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