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Continue Antigravity conversation

antigravity_continue

Resume a specific Antigravity conversation by sending a follow-up prompt. Continues the exact conversation associated with a given workspace directory.

Instructions

Continue the Antigravity conversation rooted at this workspace.

Resumes the exact conversation id recorded for workspace (via agy's --conversation flag), not agy's global "most recent", so it stays correct even if agy was used elsewhere in between.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoOptional model label for this turn (agy's --model). agy's model is per-invocation, not baked into the conversation, so a follow-up can run on a different model than the original ask — omit to use agy's settings.json default. Validated against `agy models`; an unknown label is rejected (agy would silently ignore it).
watchNoIf true, open a live "watch" view in your browser that streams agy's steps as it works (same return value, best-effort). Default false.
promptYesFollow-up message.
timeout_sNoMax seconds to wait for agy to complete. Default 180.
workspaceNoWorking directory used by the prior conversation. Defaults to cwd.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

The description adds behavioral nuance beyond annotations: it clarifies conversation resumption behavior (specific ID, not global). Annotations indicate mutation (readOnlyHint false) and side effects (openWorldHint true), which the description does not contradict. No mention of auth or rate limits, but for this tool the added context is sufficient.

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?

Two sentences with clear front-loading of action. Every sentence earns its place with no redundancy or unnecessary detail.

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?

Given the tool's complexity (5 parameters, output schema exists), the description is complete enough for an agent to use correctly. It explains the unique conversation resumption behavior, and the schema covers parameters and output.

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

Parameters3/5

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

Schema coverage is 100% with detailed parameter descriptions. The description adds no additional meaning beyond what the schema provides for parameters. Baseline of 3 is appropriate since schema does the heavy lifting.

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 clearly states the tool continues an Antigravity conversation for a specific workspace, distinguishing it from starting a new one. It uses specific verbs and resource description, and implicitly differentiates from siblings like antigravity_ask.

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

Usage Guidelines4/5

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

The description provides explicit context on when to use the tool: it resumes the exact conversation ID for the workspace, not the global most recent. It explains why this matters (stays correct if agy used elsewhere). However, it does not explicitly name alternatives or state when not to use.

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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