Continue an existing Antigravity conversation using its ID to maintain context for multi-turn coding tasks, such as iterative code modifications or follow-up questions.
延续一个已有的 Antigravity 对话。使用 agy_prompt 返回的 conversation_id 来继续之前的上下文。适合多轮交互场景，如迭代代码修改、追问细节等。
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | 追加的指令 | |
| conversation_id | Yes | 要延续的对话 ID（由 agy_prompt 返回） | |
| timeout_seconds | No | 超时时间（秒），默认 300 |
Changes observed during successful MCP inspections.
v1.0.0-windows.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It does disclose the key stateful behavior: this tool continues an existing conversation and preserves previous context. However, it does not mention side effects, whether the conversation is modified, error cases, auth requirements, or rate limits.
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 two sentences long, front-loads the core purpose, and every sentence adds value. It names the resource, the key parameter source, and representative use cases without redundancy.
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 conversational tool, the description covers purpose and usage context and the schema covers all parameters. However, with no output schema, it does not state what the tool returns, which would help an agent understand the result of continuing a conversation. Edge cases are also unaddressed.
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?
Schema description coverage is 100%, so the parameter meanings are already fully documented. The description reinforces that conversation_id comes from agy_prompt, but this is also stated in the schema. It adds no extra semantics for prompt or timeout_seconds.
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: '延续一个已有的 Antigravity 对话' (continue an existing Antigravity conversation). It clarifies that this tool is for continuing prior context using the conversation_id from agy_prompt, which distinguishes it from the sibling agy_prompt.
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?
It explicitly states suitable scenarios: multi-turn interactions such as iterative code modification and follow-up questions. It references agy_prompt as the source of conversation_id, implying agy_prompt is for starting conversations, but it does not explicitly say 'use agy_prompt for new conversations' or list exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.