Skip to main content
Glama
adeelali4

antigravity-mcp-server

by adeelali4

Follow up in the same Antigravity conversation

ag_followup

Send a follow-up prompt into the same Antigravity conversation to continue a completed task, preserving context for iterative work like adjusting a responsive header.

Instructions

Send a follow-up into the SAME Antigravity conversation as a finished task, so it keeps its context (e.g. 'now make the header responsive'). Use this rather than a fresh ag_delegate whenever the request builds on work it just did.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYes
task_idYes
timeout_secondsNo
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the key behavioral trait that the tool keeps context from the previous task. However, it does not mention required permissions, whether the task must be 'finished' (as stated), rate limits, or any side effects. The description adds some value but leaves significant gaps.

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 two sentences, front-loading the purpose and usage guidance. Every sentence adds value, and there is no extraneous text. The structure is efficient and clear.

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

Completeness2/5

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

Given the tool has 3 parameters (2 required), no output schema, and no annotations, the description is insufficient. It does not explain the task_id format, what timeout_seconds controls, or the return value. It also does not clarify whether the 'finished task' condition is a requirement or a hint. The description leaves many critical details undocumented.

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

Parameters1/5

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

Schema description coverage is 0%, meaning the input schema provides no property descriptions. The description does not explain the meaning of any parameter (task_id, prompt, timeout_seconds). It only gives an example prompt in the quote. This is a critical failure to compensate for the missing schema descriptions.

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

Purpose4/5

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

The description clearly states the tool sends a follow-up into the same conversation as a finished task, using 'prompt' as the follow-up request. It contrasts with the sibling 'ag_delegate' by noting context preservation. The phrasing 'as a finished task' is slightly ambiguous, but the example clarifies the intent.

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 provides when to use this tool ('whenever the request builds on work it just did') and when not to use it (by contrast with 'ag_delegate'). This is excellent guidance for tool selection, directly addressing the distinction from the most relevant sibling.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/adeelali4/antigravity-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server