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antigravity-mcp

antigravity-mcp

by zwsxzy
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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check_agent_job

Check a dispatched agent job's status, logs, duration, and output using its job ID to monitor progress and retrieve results.

Instructions

Check the status, logs, duration, and output of a dispatched agent job.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "job_id": "<job_id>"
    },
    "name": "check_agent_job"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYesThe job ID returned from dispatch_gemini_agent (e.g. 'agy-1a2b3c4d').

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden as a single terse sentence. It never states that the operation is read-only, whether it blocks or polls, whether log output is truncated or streamed, or how it behaves for a still-running versus failed job.

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?

One sentence, zero filler, and the object of the operation is front-loaded before the enumerated return facets. Nothing here fails to earn its place.

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?

With no output schema and no annotations, the description usefully compensates by naming what comes back (status, logs, duration, output). It still omits polling/streaming behavior and terminal state handling, which an agent monitoring a job would want.

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 description coverage is 100% for the single job_id parameter, and the schema description even cites dispatch_gemini_agent as the source and gives an example format. The prose adds no meaning beyond the schema, so the baseline of 3 applies.

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 pairs a specific verb ('Check') with a specific resource ('a dispatched agent job') and enumerates the returned facets (status, logs, duration, output), which is clearer than the bare name. It implicitly distinguishes itself from dispatch_gemini_agent by noting the job is already dispatched, but it does not explicitly contrast itself with list_active_jobs or cancel_agent_job.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus list_active_jobs (which also surfaces jobs) or cancel_agent_job. The dependency on a prior dispatch is only hinted at through 'dispatched', leaving the workflow condition to inference.

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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