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antigravity-mcp

antigravity-mcp

by zwsxzy
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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get_agent_job_status

Retrieve compact status for a known job ID without task prompts, logs, or full output; use it for low-token follow-up checks.

Instructions

Read compact status for one known job_id without task prompts, logs or full output. Prefer for low-token follow-up.

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": "get_agent_job_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are supplied, so the description must carry the load; it does disclose that this is a read of a narrow signal set and that prompts/logs/output are deliberately omitted. It says nothing about error behavior for an unknown or expired job_id, nor about what the 'compact status' actually contains.

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 short sentences, front-loaded with the core action and followed by the routing hint. Every phrase carries information; nothing is padded.

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

Completeness3/5

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

For a single-parameter, no-output-schema tool, the description covers what is excluded but not what is returned; since there is no output schema, naming the status fields or possible state values would materially help an agent interpret the result.

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 0% and the single job_id parameter has no documented format. The description adds real meaning by stating the job_id must already be known (a follow-up lookup, not a discovery/search call), but gives no expected id shape or example.

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?

States a specific verb and resource ('Read compact status for one known job_id') and immediately scopes the output as excluding task prompts, logs and full output. This implicitly separates it from heavier siblings like supervise_agent_job or check_agent_job, though no sibling is named directly.

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?

'Prefer for low-token follow-up' gives a concrete selection condition, and the exclusion list ('without task prompts, logs or full output') tells the agent when this tool is insufficient. It stops short of naming which tool to use instead for full output, so the routing is left partly 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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