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get_asset_status

Check an imported asset's build status by reading its engine receipt, optionally waiting up to 30 seconds for a specific request ID to avoid stale success.

Instructions

Read an engine receipt, optionally wait up to 30s for a specific build request.

Pass the build's request_id to prevent stale success. A wait timeout remains queued/unknown; superseded means another revision is current. Imported includes paths, geometry and scene.

Input Schema

NameRequiredDescriptionDefault
asset_idYes
request_idNo
wait_secondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.6.0
    • addedInput schema / properties / request_id
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "title": "Request Id"
      +}
    • addedInput schema / properties / wait_seconds
      Added value: +{
      +  "default": 0,
      +  "title": "Wait Seconds",
      +  "type": "number"
      +}
  2. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the burden and delivers real behavioral context: the 30s wait ceiling, that a timeout stays 'queued/unknown', that 'superseded' means another revision is current, and what 'Imported' contains. It still omits auth requirements and whether the read is safe/non-mutating, but the status-state disclosures are genuinely useful.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the core action in the first clause, then adds three tight sentences of qualifying detail with little waste. Slightly jargon-heavy ('engine receipt'), but efficiently sized.

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?

Without annotations or an output schema, the description must stand alone, and it partially does by explaining several status values. It does not cover asset_id semantics or state the return shape exhaustively, leaving gaps for a tool whose statuses are the whole point.

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 0%, so the description must compensate. It explains request_id's role (prevents stale success) and wait_seconds' cap (up to 30s), but asset_id is left entirely undefined, so roughly a third of the parameters remain undocumented.

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 an engine receipt' for an asset) and clarifies the wait semantics, so an agent can tell it returns build/asset status. However it never distinguishes itself from the closely related sibling get_task_status or inspect_asset, leaving overlap ambiguous.

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

Usage Guidelines3/5

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

Gives conditional guidance on parameters ('pass the build's request_id to prevent stale success', 'optionally wait up to 30s'), which implies when to wait vs. poll. But it never states when to choose this over get_task_status or inspect_asset, so the when-to-use decision is left to inference.

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