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runapi-ai
by runapi-ai

get_task

Check the current status and retrieve the latest result payload for a GPT Image task by providing its task ID and originating action.

Instructions

Fetch the current status and latest result payload for a gpt-image task.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesAsynchronous endpoint the task was created on.
task_idYesTask id returned when the task was created.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.2.0
    • removedInput schema / additionalProperties
      Removed value: -false
  2. Changed1 schema field changedv0.1.8
    • changedInput schema / properties / action / description
      Previous value: -"Endpoint the task was created on."New value: +"Asynchronous endpoint the task was created on."
  3. First observedv0.1.0

TDQS

B3.1/5.0
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, yet it says nothing about pending/in-progress tasks, whether the result payload is null until completion, rate limits, or error states. The read-only nature is only implied by 'Fetch'.

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?

A single front-loaded sentence with zero filler that names the action, the resource, and the payload returned.

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 two-parameter polling tool with no annotations and no output schema, the description adequately identifies what is returned but omits the status semantics (possible values, pending behavior) an agent needs to interpret results correctly.

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 100% and both parameters are documented in the schema (task_id, action enum), so the description is not required to compensate. It adds no syntax, format, or pairing detail beyond the schema, so baseline 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?

States a specific verb ('Fetch') and resource ('current status and latest result payload for a gpt-image task'), which clearly separates polling from the sibling creation tools (edit_image, text_to_image). However, it never names those siblings or explicitly frames itself as the poll-for-results counterpart to them.

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?

No guidance on when to call this versus alternatives, and no mention that this is the polling tool for asynchronously created tasks. There is no advice on cadence, retry, or what to do if the task is not yet complete.

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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