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raihan675

OpenAI Ads & Conversion Intelligence MCP Server

by raihan675

Get Audience Operation Status

get_audience_operation_status

Poll an asynchronous audience membership operation (add, remove, replace, merge) using its operation ID and audience ID to determine if it succeeded or failed.

Instructions

Poll the status of an asynchronous membership operation (add, remove, replace, merge) until 'succeeded' or 'failed'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
operation_idYesOperation ID returned by membership mutation
custom_audience_idYesTarget audience ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
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 does convey the asynchronous, polling-oriented nature and the terminal states 'succeeded' or 'failed'. However, it does not mention polling behavior such as rate limits, timeouts, or behavior for invalid operation IDs, nor does it describe the response content beyond indicating status.

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 a single, tightly constructed sentence with no filler. The core action, the resource, and the stopping condition are all front-loaded, and every word contributes value.

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?

For a two-parameter polling tool with a clear schema and no output schema, the description is largely complete. It explains the purpose, the asynchronous nature, and the terminal states. A minor gap is the lack of polling-interval or backoff guidance, but the core context needed to select and invoke the tool is present.

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%, so the schema already documents both required parameters. The description adds no additional parameter-level meaning beyond what the schema provides, so the baseline score of 3 is appropriate.

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

Purpose5/5

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

The description states a specific verb ('Poll'), a specific resource ('status of an asynchronous membership operation'), and enumerates the operation types ('add, remove, replace, merge'). This clearly distinguishes it from sibling tools like get_bulk_mutation_job_status, which targets bulk mutation jobs rather than individual audience membership operations.

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?

The description provides clear context: it is for polling an asynchronous membership operation until a terminal state is reached. It does not explicitly name alternatives or exclusion conditions, so it stops short of a 5, but the polling intent and completion criteria are unmistakable.

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