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Change proposal status

get_change_status
Read-onlyIdempotent

Status of a change proposal and its operation: whether it is approved, whether it was executed, with what result; for ad groups and ads — also the actual delivery state reported by the platform (review, rejection, issues), only when it was read after the change ran.

Input Schema

NameRequiredDescriptionDefault
change_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so safety is covered and the bar is lower. The description does add real context beyond annotations: the scope of returned status (approved, executed, result) and the important caveat that platform delivery state for ad groups/ads is only present if the read happened after execution — a timing dependence an agent cannot get from structured fields.

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

Conciseness3/5

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

It is short, but the structure is weak: it is a sentence fragment beginning with a noun ('Status of a change proposal...') rather than leading with what the tool does. The conditional clause about delivery state is tacked on and reads as an afterthought rather than a clearly bracketed caveat.

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?

There is no output schema, so the description carries the burden of explaining return values — it does so partially, enumerating approval/execution/delivery dimensions but not the response shape or what happens for non-ad entities or unexecuted changes. Combined with the missing parameter explanation and workflow guidance, it is adequate but leaves clear gaps for a status-lookup tool embedded in a propose/approve workflow.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the single parameter change_id is a bare string in the schema, so the description must explain it — but it never mentions change_id, where it comes from (presumably the ID returned by propose_change), or what happens with an unknown ID. With one undocumented required parameter, the description does not compensate for the coverage gap.

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

Purpose3/5

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

The description identifies the resource (a change proposal) and the information returned (approval status, execution outcome, delivery state), which lets an agent infer this is a status-read tool. However, it is written as a noun-phrase fragment with no verb — never stating that it retrieves/returns status given an ID — and it does not differentiate itself from siblings like approve_change, propose_change, or the *_changes tools.

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 call this versus alternatives: nothing says it should be used after propose_change, or that approve_change is the mutation counterpart. The only conditional ('only when it was read after the change ran') describes a data caveat, not a usage rule, so the agent is left to infer the workflow entirely.

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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