Google Ad Manager MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states this is a creation operation, implying it's a write/mutation tool, but doesn't cover critical aspects like required permissions, whether it's idempotent, error handling, or rate limits. The mention of returning 'created order details' hints at output but lacks detail on format or structure.

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

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

The description is well-structured and appropriately sized. It front-loads the purpose in the first sentence, then lists parameters with brief explanations, and ends with return information. There's no wasted text, though the 'Args:' and 'Returns' formatting could be slightly more integrated for flow.

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

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

Given the tool has an output schema (which handles return values) and only 2 parameters with 0% schema coverage, the description does a decent job. It covers the purpose and parameter semantics adequately. However, as a mutation tool with no annotations, it lacks behavioral details like error cases or side effects, making it incomplete for safe agent use.

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

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

Schema description coverage is 0%, so the description must compensate. It adds meaningful context for both parameters: 'order_name: Name for the new order' and 'advertiser_id: ID of the advertiser company'. This clarifies what each parameter represents beyond just their types, though it doesn't specify constraints like name length or advertiser ID format.

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

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

The description clearly states the tool's purpose: 'Create a new order for an advertiser.' This specifies the verb ('Create'), resource ('order'), and context ('for an advertiser'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'find_or_create_order' or 'get_order', which would be needed for a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether the advertiser must exist first), compare it to similar tools like 'find_or_create_order', or specify scenarios where it's appropriate. This leaves the agent without context for tool selection.

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