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AdsAgent — Google Ads MCP

google_ads_benchmark_metrics

Read-only

Read bounded native benchmark_metrics insight. Restricted services require fresh server-verified access and otherwise refuse. No writes or access grants.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes
customer_idYes10-digit Google Ads customer id.
connection_contextNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / connection_context
      Added value: +{
      +  "pattern": "^mctx_v1_[0-9a-f]{64}$",
      +  "type": "string"
      +}
  2. Added

TDQS

C2.9/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful context beyond that: restricted services need fresh server-verified access and otherwise refuse, and it explicitly disclaims writes and access grants. This helps the agent anticipate refusal behavior, though return format is still unexplained.

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?

Three short sentences with the read-only nature and access constraint front-loaded; little waste. It loses a point for vague filler like 'bounded native' that consumes space without adding meaning.

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

Completeness2/5

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

There is no output schema and the tool takes a rich nested body whose sub-fields are undocumented. The description omits what metrics are returned, the shape of the response, and guidance on the body payload, so it is not complete enough for an agent to call this correctly without additional assumptions.

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 only 33% (customer_id is documented, the nested body and connection_context are not), so the description should compensate and instead mentions no parameters at all. The required nested body fields (location_id, industry_vertical_id, product_codes, dates, currency_code) are left entirely to the schema, which does not describe them.

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 states a verb and resource ('Read ... benchmark_metrics insight'), so the core purpose is inferable. However, the phrasing is jargon-heavy ('bounded native') and it offers no differentiation from the several sibling benchmark tools (google_ads_benchmark_dates, _locations, _products, _sources), leaving the agent to guess what is unique here.

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 when-to-use guidance and no comparison to alternatives. The sentence about 'restricted services require fresh server-verified access' is an access precondition rather than a statement of when this tool should be selected over siblings.

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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