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Camberstack: Google Ads

Account overview

account_overview
Read-only

Spend, clicks, conversions and cost per conversion per campaign over a window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLook-back window in days, ending yesterday
customer_idYesGoogle Ads customer ID, with or without dashes (from list_accounts)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds the result granularity (per campaign) and that the window ends yesterday via the schema, which is modest but real context. It says nothing about result volume, whether zero-activity campaigns are included, or how metrics like cost per conversion are derived or nulled.

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 sentence with no filler, front-loading the metric list and the window scope. Every clause carries information and nothing is repeated from the title.

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?

With no output schema in play, the description partially compensates by naming the metrics returned, which is the most important thing an agent needs to judge relevance. It still omits aggregation level beyond 'per campaign', result ordering, and whether the response is a single row or a list, leaving an agent to discover these by calling.

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%: both days (look-back window ending yesterday) and customer_id (format and provenance from list_accounts) are fully documented in the schema. The description adds nothing beyond the schema, so the baseline of 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?

The description names a concrete resource (campaign performance) and enumerates the specific metrics returned: spend, clicks, conversions, cost per conversion, over a window. That is far better than a tautology of the title. However, it does not differentiate itself from siblings like run_gaql or find_wasted_spend, which an agent might reasonably consider for similar reporting questions.

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, no prerequisites, and no mention of alternatives such as run_gaql for arbitrary queries or find_wasted_spend for the narrower diagnostic case. The only implied usage is that the tool is read-oriented, which the agent could infer from the name alone.

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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