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Google Ads MCP Reader

by ceotind

get_resource_metadata

Retrieve selectable, filterable, and sortable fields for any Google Ads resource to avoid API errors when building queries.

Instructions

Discover which fields are SELECTable, FILTERable, and SORTable for a Google Ads resource. Always call this before search() — using incorrect field names causes API errors. Compatible metrics.* and segments.* fields are included for reporting queries.

Args: resource_name: The resource to explore (e.g. 'campaign', 'ad_group', 'keyword_view', 'search_term_view', 'customer_client').

Returns: A dict with resource name and three sorted arrays of fully-qualified field names. Example for resource='campaign': selectable: ['campaign.id', 'campaign.name', 'campaign.status', 'metrics.clicks', 'metrics.impressions', ...] filterable: ['campaign.id', 'campaign.status', ...] sortable: ['campaign.id', 'metrics.clicks', ...]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
resource_nameYes
Behavior4/5

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

No annotations provided, but description fully explains input, output structure with example, and includes compatible fields. No side effects noted, which is appropriate for a read-only discovery tool.

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?

Front-loaded with purpose and usage, followed by structured Args and Returns sections. Every sentence adds value with no redundancy.

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

Completeness5/5

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

For a simple one-parameter tool with no annotations or output schema, the description provides complete context: purpose, usage, parameter explanation, return format, and examples.

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

Parameters5/5

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

Schema coverage is 0%, but description compensates with detailed explanation of the single parameter 'resource_name', including example values and a list of common resources.

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?

Description clearly states the tool discovers which fields are SELECTable, FILTERable, and SORTable for a Google Ads resource, with explicit examples. It distinguishes itself from siblings like 'search' by being a preparatory tool.

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

Usage Guidelines5/5

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

Explicitly advises 'Always call this before search()' and explains that using incorrect field names causes API errors, providing clear when-to-use guidance.

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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