google_ads_report_columnsGet the column/field definitions for a given Google Ads report as raw CSV.
| Name | Required | Description | Default |
|---|---|---|---|
| reportName | Yes | Name of the report whose column definitions should be returned. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and non-destructive behavior. The description adds that the output is 'raw CSV', providing specific behavior detail beyond the annotations. It does not mention error handling or side effects, but the read-only nature is well-covered.
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 a single, focused sentence that immediately identifies the action, scope, and output format. It is concise and well-structured without unnecessary verbiage.
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?
For a simple metadata retrieval tool with one parameter, the description is largely complete. It covers the main purpose and output format, though it could hint at how report names are sourced or what the CSV contains (e.g., headers) for additional clarity. Minor gaps do not hinder basic usage.
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?
The schema provides a 100% description for the reportName parameter. The tool description essentially repeats this information without adding new details such as allowed values, format constraints, or how to obtain valid report names. No additional semantic value is provided.
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 action (getting column/field definitions) and the resource (a given Google Ads report) and specifies the output format as raw CSV. It effectively differentiates itself from sibling tools like google_ads_reports_list and google_ads_execute_report by focusing on metadata retrieval.
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 does not explicitly state when to use this tool versus alternatives. While the purpose is self-evident and the name suggests it is for retrieving column definitions, there is no direct guidance on use cases or contrast with sibling tools. This is adequate but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes, but the audit and report tools (e.g., audit_rule_output_table vs audit_rule_output_table_historical vs audit_rule_result vs audit_rule_result_campaign) are closely related and rely on detailed descriptions to differentiate.
Naming is generally consistent with snake_case and domain-prefixed groups (google_ads_*, ms_ads_*, perfmon_*), though a few tools are bare nouns (account, task, user) rather than verb-led, which slightly deviates from the dominant pattern.
23 tools is on the higher end but justified for a platform covering multiple ad platforms, audit reports, alerts, and user management; it remains navigable with clear groupings.
The tool set comprehensively covers account enumeration, audit results, report execution for major ad platforms, perfmon alerts, pacing targets, tasks, and users. Minor gaps exist (e.g., no create/update/modify operations), but the core analytics and monitoring surface is well covered.