google_ads_reports_listGet the list of available Google Ads report definitions (report/resource names in the Google Ads GAQL schema) as raw CSV.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 declare readOnlyHint=true and destructiveHint=false, so the read-only nature is known. The description adds valuable behavioral context by specifying the output format ('raw CSV') and the content (report/resource names in the GAQL schema), which goes beyond the annotations. No contradictions detected.
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, well-structured sentence that front-loads the primary action ('Get the list'), then specifies the content and output format. Every word contributes meaning, with no filler or redundancy.
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 no-parameter, read-only list tool, the description is fully complete. It states what the tool returns (list of report definitions) and the format (raw CSV), which is all an agent needs to invoke it correctly. The lack of an output schema is compensated by this explicit return description.
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?
This tool has zero parameters, and the schema description coverage is 100% (vacuously). Per the rubric, a baseline of 4 is appropriate. The description does not need to explain parameters since there are none, and it correctly avoids inventing any.
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 function: retrieving a list of available Google Ads report definitions (report/resource names) as raw CSV. It specifies the resource type and output format, making the purpose unambiguous. However, it does not explicitly distinguish itself from sibling tools like google_ads_report_columns, though the term 'report definitions' implies a difference.
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 implies usage context—when you need the list of report definitions—but does not explicitly state when to use this tool versus alternatives such as google_ads_execute_report or google_ads_report_columns. It provides clear context but no exclusions or comparative guidance.
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.