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pql

Query Google Ad Manager reporting tables using Publisher Query Language for ad-hoc data extraction not covered by standard reports.

Instructions

Execute PQL (Publisher Query Language) queries against GAM reporting tables.

MODE: read-only AUTH: OAuth 2.0 required CREDITS: 0 (free) OUTPUT: Returns a ResultSet with column definitions and rows. Each row is an array of values matching the column order. WHEN TO USE: Use pql for ad-hoc data extraction not covered by the reporting tool's structured reports. LIMITATIONS: Not all PQL tables are available on all networks (some require beta features). The Language and Device_Category tables have known limitations. For structured delivery/inventory reports, use reporting instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesSub-operation to perform: • run_query: Execute a PQL SELECT statement. Example: SELECT Id, Name FROM Order WHERE Status = 'DELIVERING'. Returns rows up to 1000 per call.
network_codeNoGAM network code (e.g. 12345678). Required for all network-scoped operations. Obtain via select_gam_network or list_accessible_networks.
pql_queryNoPQL SELECT statement. Supported tables: Order, LineItem, Creative, AdUnit, Placement, Company, User, and others. Max 1000 rows returned.
Behavior4/5

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

With no annotations, the description carries full burden. It declares read-only mode, OAuth 2.0 requirement, zero credits, and a clear output format (ResultSet with columns and rows). It also states a 1000-row limit. Minor omission: no mention of error handling or timeouts.

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?

The description is well-structured with labeled sections (MODE, AUTH, CREDITS, OUTPUT, WHEN TO USE, LIMITATIONS) and front-loaded with the main purpose. Every sentence adds information; no redundancy.

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

Completeness4/5

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

The tool has 3 parameters and no output schema. The description covers return format, row limit, table references, and alternatives. It could mention pagination or that queries must be SELECT-type, but the read-only flag implies that. Sufficient for the given complexity.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds value beyond schema by listing supported tables (Order, LineItem, etc.), providing an example query, and explaining the network_code parameter's scope. This incrementally aids understanding.

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?

The description clearly states 'Execute PQL queries against GAM reporting tables' with a specific verb and resource. It differentiates from siblings like 'reporting' by stating it's for ad-hoc extraction not covered by structured reports, and explicitly directs users to 'reporting' for structured reports.

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?

The description provides explicit when-to-use ('ad-hoc data extraction not covered by the reporting tool's structured reports') and when-not-to-use ('For structured delivery/inventory reports, use reporting instead'). It also lists limitations about table availability and known table issues.

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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