ga_run_pivot_report

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

The annotation readOnlyHint=true already establishes the tool is read-only. The description adds valuable behavioral context about potential huge output size and token optimization, warning about limits. This goes beyond the annotation by flagging performance implications, which is helpful for an AI agent to make safe and efficient calls.

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 extremely concise: one main sentence plus a focused warning. It front-loads the core purpose and adds a single high-value caution about token usage. Every sentence earns its place, with no fluff or repetition of schema details.

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?

This is a moderately complex tool with 4 parameters, no output schema, and sparse schema descriptions. The description covers purpose and a key performance warning, but does not explain the pivots/dimensions relationship, expected return shape, or how to structure date ranges beyond what the schema provides. It is minimally viable but leaves significant gaps for an agent to infer.

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?

Schema description coverage is only 25%, and the description does little to clarify the parameters. It mentions 'row and column dimensions' but does not explain that 'pivots' and 'dimensions' are distinct structures, nor does it describe how metrics or dateRanges behave. The token-optimization note mentions 'Limit dimensions' but offers no concrete parameter syntax or usage examples, leaving the agent under-informed about the main input fields.

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 a specific action: 'Run a pivot table report with row and column dimensions.' This distinguishes it from sibling tools like ga_run_report (standard reports) and ga_run_funnel_report by emphasizing the pivot/crosstab nature. The verb 'Run' and resource 'pivot table report' are specific and unambiguous.

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 provides clear usage context: 'Recommended for analysis, not raw data extraction' and advises limiting dimensions/date ranges due to token consumption. This implicitly tells the agent when to use this tool (analysis) and when not to (raw extraction), though it does not explicitly name an alternative tool. The guidance is practical and actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.