Aggregate By Column

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, establishing safety. The description adds that column/table names are validated against the schema and safe from injection, providing useful behavioral context beyond the annotations. However, it does not elaborate on other behavioral aspects like error handling or performance.

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 three sentences, front-loaded with the core purpose. Every sentence adds value: purpose, convenience context, safety note and alternative. 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?

With rich annotations, a full output schema, and a simple use case, the description covers the essential aspects: purpose, safety, and alternative. It could mention the output format or that it returns aggregated data, but the output schema likely covers that. Overall it is complete for an AI agent to correctly select and invoke the tool.

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 input schema has 100% description coverage, so the schema fully documents each parameter. The description adds no additional parameter information, meaning it neither enhances nor detracts from the schema's explanations. Baseline of 3 is appropriate.

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 'Group a table by a column and compute an aggregate — no SQL required,' providing a specific verb and resource. It also implicitly distinguishes from siblings by indicating this is a convenience wrapper for simple aggregations, while 'analytics_run_query' is for more complex queries.

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 says 'A convenience workflow tool over the most common analytics pattern' and explicitly directs to 'analytics_run_query' for anything more complex, offering clear context and an alternative. It lacks explicit 'when not to use' cases but the guidance is sufficient for an AI agent.

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