aggregate_crawl_data

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

Discloses that the tool returns total row count and per-value counts with percentages when group_by is set. Annotations indicate readOnlyHint=true, which matches the non-destructive aggregation behavior. No contradictions.

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 concise with a single summary sentence, a usage sentence, and a clear bulleted list of parameters. Every sentence adds value without 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?

Given the tool has 7 parameters, an output schema, and a clear sibling context, the description covers all necessary aspects: purpose, usage guidance, parameter details, and return format. No gaps remain.

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?

Despite 0% schema description coverage, the description provides a detailed Args section explaining every parameter: export_id, file, group_by, top, filter_column, filter_value, filter_mode, including defaults and the three modes for filter_mode. This fully compensates for the schema gap.

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 aggregates CSV data from an export, providing row counts and group-by breakdowns. It uses a specific verb (aggregate) and resource (CSV data from export), and distinguishes it from read_crawl_data which returns raw rows.

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?

Explicitly says 'Use instead of read_crawl_data when the question needs counts or a distribution', giving clear guidance on when to choose this tool over its sibling.

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