aggregate_export

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

Despite no annotations, description discloses return order and output naming convention. However, it omits potential side effects, performance implications, or constraints (e.g., file size limits).

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?

Three concise sentences front-loaded with core action, no redundant text. Essential details packed without waste.

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's complexity (aggregation with grouping and measures) and presence of output schema, description covers key aspects: measure definition, ordering, and use-case differentiation. No critical gaps apparent.

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?

With 0% schema description coverage, the description adds crucial detail: measures structure (column, op, optional alias) and default output key pattern. Does not explain file_path format or group_by semantics, but compensates well for schema gaps.

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?

Description clearly states it groups rows and computes aggregations per group, listing supported operations (sum, count, avg, min, max) and alias behavior. It explicitly distinguishes from sibling tool query_export, making purpose 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?

Explicitly advises to use this tool instead of query_export when summary statistics are needed. Provides context on return order (first-seen) and output key defaults, enabling correct tool selection.

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