cfpb_complaint_aggregations

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds the aggregation behavior — returning counts grouped by a field — but doesn't disclose response shape, group limits, or whether date filters apply to the aggregation. This is adequate but not rich.

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?

Two sentences, with the core behavior front-loaded in the first four words. Every sentence earns its place: the first states what it does, the second gives use cases and enumerates valid fields. No fluff.

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?

There is no output schema, so the description should help an agent predict the response shape, but it only says 'counts grouped by a field.' Missing details like sorting, limits, or exact result format are absent. It's adequate for a simple call, but an agent would be guessing at response structure.

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 100%, so the schema already documents all parameters and the field enum. The description mostly repeats the enum values and gives example use cases, adding little semantic information beyond what the schema provides. Baseline 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 the verb and resource: 'Get complaint counts grouped by a field,' and gives concrete examples of output (product, company, state, issue). It is distinct enough to understand, but it does not explicitly contrast itself with related siblings like cfpb_complaint_trends or cfpb_state_complaints, so it stops short of full differentiation.

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: 'useful for ranking companies by complaint volume, identifying top issues, or comparing states.' This tells an agent when the tool is appropriate, though it doesn't mention when not to use it or point to a preferred alternative.

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