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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description adds 'no auth required' which is useful, and notes the data source. However, it doesn't disclose other behaviors like pagination, default scope (all states?), or result limits. Given strong annotation coverage, a 3 is appropriate.

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 no filler. The core function is front-loaded, followed by a brief use case and data source. Every word earns its place.

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 an output schema exists and parameters are well-documented, the description covers purpose, filters, use case, data provenance, and auth. It doesn't mention edge cases like empty results or state availability, but these are not critical for an agent to invoke it correctly.

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% and each parameter is richly documented (exact values, near-miss warnings). The description merely summarizes filters as 'optionally filtered by date range, product, or company' without adding new meaning. Baseline of 3 applies when schema carries the load.

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 states a specific verb ('Get'), a resource ('CFPB complaint database'), and the key output ('per-US-state consumer complaint counts' with top products/issues). This clearly distinguishes it from sibling tools like complaints.search (likely raw records) and complaints.trends (time series) by focusing on geographic aggregation.

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?

It provides a clear use case ('Useful for geographic analysis of consumer financial complaints') and mentions optional filters. It doesn't explicitly contrast with siblings, but the geographic scope inherently differentiates it from search and trends. A slight gap is the absence of 'when not to use' guidance, but the purpose is sufficiently distinct.

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