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

Annotations cover safety (readOnly, idempotent, non-destructive), and the description goes well beyond them with a real behavioral disclosure: it reads the county's records directly, so very large counties are sampled rather than fully ranked, and the response flags that. It also previews the returned fields (LEI, originations, denials, dollar volume). This is exactly the kind of beyond-annotation context that matters for a bounded read.

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 sentences, front-loaded with the ranking scope, then the return shape, then the sampling caveat. Every sentence carries content, though the final bounded-behavior sentence is dense and could be tightened.

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 no output schema and full annotation coverage, the description fills the remaining gaps: it describes the return payload, the ranking basis, and the sampling limitation for large counties. Nothing an agent needs to invoke or interpret this tool is missing.

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 year, limit, action, and county are already fully documented in the schema. The description only echoes the ranking dimension (loan count, denials) without adding format or constraint detail beyond what the schema states, so the baseline 3 applies.

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+resource+scope: lenders ranked by loan count, drawn from HMDA county-year records. An agent can tell this is a county-scoped lender ranking rather than raw records or a lender-wide view. It stops short of naming the sibling tools it overlaps with (hmda_lender_activity, hmda_geography_activity, hmda_loan_records), leaving that differentiation to inference.

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?

Concrete usage contexts are given: the tool answers "who lends here" and "who denies most here" for a place, which tells the agent when it applies. There are no explicit exclusions or named alternatives, so the agent must reason about sibling choice on its own.

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