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

The description adds substantial behavioral context beyond the annotations: it identifies the underlying data source (CBP monthly use-of-force and assault files, FY2021 onward), explains the return content (yearly or monthly figures for incidents, force types, officers/agents using force, assaults), clarifies counting semantics (officers counted per incident, not unique people injured), notes that the current fiscal year is labeled partial, explicitly states that no rates or causation are provided, and describes non-match behavior. This is rich, transparent disclosure.

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 front-loaded with purpose and scope, then moves through return content, counting semantics, and limitations. It is dense but mostly earns its length given the complexity. Some phrases (e.g., repeating that an area is 'never a city or an operation') could be trimmed, but overall it is well-structured.

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, the description does a good job explaining the content of the return (yearly or monthly figures, incident counts, force types, etc.). It could be more explicit about the response structure (e.g., list of matching areas with nested data), but for an agent selecting and invoking the tool, the description covers the essential context, including data provenance and limitations.

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 three parameters thoroughly. The description repeats the key semantics (area as a sector/field-office substring, fiscal_year behavior) but adds little beyond what the schema provides. Baseline 3 is appropriate when the schema does the heavy lifting.

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 and resource: 'Look up a CBP area of responsibility in the Border Force Register... by sector or field-office name substring.' It is clear what the tool does. However, it does not mention the sibling tool border_force_national, so an agent cannot tell from the description alone how this differs from the national-level lookup.

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?

Usage is implied: you need a sector or field-office name substring, and the area must be a CBP office area, not a city or operation. But there is no explicit statement of when to use this versus border_force_national, nor any when-not guidance. The agent must infer the appropriate context.

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