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

With no annotations provided, the description carries the burden of disclosing behavioral traits. It conveys that the tool is a preliminary, read-only-style analysis ('before you act') and specifies the output concept (which regimes bind). It does not explicitly state side effects or return format, but for a compliance check tool, the implication of non-mutating behavior is clear enough. It adds context beyond simple verb repetition.

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 two sentences, front-loaded with the core action ('find out which regimes bind you') and immediately provides the scope and alternative. Every sentence earns its place with no redundant information, making it highly concise and 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?

The description covers purpose, timing, and scope, but lacks detail on parameter semantics and output format. With no output schema and five parameters, the description should ideally mention what kind of result to expect (e.g., a list of applicable laws) and how the parameters influence the check. It is minimally adequate but has clear gaps in completeness.

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?

The input schema has 0% coverage (no parameter descriptions), so the description must compensate for the five parameters. It only vaguely references a 'processing profile' without mapping that to processing_purpose, data_categories, ai_decisions, counterparty_types, or has_revenue_threshold. This leaves the agent without guidance on how to populate these fields, a significant gap.

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 uses a specific verb ('find out') and clearly identifies the resource (US federal sectoral regimes) and scope (US law). It distinguishes itself from the sibling india_sectoral_check by explicitly stating the US scope and naming the counterpart for India, making its 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?

The description provides explicit timing guidance ('Before you process personal data under US law') and a clear alternative ('for Indian sectoral regulators use india_sectoral_check'). This tells the agent exactly when to use this tool and contrasts it with the sibling tool, satisfying the 'when-to-use' requirement.

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