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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds 'Informational screening, not legal advice' – a useful caution that the results are non-authoritative and not legally binding. This adds value beyond annotations without contradicting them. However, it doesn't disclose return format, edge cases, or rate limits, so 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?

The description is one sentence, front-loaded with the core purpose, and includes a necessary disclaimer ('not legal advice'). It's concise, though the triple phrasing ('Company compliance API / regulatory applicability / compliance preflight') is slightly redundant. No filler or 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?

For a tool with 9 parameters and no schema descriptions, the description should explain what the tool does with those inputs. It only says 'regulatory applicability' and 'screening,' which is vague. There's no mention of output format (though output schema exists) or how parameters like 'uses_ai' or 'takes_card_payments' factor in. Annotations cover safety, so the gap is on usage scope and parameter behavior.

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 0%, and the description provides no explanation of how parameters like 'uses_ai', 'takes_card_payments', or 'processes_personal_data' influence the screening. The parameter names are self-explanatory for some (country, sector) but others (e.g., ai_use_cases) lack context. The description fails to compensate for the sparse schema.

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 the tool performs 'Company compliance API / regulatory applicability / compliance preflight' – a clear verb-resource combination. It distinguishes from sibling tools (which are specific checks like AI Act or VAT) by positioning this as a general screening. However, it doesn't explicitly name alternatives or contrast with them, so it's not a 5.

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?

No explicit guidance on when to use this vs. the more specific sibling tools (e.g., check_ai_act_applicability or screen_ofac). The phrase 'preflight' implies a first-pass screening, but there is no 'use this when...' or 'for specific regulations use...' context. This leaves the agent to infer applicability.

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