validate_tax_number

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool validates a tax number but doesn't describe behavioral traits such as what validation entails (e.g., format checks, database lookups), error handling, rate limits, or authentication needs. This leaves significant gaps for a tool that likely interacts with external systems or data.

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 appropriately sized and front-loaded, with the purpose stated first, followed by structured sections for args and returns. Each sentence adds value, such as the example for 'region_code,' but the 'Returns' section is vague ('Validation result') and could be more specific without sacrificing conciseness.

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 the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is partially complete. It covers the basic purpose and parameters but lacks details on validation behavior, error cases, and output format. Without annotations or output schema, more context on what 'Validation result' entails would improve completeness for effective agent use.

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%, so the description must compensate. It adds meaning by naming the parameters ('tax_number' and 'region_code') and providing an example for 'region_code' ('e.g., "BE" for Belgium'), which clarifies usage beyond the schema's basic types. However, it doesn't detail formats, constraints, or validation rules for 'tax_number,' leaving some semantics unclear.

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 clearly states the tool's purpose: 'Validate a tax number for a specific region.' It specifies the verb ('validate') and resource ('tax number'), and the regional scope distinguishes it from siblings like 'get_tax_report' or 'list_tax_settings.' However, it doesn't explicitly differentiate from all siblings, such as 'get_company_tax_statistics,' which might involve tax data but not validation.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid tax number format), exclusions, or comparisons to siblings like 'get_company_details' that might include tax information. Usage is implied only by the purpose, with no explicit context or alternatives stated.

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