get_supported_entities

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns a JSON string with a list of supported entity types and descriptions, which adds useful context about the output format. However, it doesn't mention behavioral traits like error handling, rate limits, or authentication needs, leaving gaps for a tool with no annotation coverage.

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: it starts with the core purpose, followed by structured sections for Args and Returns. Every sentence earns its place by providing necessary information without redundancy, making it efficient and easy to parse.

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 low complexity (1 parameter, no annotations, but has an output schema), the description is fairly complete. It explains the purpose, parameter semantics, and return format. Since an output schema exists, it doesn't need to detail return values further. However, it could improve by addressing potential errors or usage scenarios relative to siblings.

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 description adds meaning beyond the input schema by specifying that the 'language' parameter is a language code with a default of 'en', which clarifies its purpose. Since there is only one parameter and schema description coverage is 0%, the description compensates well by providing essential semantics, though it could detail format constraints (e.g., ISO codes).

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: 'Get list of all supported PII entity types for a language.' It specifies the verb ('Get'), resource ('supported PII entity types'), and scope ('for a language'), which is specific and actionable. However, it doesn't explicitly distinguish this from sibling tools like 'analyze_text' or 'get_anonymization_operators', which might also involve entity types, so it misses full sibling differentiation.

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 implies usage by mentioning the language parameter and its default, suggesting it's for retrieving entity types based on language. However, it doesn't provide explicit guidance on when to use this tool versus alternatives (e.g., 'analyze_text' for detection or 'get_anonymization_operators' for operators). The context is clear but lacks exclusions or named alternatives.

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