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

With no annotations provided, the description must disclose behavior on its own. It explicitly states that it 'Returns categories only, never actual PII values', which is a crucial privacy-preserving trait. It also enumerates detectable categories, adding behavioral insight beyond the parameter schema.

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 a single, well-structured sentence that front-loads the core purpose and immediately clarifies the key output constraint. Every phrase earns its place with no redundancy.

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 low-complexity tool with one parameter and no output schema, the description adequately covers what the tool does, what it detects, and what it returns (categories only). It could note edge cases like empty texts, but this is a minor gap given the simplicity.

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 schema covers 100% of the single parameter with a clear description ('Text to scan for PII categories'). The tool description adds no additional parameter-level detail, but the schema is sufficient, so the baseline of 3 is appropriate.

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 function: 'Detect GDPR PII categories in text' with specific examples of categories (email, phone, IP, name, location). This distinguishes it from sibling tools like detect_secrets, which focuses on secrets rather than PII categories.

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 implicitly conveys when to use this tool: whenever you need to identify types of personal data in text, without returning actual values. It does not explicitly name alternatives, but given the sibling list, no other tool performs a similar classification task, so clear context suffices.

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