Generate an AI agent disclosure (Article 50)

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

Annotations already cover readOnlyHint and destructiveHint, so the description adds real value by disclosing three behavioral traits: conformity to the Article 50 Guidelines, refusing rather than fabricating a principal, and operating offline. These go beyond what annotations or the schema express, though the description does not detail refusal output or error behavior.

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 compact and front-loaded: the first sentence states the core purpose, the second establishes regulatory provenance, and the final fragments add decisive behavioral constraints without filler. Every sentence earns its place, and no content unnecessarily duplicates schema fields.

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 detailed schema for all five parameters and annotations that establish a read-only, non-destructive profile, the description supplies enough contextual behavior for an agent to call the tool correctly. The main gap is the absence of an output schema combined with no explicit statement about what the returned disclosure artifact looks like, but for a drafting tool this is a modest omission.

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 100%, so the baseline is 3 even without additional parameter prose. The description loosely aligns with parameters via 'what it is, who it acts for, and limits of delegated authority,' but it does not add parameter-level detail beyond the schema, which already covers ask-the-user behavior and null handling.

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 identifies a specific verb ('Draft'), a precise regulated artifact ('Article 50(1) disclosure an AI agent owes'), and the three core content elements: what it is, who it acts for, and the limits of delegated authority. It is clearly not a tautology, and its legal specificity helps separate it from generic disclosure tools, though it does not explicitly contrast with the sibling 'generate_disclosure'.

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 clearly implies the intended scenario: use this when drafting an AI agent's Article 50(1) disclosure. It also communicates an important boundary through 'Refuses rather than inventing a principal.' However, it does not explicitly state when not to use the tool or how to choose between this and sibling tools such as 'generate_disclosure'.

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