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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the agent knows this is a side-effect-free local generation. The description adds that output is 'ready-to-paste' text, which hints at the return format, but says nothing about how notices are structured per channel or language, or about legal caveats.

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?

A single dense sentence with the deliverable front-loaded and no filler. It is efficient, though the language enumeration is slightly redundant with the schema's enum.

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?

With no output schema, the description carries the burden of explaining what the agent gets back, and it only gestures at this with 'ready-to-paste notices'. It does not say whether the result is one notice or one per channel/language combination, nor whether it is structured text or JSON.

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 every parameter including defaults is already documented in the schema. The description echoes the channel set and language list without adding format or behavior detail beyond it, so the baseline 3 applies.

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?

States a specific verb (generate) and a specific resource (Article 50 AI disclosure notices), and scopes it precisely to chat, voice and AI-generated content in named languages. This is unmistakably distinct from the sibling tools classify_ai_system, estimate_ai_act_fine and list_ai_act_deadlines.

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 framing 'notices required by Article 50 of the EU AI Act' implies the compliance scenario in which the tool applies, but there is no explicit when-to-use statement, no prerequisites, and no reference to the sibling tools as alternatives. Usage must be inferred from the regulatory citation.

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