get_ai_interaction_disclosure

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

With no annotations, the description carries the full burden. It discloses that the tool returns a dictionary with disclosure text and metadata, and gives an example. However, it does not elaborate on error behavior, required permissions, or any limitations, leaving some ambiguity typical for a simple getter.

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 well-structured with a clear opening, an example, and a compact args list. Every sentence adds value, and the example clarifies usage without verbosity.

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 presence of an output schema and the tool's simple nature, the description adequately covers purpose, parameters, and return format. It does not detail metadata fields, but the output schema exists and the example suffices for a low-complexity tool.

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 has 0% description coverage, but the description compensates by listing valid language codes (en, es, fr, de, it) and styles (simple, detailed, voice), plus defaults. This adds meaningful guidance beyond the raw schema properties.

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: 'Get AI interaction disclosure text for EU AI Act Article 50(1) compliance.' It specifies the resource (disclosure text) and the verb (get), and distinguishes it from siblings by focusing on AI interaction rather than deepfakes or watermarking.

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 clear context for when to use the tool: 'MUST be shown to users when they interact with an AI system.' It does not explicitly name alternative tools, but the compliance context and the distinct purpose among siblings imply when it applies.

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