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

Beyond the annotations, the description reveals concrete side effects: a lead and callback task are created in the dispatch queue, and an advisor usually calls back within 15 minutes. It also discloses the US-based AI processing detail, which is critical for consent handling and matches the tool's non-readonly 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 information-dense but efficient: the primary purpose is front-loaded, side effects and timing are stated in the first paragraph, and the consent prerequisite is given in the second. Every sentence earns its place and there is no filler.

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?

The tool has an output schema, so return-value details are not required. The description fully covers the essential context: what the tool does, when to use it, what side effects occur, the expected callback timeframe, and the mandatory consent condition. Nothing critical is missing.

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 input schema already covers 100% of parameters with descriptions, so the baseline is 3. The description adds extra semantic value by emphasizing that einwilligung_erteilt must be true, marking which fields are optional, and explaining that wunschzeit without a value means 'as soon as possible'.

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 states a specific action and resource: it requests a free callback from a Claimondo advisor and creates a lead plus callback task. It explicitly positions itself as the second funnel arm next to claimondo_melde_schaden, so the agent can distinguish it from the main sibling tool.

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 tells when to use this tool: when customers prefer being called, when no slot fits, or when data is missing. It also gives a firm precondition: only invoke with einwilligung_erteilt=true after the user has explicitly consented to data processing and phone contact, including the US AI service.

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