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

Annotations already declare readOnlyHint=true, and the description adds that it returns a breakdown by component and total, all in euros. This gives a clear picture of the output without an output schema, going beyond the annotation.

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, front-loaded sentence packs all necessary information: what it does, for what inputs, and what it returns. No wasted words.

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 two params, a read-only annotation, and no output schema, the description covers the purpose, inputs, and output breakdown. It doesn't mention potential errors or prerequisites, but for a calculation tool this is acceptable and complete enough.

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 coverage is 0%, so the description must compensate. It mentions 'property' and 'year' in natural language, mapping to property_id and year, but doesn't explicitly define each parameter or their formats. It provides enough semantic context but could be more explicit.

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 computes LMNP depreciation for a property and year, and specifies the output components (building, works, furniture, total). This distinguishes it from sibling compute tools like compute_tva, compute_loan_schedule, and compare_micro_bic.

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: use for a given property and year. While it doesn't explicitly mention alternatives or when-not to use, the tool name and description make its use case unambiguous among the siblings.

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