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

Annotations already establish this as a read-only, closed-world computation, so the bar is lower. The description still earns credit by disclosing the shape of the result: both rectangular and round answers, seating counts for each, and a designer rule-of-thumb with sources linked, which is useful output context given there is no output schema.

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?

Two sentences, front-loaded with the actual computation, with no filler. The trailing note about the linked page showing sources is slightly tangential but short and informative about provenance.

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?

For a small three-parameter calculator with full schema coverage and read-only annotations, nothing essential is missing: it says what it computes and roughly what it returns. Only a note on units or on how clearance affects the answer beyond the schema would push it higher.

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%, and the schema already spells out units and the meaning of the clearance parameter including the 24/36/42 rule. The description adds no parameter-level detail beyond that, so 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?

The description states a specific computation: the largest rectangular and round dining table that fits a room, plus seating counts for each. That is concrete enough to distinguish it from sizing siblings like coffee_table_size or rug_size, though it never names a sibling or scopes itself explicitly.

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?

Use is implied rather than stated: you call it with room dimensions when you need the biggest table that still allows chair pull-out. There is no explicit when-to-use or when-not-to-use guidance, and no mention of how it relates to neighboring sizing tools.

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