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

Beyond the readOnlyHint/openWorldHint annotations, the description discloses the actual heuristics applied (length = 1/2 to 2/3 of sofa; height = 1-2 inches below seat) and that the answer includes a link to sources, which lets an agent sanity-check output. Minor tension: 'the page linked in the answer' implies an external URL even though openWorldHint is false — not a contradiction, since the tool isn't fetching, but worth noting.

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?

Three short sentences, front-loaded with the concrete rule of thumb, then the sourcing note. 'Gives the designer rule of thumb' is mildly redundant with the formulas that precede it, but the sentence still earns its place by framing the numbers as heuristics rather than hard requirements.

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, closed-form calculator with no output schema, the description covers what the tool computes and the rules behind it. It could state output units explicitly, but the input schema's 'in inches'/'in feet' descriptions make units inferable, so no critical gap remains.

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 100%, so a 3 is the baseline, but the description goes further by explaining the relationships among the parameters — that sofa length drives table length, seat height drives table height, and room width/length drive the width suggestion. This tells the agent which inputs actually matter for each output, which the flat schema does not.

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 names the specific quantities computed (coffee table length, height, and width) and the inputs that drive them (sofa, room). This is a specific verb+resource statement that an agent can distinguish from every sibling sizing tool (bar_stool_height, dining_table_size, rug_size, etc.) without opening the schema.

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?

Usage context is clear: it is for sizing a coffee table against a sofa and a room. No explicit exclusions or alternatives are given, but the sibling set is disjoint by furniture type, so there is little real ambiguity to resolve. Nothing states when this tool would be the wrong choice.

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