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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered, and the description adds genuinely new context: what comes back (a computed answer) and the important fork that interactive tools (timers, QR codes, live weather) return inputs plus a link rather than a value. This explains the idempotentHint=false annotation without contradicting it. It stops short of noting auth requirements or rate limits, so not a 5.

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 use case is front-loaded in the first clause, and the routing and exclusion rules are placed at the end where they belong. The long enumeration of conversion categories ('length, weight, volume, area, speed, data size, energy, pressure, and more') is slightly padded but does convey coverage breadth, so only a minor deduction.

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 dispatcher tool with a nested, open-ended inputs object and an output schema that already documents return values, the description supplies everything an agent needs: how to obtain the tool id, how to shape inputs, what the call returns, and when not to call it. Nothing material 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?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning about the nested 'inputs' object: converters use {value, from, to} with the unit names reported by find_tools, and it gives concrete shapes for loan, bmi, tip, and age (including the 'YYYY-MM-DD' date format). This is partially duplicative of the schema but usefully reinforces how to populate an open-ended additionalProperties object.

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?

States a specific verb and resource ('Run a built-in tool') and immediately scopes it by enumerating the families it covers (unit conversion, loan payment, BMI, tip, discount, sales tax, percentage, temperature, age). It also distinguishes itself from the sibling 'find_tools', which is the discovery step rather than the execution step.

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?

Explicitly routes the agent: 'Call find_tools first if you do not know the tool id' names the alternative and the condition that selects it. It also gives a clear negative case — 'Do not use for general maths you can do yourself, or for anything that is not a built-in tool' — which is exactly the boundary an agent needs to avoid misrouting arithmetic.

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