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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is fully covered. The description adds only the return range ('percentile 0-100'), which is redundant given the output schema exists, and it mischaracterizes the input shape instead of disclosing 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?

Three short, front-loaded sentences with no filler; the purpose leads and the return value follows. The only deduction is that one of those compact sentences conveys incorrect information, which is a solidity rather than a length problem.

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 output schema removes any obligation to explain the return value, and the annotations cover safety, so the core is present. However, for a 3-required-parameter numeric tool with closed properties, the description's inaccurate input summary leaves the agent reliant on the schema and at risk of a malformed call.

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%, so the baseline would be 3, but the description actively contradicts the schema: it says the inputs are 'value, dataset (list of numbers)' whereas the actual required parameters are value, values_below, and total_values (counts, not a list). Since additionalProperties is false, an agent following the prose would likely construct a failing call.

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 ('Compute the percentile rank of a value within a dataset'), which is clearly distinguishable from the hundreds of other calculate_* siblings. It loses a point because the scope it describes (a dataset list) does not match how the tool actually takes input, so the agent's mental model of the operation is slightly off.

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 for benchmarking scores or salaries' gives a use-case context but no when-not guidance and no real alternatives; the 'See list_bundles for related math calculators' pointer is a weak cross-reference rather than routing logic. Usage is implied rather than specified.

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