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

Annotations already carry the safety profile (readOnlyHint=true, destructiveHint=false, idempotentHint=true), lowering the burden on the description. The description adds useful behavior ('evenly' distribution, per-team return), but it does not disclose that shuffling makes results non-deterministic across repeated calls, nor what happens with edge cases like fewer names than teams or uneven remainders. The idempotentHint on a shuffling tool is conceptually strained, though not directly contradicted.

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 tight sentences front-load the action and the return value with no wasted phrasing. The trailing source URL is provenance rather than operational guidance, so it is minor noise but not disqualifying.

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 simple two-parameter tool with fully-documented schema, safety annotations, and an output schema, the description covers the core purpose and return shape sufficiently for correct invocation. The only gaps are behavioral edge cases (odd counts, fewer names than teams) and explicit non-determinism disclosure, which are minor for this level of complexity.

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 both 'names' and 'teams' are already fully documented with types, ranges, and descriptions. The description's 'list of names' and 'set number of teams' merely echo the schema without adding new constraints such as unique names or a minimum name count relative to the number of teams. Baseline 3 is correct when the schema does the heavy lifting.

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 leads with specific verbs ('Shuffle' and 'deal them evenly') naming the resource ('a list of names') and the outcome ('into a set number of teams'). 'Returns each team's members' pins down the exact result shape. This clearly distinguishes it from sibling pickers like wheel_spinner or spin_the_bottle, which select one item rather than grouping names into multiple teams.

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 use case is implied by the description: an agent can infer this is for splitting a list of people into groups. However, there is no explicit when-to-use guidance, no exclusions, and no mention of related alternatives from the large sibling set (e.g., secret_santa_generator, wheel_spinner, random_word_generator). Applicability is left to inference rather than stated.

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