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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so safety is covered structurally. The description adds meaningful behavior beyond that: the output is an allocation result table and reproducibility depends on fixing the seed. It stops short of describing the table's columns or row count.

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 pipe-delimited layout is front-loaded: purpose, then use condition, then aliases, then return value. The long alias list (many near-duplicate Chinese and English keyword variants) is bulk that serves discoverability rather than comprehension, but the rest is tight.

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?

With five parameters, no output schema, and a required groups/n_subjects pair, the description supplies the essential context: which designs exist, that a seed makes output reproducible, and that the result is an allocation table. A brief note on how minimization and stratified differ in required inputs would close the remaining gap.

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 all five parameters including the method variants and block_size are already documented. The description reinforces the seed-as-reproducibility-control idea and mirrors the method list, but adds no syntax or constraint detail the schema lacks. 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 names a concrete verb and resource ('produce a reproducible randomization list') and enumerates the four supported designs (simple, block, stratified, minimization), so the agent knows exactly what the tool generates. It does not explicitly differentiate itself from the nearby sibling animal_randomization, which keeps it from a 5.

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 WHEN' clause gives a clear triggering condition (need a reproducible allocation list with a fixed seed), which is strong guidance. However, it names no exclusions and no alternative sibling (e.g. animal_randomization or the sample-size tools) that an agent should prefer in other situations.

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