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Animal randomization / 动物随机分组

animal_randomization
Read-only

Animal randomization / 动物随机分组 | USE WHEN: randomly assign animals to groups as required by ARRIVE | ALIASES: 动物随机分组, animal randomization, 分组表, 动物分组 | RETURNS: 分组表

Input Schema

NameRequiredDescriptionDefault
seedNo种子
groupsNo分组名
methodNo随机化方法
n_totalYes动物总数

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description only adds that a group allocation table is returned ('RETURNS: 分组表'). It does not disclose whether the seed makes the allocation reproducible, what happens when seed is omitted, or what the default randomization method is — all material behavior for a randomization tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The pipe-delimited metadata block is compact and front-loads the trigger condition and aliases, which aids discovery across Chinese and English phrasings. The only waste is the opening segment repeating the tool name and title verbatim before reaching the useful 'USE WHEN' clause.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a small, single-purpose computation tool with 4 flat parameters, full schema coverage, and trusted read-only annotations, the definition covers purpose, trigger, aliases, and return artifact. The gaps — seed determinism and default method behavior — are behavioral niceties rather than blockers to a correct call.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3 and the schema does the documenting work. The description adds no meaning about n_total, groups, method, or seed — notably nothing about seed reproducibility or the default method — so it neither compensates nor detracts.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'randomly assign animals to groups,' qualified by 'as required by ARRIVE.' An agent can tell what the tool produces ('分组表', a group allocation table). It stops short of a 5 because it never distinguishes itself from the sibling randomization_allocate, which plausibly performs a similar allocation task.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'USE WHEN: randomly assign animals to groups as required by ARRIVE' clause gives a concrete trigger condition tied to a known reporting standard. There are no explicit exclusions and no mention of when to prefer randomization_allocate or animal_sample_size instead, so it falls short of a 5.

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

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