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Animal dose & injection volume / 动物给药量计算

animal_dose_volume
Read-only

Animal dose & injection volume / 动物给药量计算 | USE WHEN: compute the dose (mg) and injection volume (mL) for an animal from body weight and mg/kg | ALIASES: 动物给药量, 给药体积, 按体重给药, dose volume, mg/kg, 注射体积, 灌胃体积 | RETURNS: 给药量与体积

Input Schema

NameRequiredDescriptionDefault
dose_mg_per_kgYes剂量(mg/kg)
animal_weight_gYes动物体重(g)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.3/5.0
Behavior3/5

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. The description adds a 'RETURNS' line naming the outputs, which is useful given there is no output schema, but it omits the fact that an injection volume cannot be derived from weight and mg/kg alone without a concentration — a behaviorally significant omission.

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

Conciseness3/5

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

The single pipe-delimited line is compact and front-loads the title and use case. The bilingual ALIASES block is largely keyword padding that consumes space without helping an agent decide or call correctly.

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

Completeness3/5

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

For a two-parameter pure calculation with full schema coverage and annotations, the definition is close to sufficient, and the RETURNS line compensates for the missing output schema. The unresolved question of how volume is computed without a concentration input leaves a real gap in understanding the tool's actual behavior.

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% and both parameters carry units (g, mg/kg), so the baseline is 3. The description names the same two inputs but adds no meaning beyond the schema — notably it does not explain how injection volume is produced when no dose concentration parameter exists.

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 (compute dose in mg and injection volume in mL) plus the exact inputs (body weight, mg/kg), so an agent can tell it apart from generic stats or writing tools. However, it never differentiates from close siblings such as species_dose_convert or renal_dose_adjust, which handle adjacent dosing math.

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

Usage Guidelines3/5

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

The 'USE WHEN' clause gives a triggering condition, but it essentially restates the purpose (compute dose from weight and mg/kg) rather than contrasting with alternatives. There is no guidance on when NOT to use it or when species_dose_convert / renal_dose_adjust would be the correct pick.

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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