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Glama

get_transport_requirement

Retrieve transport requirements for a specified disease, clarifying CDC specimen collection and submission guidance. Results use synthetic data, not for actual use.

Instructions

CDC compatibility alias. decision_support_only=true; verify_current_official_source=true; not_validated_for_hospital_deployment=true; not_pre_submission_storage=true. 不得輸入病人資料。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
diseaseYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYes
limitYes
notesYes
queryYes
offsetYes
safetyYes
warningsYes
data_modeYes
operationYes
truncatedYes
provenanceYes
sample_onlyYes
availabilityYes
result_statusYes
source_statusYes
total_matchesYes
returned_countYes
coverage_detailYes
coverage_statusYes
evaluated_as_ofYes
contract_versionNopublic-contract-v1
evaluated_timezoneYes
snapshot_traceableYes
replacement_operationYes
availability_reason_codeYes
historical_truth_supportedYes
currently_reproducible_from_upstreamYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

D1.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It offers metadata flags like 'decision_support_only=true' and 'not_validated_for_hospital_deployment=true', which hint at constraints, but it does not describe what the tool does, what it returns, or what side effects or permissions apply.

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

Conciseness2/5

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

The description is short but poorly structured: the '=true' flags read like serialized metadata rather than coherent guidance, and the Chinese privacy warning is appended without context. It is not overly long, but the limited space is spent on opaque flags instead of useful tool semantics.

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

Completeness2/5

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

Even with only one parameter and an output schema, the description omits the core purpose and input semantics, leaving an agent unable to confidently decide whether this is the correct tool among many similar sibling tools. The constraint flags add some context but do not make the definition complete.

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

Parameters1/5

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

Schema description coverage is 0%, and the description does not mention the 'disease' parameter at all. The agent must rely solely on the parameter name, with no information about accepted values, format, or expected input.

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

Purpose2/5

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

The description never states that this tool retrieves transport requirements for a disease; 'CDC compatibility alias' is an opaque label that does not explain the tool's function. It relies on the tool name for meaning and lacks a clear verb and resource description.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus siblings like get_specimen_requirement or get_collection_method. The Chinese instruction '不得輸入病人資料' ('do not input patient data') is a constraint, not a usage scenario, and no alternatives or exclusion conditions are mentioned.

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