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ons_select_search

Read-onlyIdempotent

Rank ONS datasets by relevance using explainable scoring, with prompts to clarify missing context for better results.

Instructions

Rank ONS datasets using a cached catalog with explainable scoring and elicitation prompts for missing context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNo
toolNo
limitNo
queryNo
intentTagsNo
relatedLimitNo
geographyLevelNo
includeRelatedNo
timeGranularityNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
candidatesYes
catalogMetaNo
candidateCountYes
relatedDatasetsNo
needsElicitationNo
elicitationQuestionsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.2

TDQS

B3.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, and the description adds meaningful behavioral context beyond these: use of a cached catalog, explainable scoring, and the ability to elicit prompts for missing context. This helps an agent anticipate how the tool will behave at call time, though more detail about response behavior is left to the output schema.

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

Conciseness5/5

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

The description is a single, front-loaded sentence that efficiently states the core action ('Rank ONS datasets') and then adds three informative behavioral qualifiers. Every phrase earns its place, and there is no redundant or filler content.

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?

The tool has 9 parameters, zero required, zero schema descriptions, and no parameter guidance in the tool description. While the output schema and annotations supply some safety and return-shape context, the description is not sufficient for an agent to know how to formulate a valid request, especially given the ambiguous q/query pairing and optional filtering parameters.

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 provides no explanation for the 9 parameters. There is no guidance distinguishing 'q' from 'query', nor explaining intentTags, relatedLimit, geographyLevel, or includeRelated. With this many parameters and no descriptions, the agent cannot infer correct parameter usage from the description.

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 names a specific action and resource: 'Rank ONS datasets'. It conveys the tool's purpose clearly and includes distinguishing features like 'cached catalog', 'explainable scoring', and 'elicitation prompts'. However, it does not explicitly contrast this tool with the closely related sibling ons_search_query or other ONS search tools, so it misses the full sibling-differentiation bar.

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?

The description gives context about how the tool operates (cached catalog, scoring, prompts) but does not state when to use this tool instead of alternatives. There is no mention of exclusions, complementary tools, or conditions that would select ons_select_search over ons_search_query or other search-like siblings.

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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