Uk Ons

Get Dataset

get_dataset

Read-onlyIdempotent

Single dataset metadata: title, description, methodology, contacts, release frequency, latest version, related links.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`dataset_id`	Yes	ONS dataset ID (e.g., "cpih01", "ashe-table-1")

Output Schema

TableJSON Schema

Name	Required	Description
`id`	Yes	Dataset ID
`type`	Yes	Dataset type
`state`	Yes	Dataset state
`theme`	Yes	Theme category
`title`	Yes	Dataset title
`license`	Yes	License information
`contacts`	Yes	Contact information
`publisher`	Yes	Publisher name
`description`	Yes	Dataset description
`next_release`	Yes	Next release date
`latest_version_id`	Yes	ID of the latest version
`release_frequency`	Yes	Release frequency
`national_statistic`	Yes	Whether it is a national statistic

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedMay 24, 2026

addedInput schema / examples

Added value: +[
+  {
+    "dataset_id": "cpih01"
+  },
+  {
+    "dataset_id": "ashe-table-1"
+  }
+]

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "contacts": {
+      "description": "Contact information",
+      "items": {
+        "properties": {
+          "email": {
+            "description": "Contact email",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "name": {
+            "description": "Contact name",
+            "type": [
+              "string",
+              "null"
+            ]
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "description": {
+      "description": "Dataset description",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "id": {
+      "description": "Dataset ID",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "latest_version_id": {
+      "description": "ID of the latest version",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "license": {
+      "description": "License information",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "national_statistic": {
+      "description": "Whether it is a national statistic",
+      "type": [
+        "boolean",
+        "null"
+      ]
+    },
+    "next_release": {
+      "description": "Next release date",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "publisher": {
+      "description": "Publisher name",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "release_frequency": {
+      "description": "Release frequency",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "state": {
+      "description": "Dataset state",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "theme": {
+      "description": "Theme category",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "title": {
+      "description": "Dataset title",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "type": {
+      "description": "Dataset type",
+      "type": [
+        "string",
+        "null"
+      ]
+    }
+  },
+  "required": [
+    "id",
+    "title",
+    "description",
+    "theme",
+    "state",
+    "type",
+    "national_statistic",
+    "release_frequency",
+    "next_release",
+    "license",
+    "publisher",
+    "contacts",
+    "latest_version_id"
+  ],
+  "type": "object"
+}

First observedMay 13, 2026

TDQS

A3.9/5.0

Behavior3/5

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

Annotations already indicate readOnly, idempotent, and non-destructive behavior. The description adds context about the returned metadata fields but does not disclose additional behavioral traits beyond what annotations provide.

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 extremely concise, using a single sentence with no wasted words. It front-loads the key information about what the tool returns.

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

Completeness5/5

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

Given the tool's simplicity (1 parameter, output schema present), the description adequately covers the returned metadata fields. No further context is needed.

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?

The input schema has 100% documentation coverage for the single parameter dataset_id, including examples. The description does not add extra meaning beyond the schema, so it meets the baseline.

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

Purpose5/5

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

The description clearly states it returns 'Single dataset metadata' and lists specific attributes (title, description, methodology, etc.). It effectively distinguishes from sibling tools like list_datasets and ons_timeseries by focusing on a single dataset's metadata.

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 description does not provide explicit guidance on when to use this tool versus alternatives. It implies usage for obtaining metadata for a specific dataset but lacks exclusion criteria or mention of other tools for different needs.

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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