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Estonia Statistics Table Query

estonia-statistics.series.table_query
Read-onlyIdempotent

Run a statistical query against an Estonia statistics table — specify dimension filters to slice data by year and indicator. Returns JSON-stat2 format with labeled dimensions and numeric values. Call estonia-statistics.table_metadata first to discover valid dimension codes and value codes (often Estonian words, e.g. 'Aasta' for year). Example: births/deaths/natural increase (Näitaja='1','2','3'), most recent year (Aasta filter='top' values=['1']). Data: andmed.stat.ee, no auth required, CC BY-SA 4.0 (Statistics Estonia).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesArray of dimension filters. Each filter selects which values to include for one dimension. Example: [{code:'Aasta',selection:{filter:'top',values:['3']}}, {code:'Näitaja',selection:{filter:'item',values:['1','2','3']}}]. Response is JSON-stat2 format with dimension labels and numeric values array.
table_pathYesFull path to the leaf table to query — same as estonia-statistics.table_metadata table_path. Example: 'rahvastik/rahvastikunaitajad-ja-koosseis/demograafilised-pehinaitajad/RV030.PX'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/destructive/openWorld, so the safety profile is covered. The description adds meaningful context beyond them: the JSON-stat2 return format, that no auth is required, the data host, and the license — plus the metadata prerequisite. It does not discuss rate limits or error behavior, so it stops short of a 5.

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?

Front-loaded with purpose and return format, then the prerequisite, a concrete example, and provenance — every sentence carries information an agent needs. No filler or redundancy.

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?

With an output schema present, return values need not be spelled out, and the description still names JSON-stat2. The required-parameter prerequisite (table_metadata) is covered, and the code-format caveat (Estonian non-ASCII words) is surfaced. Nothing needed to invoke correctly is missing.

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

Parameters4/5

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

Schema description coverage is 100% and the nested query/filter/values semantics are already documented with examples in the schema, so the baseline is 3. The description adds a worked example combining two dimensions (Aasta with filter='top', Näitaja with item codes) and flags the Estonian-language codes, giving slightly more than the schema alone.

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?

States a specific verb (run a statistical query) against a specific resource (Estonia statistics table) and clarifies the scoping mechanism (dimension filters for year/indicator). An agent can distinguish it immediately from sibling estonia-statistics.reference.table_metadata (discovery) and estonia-statistics.reference.catalog.

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

Usage Guidelines5/5

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

Explicitly instructs to 'Call estonia-statistics.table_metadata first to discover valid dimension codes and value codes', naming the prerequisite tool and the reason for using it. This is a clear when-and-how routing rule with no inference required.

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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