Spain Open Data

Market size in euros

market_size

Read-onlyIdempotent

Size the yearly market for a business category in a place in Spain, in euros, with a range.

Market = households × INE household spending on the category × an income adjustment.
Supply = competing businesses, calibrated against INE's company directory. Returns market
per business and an opportunity score: market per business against the region (1.0 = same as
the region), not a forecast of openings. Every assumption is listed. Assumptions can be overridden to test scenarios. Use for "how big
is the market for X in Y" and "is Y under-served for X".

Input Schema

TableJSON Schema

Name	Required	Description
`place`	Yes	Place name or INE code: municipality ('Valladolid' or '47186'), province ('41'; a bare name like 'Sevilla' means the city), autonomous community ('Cataluña' or 'CA09'), district ('4718603') or census tract ('4718603012'). 'Name, Province' picks between same-named towns.
`category`	Yes	Business category: restaurant, cafe, bar, fast_food, bakery, butcher, greengrocer, supermarket, pharmacy, optician, dentist, physiotherapy, hairdresser, beauty_salon, veterinary, gym, childcare, private_school, clothes, home. Plain words work too ('gyms', 'peluquerías').
`competitors`	No	Override the estimated number of competing businesses.
`capture_share`	No	Share of the market one business could win (0-1), to estimate obtainable revenue.
`spend_per_household`	No	Override INE's yearly spend per household on the category, in euros.

Output Schema

TableJSON Schema

Name	Required	Description
`data`	Yes
`checks`	No
`sources`	Yes
`confidence`	Yes	Lowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 17, 2026

TDQS

A4.6/5.0

Behavior5/5

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

With annotations covering safety (readOnly, idempotent, non-destructive), the description goes far beyond by disclosing the computation model (households × INE spend × income adjustment; supply calibrated against the INE directory), the return contract (market per business plus an opportunity score relative to the region), and an explicit non-goal ('not a forecast of openings'). It also notes assumptions are listed and overridable.

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

Conciseness4/5

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

Front-loaded with the core purpose and units, then method, returns, and usage, with every sentence carrying information. Minor redundancy in stating assumptions are listed and then again overridable, and the formula clauses are terse, but nothing extraneous.

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?

For a 5-parameter analytical tool with an output schema and full annotation coverage, the description supplies the missing pieces an agent needs: units (euros), geographic granularity, methodology, the meaning of the opportunity score, and the override-for-scenarios affordance. Nothing essential is omitted.

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 coverage is 100%, so the baseline is 3, but the description adds purpose-level meaning to the optional parameters: they exist so 'assumptions can be overridden to test scenarios'. It does not add per-parameter syntax (e.g. valid ranges for capture_share), so it is not a full 5.

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 and resource ('Size the yearly market for a business category in a place in Spain, in euros, with a range'), naming the units and geographic scope. This is clearly distinguishable from siblings like businesses, catchment, or income, which compute different quantities.

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

Usage Guidelines4/5

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

Explicitly gives the triggering questions: 'how big is the market for X in Y' and 'is Y under-served for X'. It provides clear positive context but no exclusions or naming of an alternative sibling (e.g. when to use income or businesses instead).

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

All Spain Open Data tools Inspect

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