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Browse Eurostat Theme Hierarchy

eurostat_browse_themes
Read-onlyIdempotent

Navigate the Eurostat theme tree. Without theme_code returns the top-level theme folders (Economy, Population, Transport, etc.) — the practical starting points. With a theme_code returns its immediate children: subtheme folders and datasets in that branch. Use this for structured discovery when you know the domain but not the dataset code, or to drill down from a broad topic to a specific dataset. Pair with eurostat_search_datasets for keyword-based discovery.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
theme_codeNoFolder code to expand (e.g., "economy", "reg"). Omit to list the top-level theme folders.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
itemsNoImmediate children of the requested theme, or the root themes if theme_code was omitted.
nextStepNoSuggested next action based on these results. Populated when there is a clear follow-up call.
itemCountNoNumber of items returned in this level.
themeCodeNoFolder code that was browsed, or omitted for root.
parentPathNoBreadcrumb from root to the requested theme (e.g., ["Database by themes", "Economy and finance"]). Empty when browsing root.
otherPlacementsNoBreadcrumbs of the other branches that file this same theme_code. Eurostat lists a few folder codes in more than one branch; the items above come from the first one the catalogue lists, which never has fewer children than the branches named here but can list different ones. theme_code takes a bare code, so those branches cannot be addressed directly — browse down to them from the root instead. Omitted when the code has a single placement — the normal case.

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the safety profile is covered. The description adds useful behavioral context by detailing the no-argument top-level behavior and the with-argument child-listing behavior, including what kinds of children to expect (subtheme folders and datasets). It does not describe pagination or limits, but output schema exists and the core navigation behavior is clearly disclosed.

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 compact and well-structured: behavior first, then parameter semantics, then usage context. Every sentence earns its place, with no redundant restatement of the tool name or title.

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 single-optional-parameter tool with a high-coverage schema and an output schema, the description is complete: it explains both invocation modes, the expected return content, and how the tool fits into the broader discovery workflow. An agent has everything it needs to select and call this tool correctly.

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%, but the description adds value beyond the schema by explaining the practical consequence of omitting theme_code versus providing it, and gives illustrative examples ('economy', 'reg'). This helps an agent understand the parameter's role in tree navigation without needing to infer it from 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?

The description clearly states a specific action ('Navigate the Eurostat theme tree') and distinguishes the two modes of operation: without a code it returns top-level theme folders, with a code it returns immediate children. It also explicitly positions itself against the sibling keyword search tool, which prevents confusion with eurostat_search_datasets.

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?

The description gives explicit use cases: 'Use this for structured discovery when you know the domain but not the dataset code, or to drill down from a broad topic to a specific dataset.' It also names the complementary tool (eurostat_search_datasets) for keyword-based discovery, giving the agent clear routing guidance.

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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TDQS

A4.7/5.0
Disambiguation5/5

Each tool has a clearly distinct role: discovery, metadata lookup, dimension value lookup, inline query, bulk download, dataframe staging, and dataframe SQL. The two data-fetching tools are explicitly differentiated as slice vs. whole-dataset routes, and the dataframe tools are clearly separate from direct Eurostat queries.

Naming Consistency4/5

Six of eight tools follow a consistent eurostat_verb_noun pattern, e.g., search_datasets, get_dataset_info, query_dataset. The two dataframe tools invert this to eurostat_dataframe_describe and eurostat_dataframe_query, which is a minor deviation but still readable and predictable.

Tool Count5/5

Eight tools is a well-scoped count for the Eurostat data-access domain. Each tool covers a distinct stage in the workflow from discovery, metadata inspection, targeted querying, bulk download, and post-query analysis.

Completeness5/5

The toolset covers the full expected lifecycle: browse and search to find datasets, get metadata and dimension values to construct queries, query or download data, and stage/query results for further analysis. No significant dead ends or missing operations are evident for the stated purpose.