EU Trade Explorer

Get Subcontracting

get_subcontracting

EU27 sub-contracting intensity: the share of sold production that is toll (sub-contracted) manufacturing rather than own-account output. Returns intensity (%) across value/quantity, its component series, per-period data-quality status, resolved PRODCOM codes and availability notes. The own/sub split only exists from 2021 onward.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`query`	Yes	The product/reporter/partner-set/period/frequency slice to query -- the same request body every tradedashboard.eu analytical endpoint takes. See its own field descriptions (product, reporter, partner_set, period_start, period_end, frequency, n_top, ...) for details; only `product` is required, everything else has a sensible default.
`compact`	No	If true, condense long numeric time series (more than ~6 points -- typically monthly/quarterly windows or wide multi-partner/multi-period breakdowns) into summary statistics (first, last, min, max, mean, pct_change) instead of returning every data point. Leave false for full-fidelity series (e.g. to actually plot a chart); set true when you just need the headline trend and want to save context.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4/5.0

Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the return components (intensity, component series, quality status, PRODCOM codes, notes) and the key data limitation that the own/sub split only exists from 2021 onward. This is meaningful behavioral context, though it does not cover auth, rate limits, or side effects (which are likely minimal).

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 three concise sentences, front-loaded with the metric definition and followed by return components and a caveat. Every sentence adds value with no redundant filler.

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

Completeness4/5

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

The description effectively explains what the tool measures, what it returns, and an important temporal constraint (2021 onward). Given that an output schema exists, it does not need to detail return structures. This is complete for a specialized data-query tool, though it could briefly mention how to invoke it (e.g., that it uses the standard query object).

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?

Schema description coverage is 100%, so the baseline is 3. The tool description does not add parameter-specific meaning; it only mentions PRODCOM codes as an output, not as an input. The schema itself thoroughly documents the query object and compact parameter, so the description does not need to compensate.

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 the tool returns EU27 sub-contracting intensity, its components (value/quantity, quality status, PRODCOM codes, availability notes), and distinguishes it from siblings by its unique metric. The verb 'returns' and the specific resource make the purpose unambiguous.

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?

Usage is implied: use this tool when you need sub-contracting intensity data. However, there is no explicit mention of when to use it over alternatives like get_subcontracting_members, nor any exclusions. The description offers no direct guidance on choosing between similar tools.

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

A3.8/5.0

Disambiguation4/5

Most tools have clearly distinct purposes, but several concentration-related tools (get_concentration, get_concentration_compare, get_concentration_map) and volatility-related tools (get_volatility, get_volatility_summary) could be confused without careful reading. The detailed descriptions help, but the boundaries are not always immediately obvious.

Naming Consistency4/5

The vast majority of tools follow a consistent get_ prefix pattern for data retrieval. A few exceptions (guidelines_for_a_*, resolve_product_code, search_codes, validate_code) deviate to signal different kinds of operations, which is sensible but breaks uniformity.

Tool Count2/5

With 37 tools, the server is heavily overloaded. Many tools are variations on the same analytical theme (e.g., multiple concentration and production tools) and could be consolidated or parameterized. This creates a steep learning curve and increases the chance of selecting the wrong tool.

Completeness5/5

The tool set comprehensively covers the trade-exploration workflow: product code resolution, hierarchical browsing, headline stats, partner/reporter detail, concentration, volatility, shocks, production metrics, and report generation. There are no obvious gaps or dead ends for its stated purpose.

Resources

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