EU Trade Explorer

Get Subcontracting Members

get_subcontracting_members

Per-country sub-contracting intensity (PRODCOM): for each reporting country, the share of its sold production that is toll manufacturing -- which countries act as processing hubs vs. autonomous producers. Spans all DS-059358 reporters that report the own/sub split; others simply don't appear. Country cells are heavily confidentiality-suppressed (null, not zero, when absent).

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 of behavioral disclosure. It explicitly states that country cells are heavily confidentiality-suppressed and that missing values are null, not zero, and that reporters not reporting the split simply do not appear. This adds meaningful behavioral context beyond the basic 'get' semantics.

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 compact sentences with no wasted words. The first sentence states the core metric, the second clarifies the scope, and the third covers a key data quality behavior. Every sentence adds value.

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 covers the essential context: the metric itself, the universe of reporters, and the confidentiality suppression behavior. Since an output schema exists and the description is concise, it is complete enough for an agent to invoke appropriately. A minor enhancement could be more explicit linkage to the PRODCOM dataset, but it is already mentioned.

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 input schema already documents all parameters thoroughly. The tool description does not duplicate or enhance parameter explanations, but given the rich schema, the baseline of 3 is appropriate. No parameter semantics are lost.

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 defines the tool's output: per-country sub-contracting intensity, measured as the share of sold production that is toll manufacturing. It also differentiates from sibling tools by emphasizing the per-country, per-reporter perspective and the specific PRODCOM dataset, making it unmistakable what this tool does.

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 implies when to use the tool (when you need per-country sub-contracting intensity) and clarifies coverage (only reporters reporting the own/sub split appear). However, it does not explicitly mention alternative tools or provide concrete 'when not to use' guidance, so the usage direction is present but somewhat implicit.

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.

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