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get_trade_flows

UN Comtrade annual export volumes by country and HS code for semiconductor-critical materials.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNolimit (default 100, max 500)
offsetNooffset (default 0)
periodNoYear, e.g. "2022".
hs_codeNoHS-6 commodity code, e.g. 280491 for gallium.
materialNoMaterial name (synonym-expanded), e.g. Gallium, Cobalt, Lithium.
reporterNoExporting country name (partial match), e.g. China, Chile, Germany.
min_valueNoMinimum trade value in USD.

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations provided, the description partially carries the transparency burden. It discloses the data source (UN Comtrade), time granularity (annual), metric (export volumes), and dimensions (country, HS code, material). However, it does not mention output format, pagination defaults, ordering, or any limitations, which is a notable gap for a data-query tool.

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 a single, tightly written sentence that front-loads the key information (UN Comtrade annual export volumes) and states the filtering dimensions concisely. Every word contributes to the meaning, with zero filler.

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

Completeness2/5

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

Given the tool has 7 parameters, no output schema, and no annotations, the one-line description is insufficiently complete. It does not describe return values, result structure, or common usage patterns. Users are left to guess what the API actually returns and how to handle the parameters effectively.

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 adds limited semantic weight beyond the schema—it groups the parameters under 'semiconductor-critical materials' but does not explain how parameters interact (e.g., material vs hs_code). Thus, no significant additional meaning is provided.

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 identifies the tool as retrieving UN Comtrade annual export volumes, filtered by country and HS code, specifically for semiconductor-critical materials. This is a specific verb+resource+scope that distinguishes it from sibling tools focused on funding, mineral deposits, regulations, restricted entities, and SEC filings.

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

Usage Guidelines2/5

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

The description provides no explicit guidance on when to use this tool versus alternatives. It states the tool's function but does not offer exclusions, prerequisites, or comparisons to sibling tools. Users must infer usage solely from the purpose statement.

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

Each tool targets a distinct data source (funding, trade, minerals, regulations, entities, filings), and the descriptions clarify their unique purposes. However, search_regulatory_signals and search_restricted_entities have conceptual overlap around compliance/restrictions, so an agent could occasionally confuse them without careful reading.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (get_quantum_funding, get_trade_flows, search_*). The use of 'get' versus 'search' is a meaningful distinction between direct retrieval and query-based lookup, so the naming remains uniform and clear.

Tool Count5/5

Six tools is well within the ideal range for a specialized data server. Each tool covers a distinct aspect of semiconductor supply chain data without redundancy, making the count feel appropriately scoped and manageable.

Completeness4/5

The set covers upstream resources, trade, regulatory signals, entity screening, and market intelligence, which is strong for the domain. The main gap is that get_quantum_funding is specific to quantum technology rather than the broader semiconductor space, leaving general funding data unaddressed.

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