Fromerica U.S. Trade Data

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

Annotations indicate readOnlyHint=true, so the safety profile is already covered. The description adds valuable fallback behavior: when no company is listed, it returns a link for posting a free request for quote visible to matching suppliers, which is not inferable from annotations or schema.

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

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

Two sentences with no redundancy. The primary action is front-loaded, and the conditional fallback behavior is stated efficiently in the second sentence.

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

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

For a one-parameter search tool with read-only annotations and no output schema, the description is complete: it explains the core search and the fallback link behavior. An agent can correctly invoke this tool and set proper expectations for both outcomes.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already fully documents the single 'product' parameter with a description and example. The tool description does not add further parameter-level detail, so it meets the baseline for high schema coverage without adding extra semantic value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches the Fromerica directory of U.S. manufacturers and exporters by product, using a specific verb and resource. It also distinguishes itself from sibling tools that focus on markets, state-level exports, tariffs, restricted parties, and FMC licenses.

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

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

The description provides clear context: this is the tool to use when an importer wants to search for U.S. exporters by product. It does not explicitly name alternative tools or state when not to use it, but the distinct purpose is evident from the directive directory search.

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

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

Annotations already declare the tool read-only, so the description doesn't need to repeat that. It adds behavioral context by specifying the exact data points returned (total exports, top countries, year-to-date change, states) and the authoritative Census source. It doesn't discuss pagination or data freshness, but with readOnlyHint covering safety, this is sufficient.

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

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

A single, well-organized sentence front-loads the authoritative scope ('Official U.S. Census Bureau statistics for one product at the HS 4-digit level') followed by a colon and a compact list of precisely what the tool returns. Every phrase earns its place.

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

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

For a one-parameter read-only tool without an output schema, the description gives an agent enough information to decide and invoke: it names the required input type, the scope, and the output components. The only minor gap is the unspecified number of 'top' destinations and the exact time window for 'year-to-date', but these are unlikely to block correct usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter, hs4, is fully documented in the schema with examples. The description reinforces that the tool works for one product at the HS 4-digit level, but adds no new meaning beyond the schema, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool's function: it provides official U.S. Census Bureau statistics for a single HS 4-digit product, including total exports, top destination countries with year-to-date change, and top shipping states. This precise breakdown distinguishes it from sibling tools like find_us_exporters or get_us_exports_by_state.

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

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

The description implies when to use it—when a product-level view of export markets is needed—but it does not explicitly mention alternatives or state when not to use it. The overlap with get_us_exports_by_state (which also touches state export data) is not addressed, leaving some ambiguity.

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

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

Annotations already declare readOnlyHint=true, so the description need not repeat that. It adds value by specifying the data scope (origin of movement) and the specific statistics returned, which is useful behavioral context beyond the annotation.

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

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

The description is a single, well-structured sentence that front-loads the purpose ('Official U.S. Census Bureau export statistics') and then enumerates the output details without waste. Every part earns its place.

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

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

For a simple tool with one parameter and no output schema, the description is complete. It covers what data is returned, the geographic scope, and the data source, leaving no critical gaps for an agent to know how to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for the single 'state' parameter, so the schema already explains the format. The description does not add extra semantic detail beyond what the schema provides, aligning with the baseline of 3 for high coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns official U.S. Census Bureau export statistics for a specific state or territory, listing the exact contents (totals, rank, top destinations/products). This distinguishes it from siblings like get_us_export_markets, which likely cover different angles.

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

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

The description implies usage for state-level export data but does not explicitly mention alternatives or when not to use this tool. There is no comparison to siblings such as get_us_export_markets or find_us_exporters, leaving the agent to infer based on the name.

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

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds value by revealing additional behaviors: it checks the official schedule, includes chapter 99 provisions, and notes that export figures are 'when available', which is useful context beyond the annotations.

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

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

The description is a single, information-dense sentence that front-loads the primary deliverable (duty rates). It includes multiple details compactly without redundancy, though it could be broken into clearer clauses. Overall, it is efficient.

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

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

The tool has only one parameter, the schema fully describes it, and annotations cover the read-only nature. The description explains most return values (duty rates, description path, last-checked date, notes, export figures). It might not specify exact structure or pagination, but with full schema coverage, missing details are minor.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides 100% coverage, including a detailed description of hts_code with the expected format and examples. The tool description does not add new parameter-level semantics, so a baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves official U.S. import duty rates for a single HTS code, listing the specific data fields (duty rates, description path, last-checked date, chapter 99 notes, export figures). It distinguishes itself from the sibling search_us_tariffs by focusing on one HTS code rather than searching.

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

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

The description implies it is for a single, specific HTS code while search_us_tariffs is for searching, providing implicit usage context. It does not explicitly state when NOT to use it (e.g., for multiple codes), but the singular focus is clear.

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

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

Annotations mark it read-only, and the description adds meaningful behavior: the list is refreshed daily, results are 'possible matches' with source list and match strength, and a match is not a legal determination. This gives an agent realistic expectations about output and limitations without contradicting the annotations.

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

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

The description is three short sentences, with the core action front-loaded and each sentence earning its place: source list and freshness, output shape, and a legal-use caveat. There is no filler or redundant information.

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

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

For a one-parameter, read-only screening tool with no output schema, the description tells the agent what input to provide and what output to expect ('possible matches with their source list and match strength'). Nothing essential for correctly invoking the tool is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter, 'name', is fully described in the schema ('Company or person name to check'), and the tool description repeats that same concept. Since schema coverage is 100%, the baseline applies; the description adds no additional syntax, formatting, or edge-case guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Check ... name') against a specific resource ('U.S. Consolidated Screening List ... Commerce, State and Treasury: OFAC SDN, BIS Entity List and others'). This clearly distinguishes it from the sibling trade/export and license-verification tools.

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

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

The description makes the use case obvious: screen a company or person name against U.S. restricted-party lists. It does not explicitly name alternatives or say when not to use it, but the context is unambiguous and none of the siblings overlap with this function.

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

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

Annotations already establish read-only behavior, so the description adds value by disclosing the daily refresh of data, the 20-result cap, and the specific output fields (general, special, and column 2 duty rates) plus links. This gives an agent a clear picture of what to expect beyond the annotation metadata.

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

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

The description is two sentences, front-loaded with the action and scope, followed by output details. It contains no redundant phrases and every clause contributes to understanding the tool's behavior.

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

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

With only one required parameter, no output schema, and annotations covering the read-only safety profile, the description sufficiently describes the return payload, result limit, and data source freshness. An agent has all the information needed to invoke and interpret the result correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already fully documents the single 'query' parameter with examples and semantics (product words or HTS prefix), providing 100% coverage. The description restates the same input types in prose without adding new meaning, so it remains at the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Search'), a specific resource ('official U.S. Harmonized Tariff Schedule'), and the input forms (product words or HTS prefix). It also describes the output shape (up to 20 tariff lines with duty rates), which distinguishes it from the singular-lookup sibling get_us_tariff.

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

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 to find tariff data by product words or HTS code prefix), but it does not explicitly compare against siblings or state when not to use it. No alternatives or exclusions are mentioned, so the guidance is limited to implied context.

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

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds the return fields (license number, type, location, renewal date), which is useful, but it does not disclose potential caveats like data freshness, match behavior, or error conditions. With annotations covering safety, this is adequate but not exceptional.

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

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

The description is a single, front-loaded sentence that states the purpose, the matching criteria, and the returned fields with no redundancy or filler. Every word contributes to understanding.

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

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

For a tool with one parameter, no output schema, and simple look-up behavior, the description adequately covers the core aspects: what it checks, how to query, and what is returned. It does not address edge cases like not-found or multiple matches, but these are minor for such a simple tool and could be inferred from the described behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the schema description ('Company name (e.g. "Young Sea Cargo") or FMC license number.') already fully defines the query parameter. The tool description only restates this ('by company name or license number') without adding new meaning, so it stays at the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb ('Check') and resource ('FMC list of licensed and bonded Ocean Transportation Intermediaries'), and clarifies it operates by company name or license number. It is clearly distinct from the sibling tools which focus on exports, tariffs, and restricted parties, so an agent can immediately identify its purpose.

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

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

The description states what the tool does but offers no explicit guidance on when to use it versus alternatives, nor any exclusions. While the purpose is clear enough to infer, it does not mention, for example, that restricted-party screening should use screen_restricted_party, leaving the routing to the agent's inference.

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