Lookup a Swiss customs tariff (HS8) and return the full TARES row including MFN duty, preferential regimes, restrictions and customs relief codes. Always returns a non-official disclaimer that the agent must surface to the end user.
| Name | Required | Description | Default |
|---|---|---|---|
| hs8 | Yes | 8-digit Swiss tariff number | |
| lang | No | fr |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It usefully discloses that the tool 'always returns a non-official disclaimer that the agent must surface to the end user.' However, it does not mention other behavioral aspects such as error behavior, required permissions, or data source reliability, leaving room for improvement.
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, front-loaded with the action and resource, and the second sentence adds a critical usage note (disclaimer handling). Every word earns its place with no filler or repetition.
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 two-parameter lookup with no output schema, the description covers purpose, return content (full TARES row including MFN duty, preferential regimes, etc.), and a behavioral requirement (disclaimer surfacing). It is reasonably complete, though it omits explanation of the 'lang' parameter and does not describe the exact response format in the absence of an output schema.
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 50%: the hs8 parameter is described in the schema ('8-digit Swiss tariff number') and the description adds that it is used for lookup. However, the 'lang' parameter is not mentioned in the description at all, and its meaning (language choice) is only conveyed by the enum and default value. The description partially compensates but does not fully clarify both parameters.
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's function: 'Lookup a Swiss customs tariff (HS8) and return the full TARES row.' The verb 'lookup' plus the specific resource (HS8 tariff) and output content distinguish it from sibling tools like tariff_changelog (changes) and tariff_semantic_search (semantic search).
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?
No guidance is given on when to use this tool versus alternatives. The description focuses on what it does, not on context such as 'use when you have an HS8 code' or 'use instead of tariff_semantic_search for exact lookups.' This is a clear gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
finma_search and kyc_check overlap heavily; both search the FINMA registry by name, and kyc_check essentially does what finma_search does with include_warnings=true. The other tools are distinct, but this pair creates real selection ambiguity.
Names mix verb-first (classify_text), noun-first (finma_search, tariff_lookup), and pure nouns (cross_walk, entity_history). All are lowercase with underscores, so it's readable, but the inconsistent verb placement breaks a predictable pattern.
9 tools is well-scoped for a server covering multiple Swiss data domains (classifications, FINMA, tariffs, statistics). Each tool serves a distinct purpose and earns its place without being overwhelming.
The set covers core workflows: text classification, code mapping, entity search/history, tariff lookup/changelog/search, and statistics. Minor gaps like a direct get-entity-by-UID endpoint or more granular statistics exist, but agents can work around them.
