get_chaptersList all top-level Combined Nomenclature chapters (2-digit codes).
Bootstraps browsing the nomenclature top-down; drill into a chapter with
get_subtree.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Language for translated labels in the response. One of: bg, cs, da, de, el, en, es, et, fi, fr, ga, hr, hu, it, lt, lv, mt, nl, pl, pt, ro, sk, sl, sv. | en |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of disclosing behavior. It clearly implies a read-only list operation and clarifies that only top-level entries (2-digit codes) are returned, which is a key boundary. However, it does not explicitly address potential missing behavior like pagination or language-specific variations, though the lang parameter is fully documented in the 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?
The description is two concise sentences. The first states the core purpose, and the second gives navigation context. There is no wasted wording, and the information is front-loaded.
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 is simple with one parameter and an output schema. The description provides enough context for an agent to select and invoke the tool correctly, including its role in the browsing flow and the pointer to get_subtree for deeper exploration. The output schema handles return-value details, so no additional description is needed.
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 covers the only parameter 'lang' with a complete list of supported values, achieving 100% schema description coverage. The description itself does not add parameter-specific detail, which is acceptable given the schema already provides full semantics, but it also does not enhance the parameter understanding beyond the schema.
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 uses the specific verb 'List' with the resource 'top-level Combined Nomenclature chapters' and specifies '2-digit codes', making the tool's function clear. It also distinguishes itself from the sibling get_subtree by positioning itself as the top-down bootstrap and referencing the drill-down tool.
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 explicitly states when to use this tool ('Bootstraps browsing the nomenclature top-down') and provides a clear alternative for the next step ('drill into a chapter with get_subtree'). This gives the agent direct guidance on how this tool fits into the workflow.
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.
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.
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.
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.
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.