Get product functions, voice support by language, and Autopilot in-call quotes from the customer's uploaded tariff tables. Parameter lang; alias: language.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Language code; alias: language. | |
| language | No | Alias for lang. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the burden. It transparently implies a read operation from uploaded tariff tables, but does not disclose behavior when parameters are omitted, whether uploaded tables are required, or potential error scenarios.
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 with no filler. It packs the subject, source, and parameter alias note efficiently.
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 read tool with optional parameters and no output schema, the description covers the returned data categories and source adequately. However, it lacks usage conditions, output format, and any caveats about the tariff tables, leaving some gaps.
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%, so the baseline is 3. The description merely restates that 'lang' has alias 'language', adding no semantics beyond what the schema already documents.
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 names a specific verb (Get), concrete data categories (product functions, voice support by language, Autopilot in-call quotes), and a unique source (customer's uploaded tariff tables). This clearly separates it from sibling getters like get_plans and get_use_cases.
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?
There is no guidance on when to use this tool versus alternatives such as get_plans or list_languages. No prerequisites, exclusions, or contextual triggers are provided.
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.
Each tool maps to a distinct resource/action: one submission tool, six retrieval tools, and one language enumeration. The only potentially overlapping pair (get_capabilities vs get_plans) is explicitly separated by the pricing-on-request vs caller-quote distinction.
All names follow an action_object snake_case pattern: create_inquiry and get_* for content retrieval, with list_languages as a sensible enumeration name. There are no mixed conventions or vague verbs.
Eight tools is well-scoped for a CargoVox information and inquiry server. Each tool covers a meaningful part of the surface without redundancy.
The server covers the obvious lifecycle for its purpose: lookup/capability/plan/FAQ/integration/use-case/language information and a way to submit inquiries. No critical gap is evident from the tool surface.