check_shippingCheck whether Neptune Cigars can ship premium cigars to a US state.
Accepts a state name or 2-letter code. Returns the DTC shipping posture, age/ID delivery rules, and tax notes for that state. Neptune ships from Florida; all deliveries require an adult (21+) recipient.
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint annotation, the description discloses useful behavioral details: accepted state input formats, returned information categories (DTC shipping posture, age/ID rules, tax notes), and the 21+ adult signature requirement. This gives the agent a solid behavioral model without contradicting 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 four sentences with no filler: purpose first, then input format, return contents, and a key shipping constraint. Every sentence adds necessary 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 single-parameter read-only tool with an output schema, the description is complete. It explains the input, the kind of output, and an important delivery rule. Nothing essential is missing for an agent to call 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 coverage is 0%, but the description fully compensates by explaining that the single 'state' parameter accepts a state name or 2-letter code and refers to a US state. This is the only parameter, and its meaning and accepted formats are fully covered.
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 and resource: 'Check whether Neptune Cigars can ship premium cigars to a US state.' This clearly distinguishes it from sibling search and product tools. The title and description align, and the intended operation is immediately evident.
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 gives clear context for when to use the tool: to determine shipping eligibility for a US state. It does not name alternatives or exclusions, but the sibling tools are search/product-related and not plausible substitutes, so no explicit exclusion is necessary.
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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The two search tools are clearly separated by description—search_cigars finds cigar lines while search_products finds buyable SKUs—so the main overlap is manageable. get_cigar_line and similar_cigars are also distinct (details vs recommendations). The slight ambiguity between the two search tools prevents a perfect score.
Most names follow a clean verb_noun snake_case pattern: check_shipping, get_cigar_line, search_cigars, search_products. similar_cigars breaks the pattern by omitting a verb, making it slightly less consistent than the rest.
Five tools is well-scoped for this domain: shipping lookup, line search, line details, product search, and similar-cigar discovery. Each tool serves a clear purpose without redundancy or bloat.
Core workflows are covered: discover lines, inspect details, find similar options, locate buyable products, and verify shipping legality. A minor gap is the lack of a direct product-detail-by-SKU endpoint or brand-based filtering, but agents can work around these without major failure.