The New Zealand specialty roasters we track: how many bags each has, their cheapest per 100g, their published shipping terms and where they roast. Omit roaster for all of them.
| Name | Required | Description | Default |
|---|---|---|---|
| roaster | No | Name or slug. Omit for all. | |
| include_beans | No | Also return that roaster's shelf, up to 200 bags. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It frames the tool as an informational lookup and lists the returned fields, implying a read-only operation. Still, it does not mention error behavior, data freshness, or what exactly happens when `roaster` is omitted versus provided.
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 one dense, front-loaded sentence: it names the resource, lists the key output attributes, and ends with the critical calling convention. Every phrase contributes value and there is no filler.
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 read-only lookup with two optional parameters, the description adequately summarizes the main output. However, with no output schema and no annotations, an agent still lacks clarity on the exact response shape and failure behavior, so the definition is only minimally complete.
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%, so the baseline is 3. The description adds useful context around `roaster` by explaining the omit-for-all behavior and clarifies the per-100g metric, but it does not substantially expand on the schema's parameter descriptions.
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 resource as the tracked New Zealand specialty roasters and enumerates the specific data returned: bag counts, cheapest per 100g, shipping terms, and roast location. It lacks an explicit verb and does not differentiate from siblings, but the purpose is unambiguous.
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 instruction to omit `roaster` for all roasters is a concrete usage rule. However, the description does not explicitly state when to choose this tool over `best_deals` or `search_beans`, leaving the routing decision mostly to inference from the tool name and scope.
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 targets a distinct concern: curated deals, roaster-level details, and full searchable bean catalog. Although best_deals and search_beans both surface cheap prices, their purposes are clearly separated by the deal reasons versus filterable search.
Names are readable and all snake_case, but they mix conventions: search_beans is verb-first while best_deals and roaster_info are noun phrases. A more consistent pattern would be search_beans alongside get_deals and get_roasters or similar.
Three tools is a tight, well-scoped set for a read-only specialty coffee price tracker. No tool feels redundant or unnecessary for the server's purpose.
The surface covers the full stated domain: search all beans, see curated deals, and get roaster information including shipping and stats. Agents can accomplish all advertised user goals without dead ends.