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Glama

search_beans

Search every bag of specialty coffee on sale in New Zealand. Filter by free text (name, roaster, origin, tasting notes), origin, roast style, roaster, price and stock. Results are cheapest per 100g first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNoFree text: name, roaster, origin or tasting note.
originNoCountry or region, e.g. 'Ethiopia'.
roasterNoRoaster name or slug.
roast_styleNo
in_stock_onlyNo
max_price_nzdNo
max_price_per_100gNo

TDQS

A3.7/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full disclosure burden. It usefully reveals the scope ('every bag... on sale in New Zealand') and the sort order ('cheapest per 100g first'), but it does not mention pagination, default stock filtering, or response shape.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler. The search scope and ordering rule are front-loaded, and every clause adds information relevant to calling the tool correctly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers scope, filters, and ordering, which is good for a search tool. However, with no output schema and no mention of pagination, limit defaults, or result format, an agent cannot fully predict what the tool returns or how many results to expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is low (38%), so the description adds some value by clarifying that the free-text query covers name, roaster, origin, and tasting notes, and by listing filterable dimensions. However, it does not clarify the difference between max_price_nzd and max_price_per_100g or the behavior of limit and in_stock_only.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Search'), a precise resource ('every bag of specialty coffee on sale in New Zealand'), the available filter dimensions, and the result ordering. This clearly distinguishes the tool from siblings like best_deals and roaster_info even without naming them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The use case is implied by the search-and-filter phrasing, but there is no explicit guidance on when to prefer this tool over best_deals or roaster_info, nor when not to use it. An agent would have to infer the boundary from tool names alone.

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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TDQS

A3.9/5.0
Disambiguation5/5

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.

Naming Consistency3/5

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.

Tool Count5/5

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.

Completeness5/5

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.

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