Get BraFinder's cross-brand bra-size offset dataset: the key facts and the machine-readable feed URL to cite. Use when you need the authoritative source for how bra sizes translate between brands.
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the tool as returning 'key facts and the machine-readable feed URL,' which is transparent about the output but lacks details on format or potential side effects. Since it's a read-only data retrieval, the transparency is adequate but not rich.
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 consists of two concise sentences: one stating what the tool does and one specifying when to use it. Every sentence adds value without unnecessary detail.
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?
Given zero parameters and no output schema, the description provides sufficient context: it identifies the resource and its use case. It lacks some detail on the exact structure of the returned dataset but is complete enough for an agent to understand the tool's role.
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?
There are no parameters (schema covers 100% with no properties). The description implies no input is needed by stating 'Get... dataset,' which is sufficient. The schema already indicates no parameters, so the description adds value by confirming simplicity.
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 states 'Get BraFinder's cross-brand bra-size offset dataset', specifying a verb and resource. It also mentions key facts and a feed URL. This distinguishes it from siblings like translate_bra_size (individual conversion) and bra_brand_fit (fitting guide).
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 says 'Use when you need the authoritative source for how bra sizes translate between brands,' providing a clear usage context. It does not explicitly state when not to use, but the context implies alternatives from sibling tools.
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.
Tools are mostly distinct: bra_brand_fit gives fit notes, translate_bra_size gives exact conversions, find_bras finds products, bra_size_dataset provides raw data. However, bra_brand_fit and translate_bra_size both deal with cross-brand sizing, which could cause minor confusion.
Naming patterns are mixed: 'find_bras' and 'translate_bra_size' follow verb_noun, while 'bra_brand_fit' and 'bra_size_dataset' are noun phrases starting with 'bra'. Inconsistent but still clear.
4 tools is reasonable for a niche domain like bra sizing. Not overly thin, covers key operations without excess. Could add one more tool for user contributions, but current count is appropriate.
Covers core use cases: finding fit notes, translating sizes, searching bras, and accessing the dataset. Missing update/delete operations, but this is a read-only informative server, so gaps are minor.