quedas_de_precoLista produtos cujo preço caiu de forma relevante nas últimas horas, incluindo os que atingiram o menor preço já registrado desde que passaram a ser monitorados.
| Name | Required | Description | Default |
|---|---|---|---|
| limite | No | Quantas quedas retornar (1-50, padrão 10). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for transparency. It describes the action of listing price drops but does not mention any limitations (e.g., date range, data sources) or side effects, though the read-only nature is implicit. The mention of 'including those that reached the lowest price ever recorded' adds some specificity but lacks deeper behavioral detail.
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 concise sentence, directly stating the tool's function without unnecessary words. It is well-structured and easy to parse, containing all essential 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?
The description provides sufficient context to understand the tool's purpose and how to invoke it, including the parameter. It does not describe the output format, but since no output schema is specified, this is acceptable. The description is complete enough for an agent to use the tool 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?
The parameter 'limite' is fully described in the schema (quantas quedas retornar, 1-50, default 10). The description adds no additional meaning beyond the schema, but the schema coverage is 100%, so the parameter semantics are clear without further elaboration.
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 the tool lists products with significant price drops, including those reaching all-time lows. It distinguishes from sibling tools like promotions and coupons by focusing on price drops, making the purpose specific and 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 description implies usage for price-drop queries, and the presence of sibling tools (buscar_promocoes, melhor_cupom) provides context for when this tool may be appropriate. However, it does not explicitly state when to use this over alternatives, leaving some inference to the agent.
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 has a distinct focus: listing promotions, finding coupons for a specific product, and listing recent price drops. There is minor overlap because buscar_promocoes also surfaces applicable coupons, but melhor_cupom is clearly more specialized and per-product.
The names are readable Portuguese but follow no consistent pattern: buscar_promocoes is verb+noun, melhor_cupom is adjective+noun, and quedas_de_preco is noun+preposition+noun. A consistent verb_noun style like listar_promocoes, obter_cupom, listar_quedas would be clearer.
Three tools is on the small side but appropriate for a focused discount/price-tracking server. The scope is narrow enough that each tool earns its place without feeling padded.
The server covers the main deal-discovery use cases: browsing active promotions, checking coupons for a specific product, and surfacing meaningful price drops. A minor gap is the lack of a tool for detailed price history or category-specific searches, but agents can likely work around this.