Busca calculadoras de Hacé Cuentas por palabra clave (ej. "imc", "préstamo", "aguinaldo"). Devolvé el slug para usar luego con get_calculator o compute. Opcional: filtrar por category y limitar resultados.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | máximo de resultados (default 10) | |
| query | Yes | palabras clave a buscar | |
| category | No | filtro opcional de categoría (finanzas, salud, deportes, impuestos, etc.) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It states that the tool returns a slug for later use but does not disclose any behavioral traits such as rate limits, authentication, or side effects. It adequately conveys the read-like nature but lacks depth.
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?
Two concise sentences with front-loaded purpose and examples. No unnecessary words. Very efficient.
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 the tool's simplicity (3 params, no output schema), the description covers the key points: what it does, what to do with the result, and optional filters. It could elaborate on the return structure, but it explicitly mentions returning a slug, which is sufficient.
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 100%, so the schema already describes all parameters. The description adds context by mentioning optional filters and giving keyword examples, but does not provide additional semantic detail beyond what the schema offers.
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's purpose: search calculators by keyword, with examples provided. It distinguishes from siblings by explaining that the result (slug) is to be used with get_calculator or compute.
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 provides clear guidance on the workflow: search first, then use the returned slug with sibling tools. It also mentions optional filters. It does not explicitly state when not to use, but context is clear.
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 purpose: search finds calculators, get_calculator retrieves details, compute runs calculations. No overlap.
All names use verbs and are in snake_case, but compute lacks a noun object unlike get_calculator and search_calculators, causing a slight inconsistency.
Three tools cover the core workflow of search, inspect, and compute, which is well-scoped for a calculator service.
The set covers the complete user-facing lifecycle: finding a calculator, understanding its inputs, and computing a result.