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?
With no annotations, the description carries the full burden. It describes the search behavior and optional filters, but does not explicitly state that it is read-only or mention any side effects, rate limits, or authentication requirements. However, the nature of 'search' implies non-destructive action.
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 two sentences, front-loaded with the main action. Every word serves a purpose, with no redundancy or 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?
The tool has no output schema, but the description explains what is returned (slug) and how it fits into a workflow with siblings. It could mention response structure or pagination, but for a simple search tool, it is adequately 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 coverage is 100%, providing baseline of 3. The description adds value by giving example keywords and explaining the purpose of the parameters (e.g., returning slug for later use), which helps agents understand the context beyond the schema definitions.
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. It distinguishes from siblings by specifying that the returned slug is for use 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?
Guidance is explicit about using the returned slug with sibling tools, implying this is a preparatory step. No alternative tools or when-not-to-use scenarios are mentioned, but the workflow 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 unique and clear purpose: search finds calculators, get_calculator retrieves details, and compute performs calculations. No overlap exists.
All tools use lowercase with underscores and follow a verb_noun pattern (search_calculators, get_calculator, compute). Consistent naming convention.
Three tools is ideal for this domain: discover, inspect, and compute. Each tool earns its place without unnecessary bloat.
The tool surface covers the full workflow: searching for calculators, retrieving their input schema, and computing results. No obvious gaps.