Returns Chilean national public holidays for any given year. Use this tool when calculating delivery dates, scheduling appointments, computing working days, or any task requiring knowledge of non-working days in Chile. Returns all national holidays with dates in YYYY-MM-DD format and names in both Spanish and English.
| Name | Required | Description | Default |
|---|---|---|---|
| year | Yes | The year to get holidays for. Example: 2026 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and idempotentHint. The description adds behavioral context by specifying the date format (YYYY-MM-DD) and bilingual names (Spanish and English), which goes beyond the annotations. No contradictions.
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: the first states what the tool does, the second states when to use it and what it returns. Every sentence earns its place with no redundancy.
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?
For a simple read-only holiday lookup with one parameter and no output schema, the description adequately covers usage, return format, language, and scope. It does not mention error handling or edge cases, but the tool's simplicity makes this acceptable.
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%: the schema already describes the 'year' parameter with an example. The description's phrase 'any given year' adds no new information, so the baseline of 3 is appropriate since the schema does the heavy lifting.
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 returns Chilean national public holidays for any given year. The verb 'Returns' plus the specific resource (Chilean holidays) distinguishes it from sibling tools for other countries. It also specifies output format and languages.
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 gives explicit use cases: calculating delivery dates, scheduling appointments, computing working days. It implies Chile-specific usage, though it does not explicitly name sibling alternatives like get_argentina_holidays for other countries, which prevents a perfect score.
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 targets a distinct resource (a specific country's holidays or a specific identifier type). The four holiday tools are clearly separated by country, and the seven validation tools are each for a different document or identifier (CNPJ, CPF, CUIL, CUIT, PIX key, RFC, RUT). No two tools appear to overlap in purpose.
All tool names follow a consistent pattern: get_<country>_holidays for holiday lookups and validate_<identifier> for validation. Naming is entirely lowercase snake_case with a clear verb prefix, making it easy to predict tool names.
With 11 tools, the server is well-scoped for its purpose of providing Latin American business utilities. The set is neither too sparse nor overly large, and each tool contributes a distinct function. This count is appropriate for the intended domain.
The tool surface covers the major Latin American economies (Argentina, Brazil, Chile, Mexico) for both holidays and key identifiers. Minor gaps exist, such as missing validation for Peruvian RUC or Colombian NIT, and holiday coverage is limited to four countries. However, the core workflows for the included countries are well covered.