PAID ($0.005). Historical values of a reference series with effective date ranges, optionally filtered by from/to (YYYY-MM-DD). Pass api_key if you have one; otherwise the response explains how to pay via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | Latest effective date, YYYY-MM-DD | |
| from | No | Earliest effective date, YYYY-MM-DD | |
| series | Yes | Series id | |
| api_key | No | API key | |
| country | Yes | ISO country code |
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 discloses the $0.005 cost, the need for an api_key, and that without one the response explains x402 payment. This is valuable behavioral context. It does not mention rate limits or response structure, but the paid nature is the most critical trait.
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 sentences, front-loaded with the cost warning, and every word earns its place. It packs purpose, filtering, and payment information without 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 paid data-retrieval tool with 5 parameters and no output schema, the description covers the essential aspects: purpose, date filtering, cost, and payment flow. It does not describe the return format or pagination, but the effective date ranges and historical values give a clear enough picture. Sibling context further clarifies its 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?
Schema coverage is 100%, so a baseline of 3 is appropriate. The description adds meaning by explaining the from/to parameters are YYYY-MM-DD filters, and that api_key is optional with a specific fallback behavior. This goes beyond the schema descriptions and clarifies parameter usage.
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 'Historical values of a reference series' with a specific verb ('get') and resource, and distinguishes itself from siblings like get_series (likely current values) and get_snapshot by focusing on historical data with effective date ranges. The '$0.005' cost flag and date-filter mention add unique scope.
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?
It provides clear usage context: use for historical values, optionally filter by from/to, and how to pay. However, it does not explicitly name sibling tools as alternatives or state when not to use, leaving some inference to the reader. Still, the date-range and historical framing give good guidance.
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 reference-data query: minimum wage check, income tax computation, VAT breakdown, working days, public holidays, series current/history/snapshot/catalog, and settlement date. There is no overlap; even get_series and get_series_history are explicitly separated as current vs. historical values.
Most tools follow a clear verb_noun pattern (check_, compute_, count_, get_, list_). The one outlier is settlement_date, which is a noun phrase rather than verb_noun, but the deviation is minor and does not cause confusion.
With 10 tools, the set is well-scoped for a reference-data server covering tax, labor, calendars, and settlement. Each tool serves a distinct purpose and none feel redundant or unnecessary.
The server provides strong coverage: discovery via list_series, current and historical series values, a bulk snapshot, and domain-specific computations for minimum wage, income tax, VAT, working days, holidays, and settlement dates. Minor gaps exist (e.g., no direct tool for social security contributions), but the core reference-data workflows are well supported.
