get_snapshot
PAID ($0.02). Snapshot of every series for every country in one call. Pass api_key if you have one; otherwise the response explains how to pay via x402.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | No | API key |
PAID ($0.02). Snapshot of every series for every country in one call. Pass api_key if you have one; otherwise the response explains how to pay via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | No | API key |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses paid cost ($0.02) and payment mechanism (api_key or x402), but does not mention rate limits, response size, or failure modes. No annotations provided, so the description carries the burden but is incomplete.
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 purpose, zero waste. Every word adds value.
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?
No output schema, so description should hint at return structure. It misses potential large response size or pagination. Covers cost and auth, but not output format.
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?
Adds meaning beyond schema: explains that api_key is optional and if missing, response explains payment via x402. Schema coverage is 100% but description enriches the parameter's role.
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 it provides a 'snapshot of every series for every country', which is a specific verb-resource pair. It distinguishes from sibling tools like get_series or list_series that are more focused.
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?
Implies usage for broad overview, but no explicit when-to-use vs alternatives. The paid nature and payment method are noted, but sibling tools like compute_tax or get_public_holidays suggest different use cases.
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 operation: minimum wage, income tax, VAT, working days, holidays, series data, and settlement dates. No overlap in purpose.
All tool names follow a consistent verb_noun pattern (e.g., check_minimum_wage, compute_income_tax, get_public_holidays, list_series). Only 'settlement_date' is a noun phrase but still clear.
10 tools cover a well-scoped domain of economic reference data without bloat. The count feels appropriate for the server's purpose.
Covers core areas: wage, tax, VAT, holidays, series, settlement dates. Minor gaps exist (e.g., no social security or currency data), but the scope is clearly defined and noted.