eur_gbpLatest N observations of the EUR/GBP spot rate — € per £1 (series XUDLERS), most recent first.
This call uses example arguments supplied in the tool’s input schema.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {
"last": 10
},
"name": "eur_gbp"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| last | No | Number of most-recent observations (default 10). |
Changes observed during successful MCP inspections.
Input schema / examplesAdded value: +[
+ {
+ "last": 10
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds behavioral context by stating the observations are most recent first and specifying the series code, which helps the agent understand the data ordering and source. This goes beyond the annotation-provided safety profile.
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 a single, concise sentence that front-loads the core functionality, includes the currency pair, unit, series code, and ordering. There is no redundant information 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?
For a simple read-only tool with one optional parameter and no output schema, the description is reasonably complete. It specifies the type of data (spot rate), the series, the ordering, and the unit. It does not detail the exact return structure, but this is not necessary for such a straightforward retrieval tool.
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% for the single parameter 'last', which already explains it is the number of most-recent observations with a default of 10. The description uses 'N' to correspond to this parameter but does not add significant new meaning beyond the schema's own documentation.
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 the latest N observations of the EUR/GBP spot rate, specifying the currency pair, the unit (€ per £1), and the series code (XUDLERS). This distinguishes it from sibling tools like usd_gbp and generic get_series.
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 implies when to use the tool: to obtain recent EUR/GBP spot rate data. The context is clear from the currency pair and series identifier, though it does not explicitly mention alternatives or exclusions. Since the name and description make the use case obvious, this is a clear context without explicit alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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