DatoQA — Historical Exchange Rates

get_record

Read-onlyIdempotent

Get an unexpired record with provenance and its explicit verification level. Source/schema validation is not independent factual verification.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes	Opaque record id returned by a DatoQA data response. Reuse it exactly; do not invent an id.

Output Schema

TableJSON Schema

Name	Required	Description
`id`	Yes
`data`	Yes	Source-specific payload; inspect units, observation dates, nulls and source notes.
`domain`	Yes
`citation`	Yes
`freshness`	Yes
`provenance`	Yes
`display_label`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 27, 2026

changedOutput schema / properties / provenance / properties / verification_level / enum

Previous value: -[
-  "official_source_and_schema_checked",
-  "method_specific"
-]New value: +[
+  "official_source_and_schema_checked",
+  "public_aggregator_and_schema_checked",
+  "method_specific"
+]

First observedSep 27, 2026

TDQS

A3.7/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only, idempotent, non-destructive, and closed-world behavior. The description adds valuable semantic context by stating that records are unexpired and that source/schema validation is not independent factual verification, but it does not disclose error behavior or return shape beyond what the output schema provides.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core action and followed by a precise caveat. Every phrase earns its place and nothing is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple one-parameter interface, rich annotations, and an output schema, the description is complete enough for an agent to call the tool correctly. It clarifies the record's expiration and verification semantics without needing to restate schema or return details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage for the single id parameter, including an opaque-id warning. The description adds no additional parameter semantics, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description provides a specific verb and resource: 'Get an unexpired record' with provenance and verification level. It is clear what the tool retrieves, but it does not explicitly differentiate this tool from siblings like get_evidence or catalog.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description offers no explicit guidance on when to use this tool versus alternatives. The usage is only weakly implied by the tool name and the requirement of an id, and no exclusions or alternative conditions are stated.

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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