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LastLook Data

by io.github.zev-lll

Get G10 FX Rate by Date

get_fx_rate_by_date
Read-onlyIdempotent

Returns the exchange rate for a G10 currency pair on a specific date. Source: European Central Bank. Use YYYY-MM-DD format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYesDate in YYYY-MM-DD format e.g. 2026-01-15
pairYesG10 currency pair e.g. EURUSD, USDJPY

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYesDate of the rate (YYYY-MM-DD)
pairYesCurrency pair identifier
rateYesExchange rate on the requested date
labelYesHuman-readable pair name

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, covering the safety profile. The description adds only the ECB source and date format requirement, which are useful but not rich behavioral disclosures. It does not contradict any annotations.

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?

Two short, focused sentences. The first states the core function; the second gives the date format. No redundancy or filler.

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?

The tool is simple, annotations cover safety, an output schema exists, and parameters are fully described. The description supplies purpose, source, and format, which is complete for this context.

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?

Schema coverage is 100% with detailed descriptions for both 'date' and 'pair', including a pattern and enum. The description reinforces the date format but adds no meaningful parameter semantics beyond what the schema already provides, so baseline 3 applies.

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

Purpose5/5

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

The description clearly states the tool 'Returns the exchange rate for a G10 currency pair on a specific date,' using a specific verb and resource. It distinguishes from sibling tools like get_fx_rate_current and get_fx_rate_series by emphasizing the specific date, and adds the data source (ECB).

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

Usage Guidelines4/5

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

The description explicitly specifies the date-specific use case and instructs 'Use YYYY-MM-DD format,' which is direct guidance. It does not name alternative tools like get_fx_rate_current or get_fx_rate_series, but the qualifier 'on a specific date' clearly implies the intended context.

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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TDQS

A3.9/5.0
Disambiguation3/5

The tool set has several overlapping functions, particularly among the bundle tools (e.g., get_bundle_context_brief vs get_bundle_macro both provide macro indicators, and get_bundle_rate_environment overlaps with get_yield_curve and get_policy_spread). Individual current/history/date tools are distinct but some redundancy exists (e.g., get_treasury_yield_current vs get_current_value for DGS30). Descriptions help differentiate purposes, but agents may still hesitate when selecting between similar bundles.

Naming Consistency4/5

All tool names begin with the verb 'get_' and use snake_case, creating a consistent pattern. The bundle tools are uniformly prefixed with 'get_bundle_', and individual data tools follow a get_[entity]_[modifier] structure (e.g., get_fx_rate_current, get_fx_rate_by_date, get_fx_rate_series). Minor deviations exist (e.g., get_series, get_current_value, get_value_by_date are less descriptive of the underlying entity), but overall the naming is predictable and readable.

Tool Count3/5

With 24 tools, the server is on the heavy side of the typical range. The broad domain (macro data, mortgage, crypto, FX, treasury, EDGAR) justifies many tools, but some could potentially be consolidated (e.g., individual rate tools vs rate bundles). The count does not feel overwhelming, but it is borderline heavy.

Completeness4/5

The server covers a wide range of economic and financial data with both bundled and granular views. It includes current, historical, and date-specific retrievals for FRED series, FX, and crypto, plus specialized tools for mortgages, recession, and yield curves. Minor gaps exist, such as no way to list all supported FRED series or full financial statements for EDGAR, but the core lifecycle of data querying is well covered.

Resources