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LastLook Data

by io.github.zev-lll

Get Yield Curve Spreads

get_yield_curve
Read-onlyIdempotent

Returns 2s10s (2-year vs 10-year) and 3m10y (3-month vs 10-year) Treasury yield curve spreads with inversion signal. An inverted yield curve (negative spread) historically precedes recessions. Source: FRED.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
DGS2Yes2-Year Treasury yield
DGS10Yes10-Year Treasury yield
as_ofYesDate of the most recent underlying data
DGS1MOYes1-Month T-Bill rate
signalYesCurve shape signal: Fully inverted, Partially inverted, or Normal
spread_2s10sYes10Y minus 2Y Treasury spread in percentage points
spread_3m10yYes10Y minus 3-Month T-Bill spread in percentage points
inverted_2s10sYesWhether the 2s10s spread is negative (inverted)
inverted_3m10yYesWhether the 3m10y spread is negative (inverted)

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint=false, so safety is covered. The description adds useful context about the specific spreads and inversion signal meaning, plus the source (FRED), but does not disclose additional behavioral details such as data latency or error handling.

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 concise sentences, front-loaded with the main function. The first sentence states exactly what is returned; the second adds interpretive context. Every word earns its place with no redundancy.

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?

For a no-parameter tool with an output schema and comprehensive annotations, the description provides complete context: what spreads are returned, the inversion signal's meaning, and data source. Nothing essential is missing.

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

Parameters4/5

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

The input schema is empty (0 parameters), and baseline for 0 params is 4. The description does not need to explain nonexistent parameters, and the schema already provides full coverage.

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 uses a specific verb and resource: 'Returns 2s10s (2-year vs 10-year) and 3m10y (3-month vs 10-year) Treasury yield curve spreads with inversion signal.' This clearly states what the tool does and distinguishes it from sibling tools that return yields or bundles.

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 clearly implies usage when yield curve spreads and inversion signals are needed, noting their historical recession link. However, it does not explicitly name alternatives or state when not to use this tool, so it falls short of a 5.

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