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LastLook Data

by io.github.zev-lll

Get Rate Environment Snapshot Bundle

get_bundle_rate_environment
Read-onlyIdempotent

Returns a complete rate environment snapshot in one call: FEDFUNDS, SOFR, DGS2, DGS5, DGS10, DGS30, plus computed yield curve spreads (2s10s and 3m10y), Fed policy spread (EFFR vs IORB), and curve shape signal. Use this instead of multiple individual calls when you need the full rate picture.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
as_ofYesDate of the most recent underlying data
bundleYesBundle identifier
seriesYesCurrent values for each rate series
derivedYesComputed spread and policy fields
signalsYesCurve shape and policy stance signals

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds behavioral context by revealing computed outputs (e.g., curves, signals) beyond raw data, indicating that the tool performs calculations and returns a synthesized snapshot. While it doesn't clarify rate limits or output format, the description supplements annotations with valuable behavioral nuance.

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: the first compactly lists the full inventory of returns, the second offers tactical guidance. Every word earns its place, and the key information is front-loaded.

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 presence of a rich output schema (acknowledged in signals) and comprehensive annotations, the description is fully adequate for an agent to select this tool. It explains the tool's scope, contents, and use case, making it a complete reference for decision-making.

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?

With zero parameters and 100% schema coverage (trivially empty), the baseline is 4 per the rubric. The description adds no parameter semantics because there are none to explain; it appropriately focuses on the tool's broad return scope.

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 'Returns a complete rate environment snapshot' and explicitly enumerates all included series and computed metrics (FEDFUNDS, SOFR, DGS2, DGS5, DGS10, DGS30, yield curve spreads, Fed policy spread, curve shape signal). This distinguishes it clearly from sibling tools like get_treasury_yield_current or get_policy_spread by establishing the full-picture scope.

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 states when to use the tool: 'as the full rate picture' and recommends it instead of multiple individual calls. This provides clear contextual guidance, though it does not name specific sibling tools as alternatives or state exclusion criteria (e.g., when only a single series is needed).

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.

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