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LastLook Data

by io.github.zev-lll

Get Home Purchase Market Bundle

get_bundle_purchase_market
Read-onlyIdempotent

Returns a home purchase market bundle: current 30yr mortgage rate, median US home sale price (MSPUS), estimated monthly P&I payment on the median home assuming 20% down, annual income required to qualify at 28% DTI, affordability level signal, and housing starts. Directly answers "can my client afford a home today?" Priced at $0.60 USDC via x402 on Base.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
as_ofYesDate of the most recent underlying data
bundleYesBundle identifier: purchase_market
seriesYesMORTGAGE30US, MSPUS, HOUST, FEDFUNDS
derivedYesloan_amount, monthly_payment_estimate, income_required_28pct, home_price_change_qoq
signalsYesaffordability_level (elevated/moderate/accessible), market_activity (strong/moderate/subdued)

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 as read-only, idempotent, and non-destructive. The description adds valuable context beyond annotations by specifying the exact contents, underlying assumptions (20% down, 28% DTI), and pricing via x402. It does not disclose potential data freshness limitations, but for a read-only bundle this is sufficient.

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 exceptionally concise: two sentences that deliver the core information (contents and purpose) upfront, followed by practical pricing. Every word adds value, and there is no redundant or filler content.

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 tool has no parameters, a known output schema, and strongly annotated read-only/idempotent behavior, the description fully covers the necessary context. It lists all data elements, states the use case, and notes the payment mechanism, leaving no significant gaps for an agent to select and invoke the tool.

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 tool has zero parameters, so the baseline is 4. The description correctly focuses on what the bundle contains rather than parameter explanations, which are unnecessary. There is no additional parameter semantics needed beyond the schema, which already has 100% 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 'Returns' and clearly identifies the resource as a 'home purchase market bundle' with a detailed list of components (30yr mortgage rate, median home price, P&I payment, income required, affordability signal, housing starts). It also states the direct use case ('can my client afford a home today?'), distinguishing it from other bundle tools focused on different markets.

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 provides clear contextual guidance with the statement 'Directly answers "can my client afford a home today?"' implying when to use this tool. However, it does not explicitly name sibling alternatives or state when not to use it, so it falls short of a 5 but is still well above average.

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