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fhfa_hpi_trend

Read-onlyIdempotent

Summarize the latest FHFA HPI trend for one US geography from the self-hosted official series. Returns latest index, previous-period, one-year and five-year changes, five-year CAGR, recent direction, stable geography identifiers, and provenance. Use this for 'how fast are home prices rising in Texas?', 'is the Miami HPI falling?', or as the public-data corroboration leg for a realestate_market_screen. Not a forecast, appraisal, or investment recommendation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
placeYesExact FHFA place_id or geography name, such as 'CA', 'California', a 5-digit CBSA id, or an FHFA metro name.
frequencyNoObservation frequency. Default quarterly.
hpi_flavorNoFHFA index flavor. Default purchase-only.
index_basisNoIndex column to use. Default seasonally_adjusted.
geography_levelNoOptional exact FHFA geography level to disambiguate state, metro, division, or national series.
response_formatNoHuman-readable markdown or machine-readable JSON. Default markdown.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / geography_level / maxLength
      Added value: +100
    • addedInput schema / properties / place / maxLength
      Added value: +120
    • addedInput schema / properties / place / minLength
      Added value: +1
  2. Added

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, openWorld, so the safety profile is covered. The description adds useful framing with the 'not a forecast, appraisal, or investment recommendation' disclaimer and 'self-hosted official series' provenance note. It doesn't discuss failure modes (unknown geography, series gaps) or output verbosity, so a 3 is appropriate.

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?

Front-loaded with the core action and scope, then a bullet-style enumeration of outputs, then example queries, then an explicit exclusion. Every sentence carries information with no padding.

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

Completeness4/5

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

For a read-only, 6-parameter (1 required), fully-described-schema tool with no output schema, the description sufficiently explains what is returned (index, prior period, 1y/5y changes, CAGR, direction, identifiers, provenance) and what it is not. Minor gap: no guidance on disambiguating place when multiple geographies match.

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% and each parameter has a description and enums where applicable, so the schema carries the semantic load. The description adds only the geography constraint ('one US geography') which the schema already conveys via the place parameter. Baseline 3.

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?

Specific verb (Summarize) + resource (latest FHFA HPI trend) + scope (one US geography from self-hosted official series). The description also enumerates what the return contains, which distinguishes it from sibling fhfa_hpi_series and fhfa_hpi_compare.

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?

Gives concrete example queries ('how fast are home prices rising in Texas?', 'is the Miami HPI falling?') and names a specific integration use case (corroboration leg for realestate_market_screen). Does not explicitly state when NOT to use it, e.g. versus fhfa_hpi_compare or fhfa_hpi_series, so it stops short of full routing guidance.

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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