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Real Estate Forecast

forecast_real_estate
Read-onlyIdempotent

Predict real estate market trends using key indicators like Case-Shiller index, housing supply, permits, and mortgage rates to inform investment decisions.

Instructions

Housing: Case-Shiller, supply, permits, 30-year mortgage rate.

Optional API key via headers or ?api_key= selects Pro when valid.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indicatorYes
timeframeNomonthly

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already declare readOnly/idempotent/destructive status. The description adds valuable authentication context regarding API keys (headers vs query param) and Pro tier selection, but omits behavioral details like rate limits, forecast horizon, or data freshness that would be useful given the 'forecast' nature.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two compact sentences with no redundancy. Efficiently front-loads the domain (Housing) and covers authentication in the second sentence. However, extreme brevity contributes to underspecification given the lack of parameter documentation.

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

Completeness2/5

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

Despite having an output schema (relieving description of return value documentation), the description fails to adequately cover the input parameters. With 2 parameters and 0% schema coverage, the terse description leaves timeframe completely undocumented and indicator only partially explained through implicit mapping.

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

Parameters2/5

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

With 0% schema description coverage, the description must compensate for both parameters. It effectively maps prose descriptions to the indicator enum values (listing the four specific data types), but provides zero explanation for the timeframe parameter or what the indicator values represent semantically.

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

Purpose3/5

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

The description lists specific real estate indicators (Case-Shiller, supply, permits, mortgage rate) identifying the domain, but lacks an explicit action verb stating what the tool does (retrieve, forecast, fetch). It relies on the tool name/title to imply the forecasting action rather than stating it directly.

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

Usage Guidelines2/5

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

No guidance provided on when to use this tool versus siblings like forecast_commodities or forecast_gdp. No mention of prerequisites, data availability, or selection criteria for the specific indicators listed.

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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