US Real Estate Data

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

The description discloses what data is returned (current value, YoY change, 12-month history) and basic parameter behavior (e.g., national vs metro, metro name required for metro data). However, it lacks information on authentication, rate limits, or potential side effects. Since no annotations are provided, the description carries full burden and does reasonably well but could be more thorough.

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

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

The description is concise with two sentences. It front-loads the purpose and key output details. However, it could be slightly more structured by ordering parameter information more clearly.

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

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

Given four parameters, no output schema, and no annotations, the description covers the main functionality but misses details on parameter interactions (e.g., using metro vs state together) and does not describe the response structure. It is adequate but not fully complete.

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

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

All four parameters are described in the input schema (100% coverage). The description adds minimal new information beyond summarizing the data type and what's returned. It does not clarify parameter interactions (e.g., mutual exclusivity of metro and state) or provide context beyond the schema descriptions.

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

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

The description clearly states the tool gets US home price data and specifies it returns national median home price or metro-level Zillow ZHVI data. It distinguishes itself from siblings like 'get_market_indicators' and 'get_rental_data' through its specific focus on home prices, though it does not explicitly contrast them.

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

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

There is no explicit guidance on when to use this tool versus alternatives. The description implies usage by detailing output, but it does not provide when-not-to-use scenarios or mention sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries full burden. It does not disclose behavioral traits such as data freshness, rate limits, required API keys, or what happens if an invalid series ID is provided. The tool's behavior is assumed but not explicitly stated.

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

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

The description is a single sentence front-loaded with the core purpose and followed by specific examples. Every word is necessary and contributes to understanding, with no redundancy.

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

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

Given there is no output schema and only one parameter, the description is fairly complete but lacks information about the return format or structure of the data, which would help an agent process the result correctly. The complexity is low, so a score of 3 is appropriate.

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

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

Schema coverage is 100% for the single parameter 'series'. The description adds meaning beyond the schema by stating that the default is 'all' and that values are comma-separated, reinforcing the valid list already in the schema. This extra context earns a score above baseline 3.

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

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

The description uses a specific verb ('Get') and identifies the resource ('key US housing market indicators from FRED'), listing concrete indicators (housing starts, building permits, etc.). It clearly distinguishes from sibling tools like get_home_prices and get_rental_data by focusing on broad market indicators.

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

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

There is no explicit guidance on when to use this tool versus siblings. The description implies it is for a broad overview, but does not state when to prefer get_home_prices for detailed price data or get_rental_data for rental-specific metrics.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations provided, so the description carries full burden. It does not disclose operational behavior such as data update frequency, whether metro filtering actually works (notes 'optional; national data returned regardless'), or any rate limits. Minimal behavioral context beyond return values.

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

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

Two sentences, front-loaded with core purpose, no redundancy. Efficiently communicates source, scope, and return data.

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

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

For a simple read-only tool with sibling context and no output schema, the description adequately covers purpose, data source, and outputs. Could mention data frequency or exactly which CPI series, but not essential for selection or invocation.

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

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

Schema coverage is 100%, so the baseline is 3. Description adds no new meaning beyond the schema's parameter descriptions. Does not clarify default behavior or metro limitations beyond what schema says.

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

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

Description clearly states the tool retrieves US rental market data from FRED BLS CPI series, specifying three outputs (national rent index, YoY change, monthly history). The name 'get_rental_data' and sibling tools (get_home_prices, get_market_indicators) make the domain and differentiation obvious.

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

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

No explicit guidance on when to use versus alternatives like get_home_prices. The description implies rental-specific context via the name and data origin, but lacks explicit 'when-to-use' or 'when-not-to-use' instructions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.