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

Annotations already mark it read-only, and the description adds valuable behavioral context: the 0-100 scale, composite z-score methodology, data sources, weekly frequency, and the fields returned (per-metro score, driver attribution, confidence, methodology_version). The optional 'days' parameter further explains the history-series behavior and Gold-tier requirement, going well beyond the annotations.

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 information-dense but well-structured: first the return value and composition, then the output details, then explicit use cases, and a final update cadence note. Every sentence delivers distinct value; no filler or 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 a single optional parameter, no output schema, and read-only nature, the description covers the core outputs, scope, methodology, frequency, and typical use cases. A minor gap is that it does not explicitly map high vs. low score to seller's/buyer's market, but the phrase 'housing heat' strongly implies that. Overall, it is sufficiently complete for an agent to decide when and how to invoke it.

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?

The single parameter 'days' is fully documented in the schema (range, purpose, tier requirement, fallback behavior), so schema coverage is 100%. The tool description does not add extra parameter semantics, but it does set context that the default is a current snapshot. This matches the baseline for high schema coverage.

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 opens with a specific verb and resource: 'Returns a 0-100 metro housing heat score' and details the composite inputs (Zillow/Redfin listing dynamics) and scope (~894 US metros). This clearly distinguishes it as the housing-heat/ranking tool within the adw family, with no ambiguity about what it does.

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?

The description explicitly states when to call: 'Call when the user asks which US metros are seller's vs buyer's markets, about housing heat or metro rankings, or when timing a home purchase, listing, or SFR acquisition.' It does not name alternative tools or provide when-not-to-use guidance, but the usage scenarios are concrete and easy to map to user intents.

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