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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It accurately describes the calculation and adds a useful interpretation threshold. However, it does not mention data source, freshness, or any limitations (e.g., if it returns null for unknown suburbs). For a simple metric tool, this is acceptable but not rich.

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 with zero waste. The core definition is front-loaded, followed by a practical interpretation. Perfectly sized for the tool's simplicity.

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 one-parameter read-only metric with an output schema, the description covers the essential meaning and interpretation. It doesn't mention potential error cases or prerequisites, but the output schema likely covers return format. It's complete enough for an agent to call correctly, though it could briefly note that the suburb must exist.

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 only parameter, suburb_name, has no schema description (0% coverage). The description implies it refers to a suburb ('at the suburb's current sales rate') but does not clarify the expected format, case sensitivity, or that it must be a valid suburb. Without schema documentation, the description should compensate but only partially does.

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 what the tool computes: months of supply (how many months to clear current for-sale stock at the current sales rate). It also adds an interpretive threshold (under 2 months = seller's market), which distinguishes it from sibling market metrics like days_on_market or stock_on_market. The verb and resource are specific.

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 defines the metric and its interpretation but does not explicitly say when to use this tool versus alternatives (e.g., supply_pressure or stock_on_market). It implies usage for assessing market tightness, but there are no exclusions or alternative routing. The guidance is adequate but not explicit.

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