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

Annotations already disclose readOnly, idempotent, and non-destructive behavior. The description adds useful authentication context: an optional API key selects Pro when valid. It does not describe return format or any other behavioral traits, but given the annotation coverage, the addition is enough to justify a mid score.

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 compact: a front-loaded domain summary plus a necessary note about the Pro API key. There is no filler or redundancy. It loses a point because the first sentence is a fragment rather than a complete, self-explanatory statement.

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 two-parameter tool with an output schema and safety annotations, the description covers domain and authentication but misses key context: what the output actually represents (forecast vs. historical data), how timeframe changes results, and when to prefer sibling tools. An agent could call the tool from schema alone, but the description leaves too much to assumption.

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 description coverage is 0%, so the description must compensate. It partially does by listing human-readable indicator names, which map to the indicator enum. However, it never mentions the timeframe parameter or explains how it affects results. The enum values are self-explanatory, but the description fails to provide explicit parameter guidance.

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 identifies the domain (real estate) and lists the specific data series: Case-Shiller, supply, permits, and 30-year mortgage rate. This distinguishes it from sibling forecast_* tools. However, it lacks an explicit verb such as 'retrieves' or 'forecasts,' so the action is only implied by the tool name and title.

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 implies usage for housing-related indicators by listing those categories, but it never explicitly states when to use this tool versus alternatives like forecast_commodities or forecast_rates. There is no 'when not to use' or mention of sibling tools, so an agent must infer the selection from the domain list.

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