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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds valuable context beyond annotations: data source (Census Bureau), units (thousands of units at SAAR), and the structuredContent return shape with field names. It doesn't contradict annotations, though it omits deeper caveats like data revisions or seasonal adjustment nuances.

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 well-structured with clearly separated sections: purpose, when to use, when not to use, args, return format, and units. Every sentence contributes meaningful information without redundancy or fluff. It is appropriately sized for the tool's complexity.

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 the tool has no parameters and no output schema, the description fully documents the return payload fields (asOf, startsThousands, permitsThousands, startsMomPercent, permitsMomPercent, source), units, source URL, and interpretive context. It leaves no critical gaps for an AI agent to invoke and use the result correctly.

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 tool has zero parameters, and the description explicitly states 'Args: none.' The input schema confirms an empty object, so there is no additional parameter information needed. The baseline for zero parameters is 4, and the description fully satisfies it.

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 tool's purpose: providing the latest U.S. housing starts and building permits at a seasonally-adjusted annualized rate. It distinguishes itself from sibling macro tools by focusing specifically on residential construction and even clarifies the leading-indicator relationship between permits and starts.

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 includes explicit 'When to use' and 'When NOT to use' sections with concrete examples (gauging housing-market momentum, leading indicator for construction activity) and exclusions (single-family vs multi-family, regional detail, completions). This provides clear decision guidance for selecting this tool over alternatives.

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