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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds valuable context beyond annotations: data provenance (LiveDataLink self-hosted snapshot), return contents (place_id, geography level, year/period, adjusted/unadjusted values, pagination, snapshot hash, attribution), and semantic clarification ('not a property value or appraisal'). No contradictions with 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?

Three sentences with zero fluff. The first sentence states the core action, the second enumerates key output components, and the third gives examples plus a critical disambiguation. Content is front-loaded and every sentence earns its place.

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 read-only, idempotent tool with a fully documented schema)Skip, the description provides everything an agent needs: anchor examples, output field list, data source, and conceptual context ('index measures average price change; not a property value'). Pagination, years, and frequency are in the schema, so no gaps remain for correct 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?

Input schema coverage is 100%, so the baseline is 3. The description references place examples ('California', 'Austin metro') and mentions adjusted/unadjusted values, which maps to index_basis, but does not add meaning beyond what the schema's parameter descriptions already provide. No additional parameter semantics are introduced.

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 states a specific verb ('Return'), a precise resource ('bounded FHFA House Price Index history for one US geography'), and scoping (single geography, official snapshot). It distinguishes itself from siblings like fhfa_hpi_compare and realestate_trend by noting it covers one geography and serves a distinct data role. The purpose is unambiguous.

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?

Explicit usage examples ('show California house-price history', 'chart the Austin metro HPI') and a collaboration note (e.g., 'federal price-index leg alongside realestate_trend') provide clear context. It stops short of explicit exclusions (e.g., 'for comparing multiple geographies, use fhfa_hpi_compare'), so guidance is strong but not fully exhaustive.

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