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

Annotations include only openWorldHint: true, which implies potential external effects but gives no specifics. The description adds valuable context about the output type (consumption level index/description) and explicitly excludes raw data, clarifying the tool's scope. However, it does not mention any side effects or mutation, which could be a gap if the tool triggers writes. The description’s clarification of behavior (what it returns and what it omits) earns a strong score, though not the highest due to missing side-effect disclosure.

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 reasonably concise given the complexity: it states purpose, coverage, exclusions, and typical questions in a structured way. While not ultra-short, every sentence contributes useful information (e.g., what is included, what is not, example queries). It is front-loaded with the core action and scope, making it efficient without being verbose.

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?

With an output schema present (not shown but indicated), the description need not explain return values. It covers what the tool does, what it returns (consumption index/description), exclusions, address requirements, and typical usage. For a two-parameter tool with full schema coverage and rich sibling context, the description is comprehensive and leaves no major gaps for an agent to choose and invoke 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?

Schema descriptions cover 100% of parameters, already explaining city format and address structure. The description adds extra guidance on address granularity (must be a specific point, not city/district) and provides multiple address examples, which reinforces the schema. It does not redefine parameters but adds contextual color that aids correct invocation, so it adds value beyond the schema.

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 the tool queries surrounding consumption analysis for a specific address in China, returning a consumption level index and description, and explicitly lists exclusions (e.g., no per-capita expenses, POI lists). It differentiates from sibling tools (cbd_surrounding_amenity, housing, population) by focusing on consumption, making its purpose 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?

The description provides explicit usage constraints: the address must be a locatable point within China (not a city or district name, no overseas), and typical question formats are given. It also lists what the tool does not include, guiding when to use it (for consumption level, not detailed data). This goes beyond basic context and offers actionable guidance for selection.

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