zone_profile

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

No annotations are provided, so the description carries the full burden. It discloses the data sources and types of data returned. While it doesn't explicitly mention read-only behavior, rate limits, or data freshness, it is sufficiently transparent for a straightforward data retrieval tool.

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 clear sections (purpose, use when, returns, examples, args). Every sentence adds value, and the key information is front-loaded.

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's simplicity (1 parameter, no nested objects, straightforward output), the description covers all needed aspects: what it does, when to use, input format, and output contents. No gaps.

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 coverage is 0% but the description compensates fully by describing the only parameter 'postal_code' with format ('Spanish 5-digit postal code') and examples ('28001, 08001, 41001...'). This adds essential context beyond the schema's title and type.

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 explicitly states 'Spanish socioeconomic data by postal code' and lists specific data sources (INE/SEPE/AEAT/MITMA/MITECO) and metrics (income, unemployment, etc.). It clearly distinguishes from sibling tools (e.g., entity_lookup, borme_lookup) which target different domains.

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 'Use when' guidance with examples of user queries, and includes example inputs and outputs. This clearly indicates when the tool is appropriate.

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