zippopotam

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes a read operation ('Get'), which implies it's non-destructive, but doesn't specify any behavioral traits like error handling, rate limits, authentication needs, or what happens if the city isn't found. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 a single, efficient sentence that directly states the tool's purpose without any unnecessary words or fluff. It's appropriately sized and front-loaded, making it easy to parse quickly. Every part of the sentence earns its place by conveying essential information.

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 moderate complexity (3 required parameters) and the absence of annotations and output schema, the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, usage guidelines, and output format. With no output schema, the description doesn't explain what the tool returns (e.g., list of postal codes, error responses), leaving gaps in completeness.

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 input schema has 100% description coverage, with clear documentation for each parameter (city, state, country), including examples and formats. The description adds no additional parameter semantics beyond what's in the schema, such as explaining relationships between parameters or usage nuances. Given the high schema coverage, a baseline score of 3 is appropriate as the schema does the heavy lifting.

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's purpose: 'Get all postal codes for a city in a given country and state/province.' It specifies the verb ('Get'), resource ('postal codes'), and scope ('city in a given country and state/province'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from its sibling tool 'lookup_zipcode', which might offer similar or complementary functionality.

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 no guidance on when to use this tool versus alternatives, such as the sibling tool 'lookup_zipcode'. It doesn't mention any prerequisites, exclusions, or specific contexts for usage. The only implied usage is based on the purpose, but no explicit guidelines are given.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool's function but omits critical behavioral details such as error handling (e.g., invalid codes), data sources, accuracy, rate limits, or authentication requirements. This leaves significant gaps for an agent to understand operational constraints.

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 a single, efficient sentence that front-loads the core purpose and includes key details (what information is retrieved and the input parameters). There is no wasted verbiage or redundancy, making it highly concise and well-structured for quick comprehension.

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 moderate complexity (2 required parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks behavioral transparency and usage guidelines, leaving the agent without full context for reliable operation. The absence of an output schema means the description should ideally hint at return values, which it does not.

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 100%, with both parameters clearly documented in the schema (country as ISO code, zipcode as string). The description adds no additional semantic context beyond what the schema provides, such as format examples or usage notes, so it meets the baseline for high schema coverage without compensating value.

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 verb ('look up') and resource ('place information'), specifying what data is retrieved (city, state, coordinates) and the input type (ZIP/postal code). It distinguishes from the sibling tool 'lookup_city' by focusing on postal codes rather than cities, though not explicitly contrasting them.

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 retrieving geographic data from postal codes in a specific country, but provides no explicit guidance on when to use this tool versus alternatives like 'lookup_city' or other geographic tools. It lacks any mention of prerequisites, exclusions, or comparative scenarios.

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