Moradas — Portuguese addresses & postal codes

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

With no annotations, the description carries the burden of disclosing behavior. It makes the read-only nature clear through 'Look up' and enumerates the returned fields, including that street coverage is part of the result. It doesn't cover invalid input behavior or response shape, but for a simple lookup the core behavior is transparent.

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?

One sentence front-loads the verb and resource, gives a concrete example, and lists the output fields. No filler or redundancy.

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 one-parameter read-only lookup with no output schema, the description covers input format (with example) and output contents (place hierarchy and streets). The only gaps are lack of explicit differentiation from resolve_postal_code and any error/edge-case information, but the tool is otherwise self-explanatory.

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 100% and the single cp7 parameter is already documented as 'Postal code NNNN-NNN'. The description adds only a concrete example and the CP7 term, which is helpful but does not substantially extend the schema's meaning.

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 opens with a specific verb ('Look up') and names the resource (Portuguese postal code CP7 with an example), then lists the returned information (localidade, concelho, distrito, streets). It is clear and concrete, though it does not explicitly differentiate itself from the sibling resolve_postal_code.

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 intended use is implied: use this when you have a CP7 like '1000-098' and want locality/district/street information. However, it gives no explicit when-to-use guidance, no prerequisites, and no comparison to resolve_postal_code or suggest_address.

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?

With no annotations, the description correctly carries the behavioral disclosure burden. It states the return behavior, including the null case ('returns resolved address (or null)') and the additional list of postal-code segments. It does not mention side effects or auth, but this appears to be a simple lookup operation.

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 two sentences with no fluff. The purpose is front-loaded, followed by input provenance and return behavior. 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?

This is a simple tool with two well-documented parameters and no output schema. The description covers the inputs, the expected result, the null case, and the additional segment list, making it complete for an agent to select 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 description coverage is 100%, so the schema already documents art_id and numero well. The description reinforces 'art_id comes from suggest_address' and the door-number concept, but adds little 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 names a specific operation ('Resolve the exact 7-digit postal code') and a clear resource scope ('for a street and door number'). It also mentions that art_id comes from suggest_address, which helps distinguish this tool from the suggest-address and postal-code-info siblings.

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 clear context by indicating that art_id is obtained from suggest_address, implying this is the follow-up step after address suggestion. It does not explicitly contrast with postal_code_info, but the intended use case is evident.

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?

With no annotations, the description carries the behavioral disclosure burden. It clearly states the output fields (street, localidade, concelho, distrito, cp7) and the special cp7-null behavior. This provides meaningful operational information beyond the input schema, though it omits details like empty-result 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?

Four tightly written sentences: one overview, one input format with examples, one output description, and one conditional handoff to a sibling. Every sentence adds distinct value with no filler or repetition.

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 low parameter count and absence of an output schema, the description is nearly complete: it explains input variants, expected output fields, and a routing condition. A minor gap is that art_id is referenced as an input to resolve_postal_code but is not explicitly listed among the suggestion fields, so the agent must infer it comes from the response.

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 100%, so the baseline is 3. The description goes beyond the schema by giving real examples ('av liberdade lisboa 196', '1000-098') and explaining how q can represent different forms, including locality and door number. It does not add much for count, but the schema already documents 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 begins with a specific verb and resource: 'Autocomplete a Portuguese address or postal code.' It also differentiates from the sibling tool by explaining the condition under which resolve_postal_code should be used instead.

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?

It explicitly tells the agent when to hand off to resolve_postal_code: 'When cp7 is null ... call resolve_postal_code with art_id and the door number.' It also gives concrete input examples for both address text and postal codes. It does not fully distinguish from postal_code_info, but the core usage context is clear.

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