Menor Preço Hoje - MPH

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

With no annotations, the description carries the full burden of disclosing behavior. It explains the source and geographic scope, but does not mention output shape, freshness of the price data, or any limitations. I believe the lookup-style behavior is reasonably clear, but the description could offer more detail about what the agent and user should expect.

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 compact: two sentences, with the core purpose front-loaded and the use case stated immediately after. Every sentence contributes useful information and there is no redundancy or filler.

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 single-parameter lookup tool, the description covers the main purpose, the location, the data source, and the trigger. It could be slightly more complete by clarifying what the response will contain, but the tool's simplicity means the current description is largely sufficient.

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 'product' already described as 'Produto procurado' and accompanied by an example. The description adds no additional parameter-level detail beyond restating the product context, so it stays at the baseline for fully documented schemas.

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 a specific action: finding the current lowest price of a product in a specific city using structured data from Menor Preço Hoje. This goes beyond a simple restatement and gives the agent a concrete sense of what the tool does, though it does not explicitly contrast it with sibling tools like search_offers or top_offers.

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 an explicit trigger: 'Use quando o usuário perguntar onde determinado produto está mais barato.' This gives clear context for when to invoke the tool, but it does not describe when not to use it or how it compares to the sibling alternatives.

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 only states the action ('compares offers') without revealing side effects (likely read-only), output format, pagination, or behavior when no offers are found. The limited information is not misleading but is insufficient for the agent to predict runtime 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 front-loads the action ('compares') and the object ('offers of a product'). It includes essential context (geographic scope) without extraneous words. Perfectly concise and well-structured.

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 simple tool with one parameter and no output schema, the description covers the basic function but lacks behavioral details (e.g., whether it returns a list, how it handles missing products) and usage guidance. The absence of annotations and output schema makes the description incomplete for full situational awareness.

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 already provides a clear description for the single 'product' parameter ('Produto que será comparado entre mercados'). The tool description adds no additional meaning to the parameter semantics. With 100% schema coverage, the baseline of 3 is appropriate.

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 it compares current offers of a product among supermarkets, with a specific geographic scope (Lages, Santa Catarina). It uses a specific verb (compare) and identifies the resource (product offers). However, it does not differentiate from sibling tools like search_offers or top_offers, so it loses a point on distinguishability.

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 like search_offers or best_price. It doesn't mention prerequisites, exclusions, or the appropriate context for choosing this tool. The agent is left to infer usage from the name alone.

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 full burden of behavioral disclosure. It communicates the core read-only behavior ('Lista') and geographic scope, but does not mention return format, ordering, pagination, or whether all markets are returned without filtering. It is adequate but minimal.

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, front-loaded sentence with no filler. It efficiently conveys the resource, action, and geographic context.

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 zero-parameter list tool with no annotations and no output schema, the description provides the essential context: what the list contains and where. It could have added more detail about the result structure, but the tool is simple enough that an agent can reasonably invoke it correctly from this description alone.

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 tool takes zero parameters, so there are no parameter semantics to clarify. Baseline is 4 given the empty schema; the description accurately describes what the no-argument tool will do, so there is nothing missing here.

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 ('Lista') and a specific resource ('mercados') with a clear scope ('Menor Preço Hoje em Lages, Santa Catarina'). This distinguishes it from sibling tools like search_offers and best_price, which target offers and prices rather than the markets themselves.

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: this tool is for listing markets tracked by Menor Preço Hoje in Lages, SC. It implies use when the agent needs the full set of markets, though it does not explicitly mention when to avoid it or name alternatives.

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 present, so the description carries the full burden of behavioral disclosure. It only states the search scope and does not mention return shape, pagination, data freshness, or other constraints. It adds minimal behavioral value beyond the action itself.

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?

Two short sentences front-load the core purpose and then provide a clear usage trigger. There is no redundant or filler content.

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 single-parameter search tool with no output schema, the description provides enough geographic and domain context and defines the result scope ('ofertas vigentes'). It lacks detail on response format, but the overall complexity is low and the input schema fully covers the parameter.

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 baseline is 3. The description adds user-intent context for the query but no additional syntax, format, or value constraints beyond what the schema already provides.

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 clear action ('Busca ofertas vigentes') on a specific resource (Menor Preço Hoje offers in Lages, SC) and domain. It does not explicitly name or contrast sibling tools, so it falls short of full differentiation.

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?

Explicitly says when to use ('Use quando o usuário procurar produtos, preços, promoções ou supermercados locais'). It provides clear context but no exclusions or alternative routing relative to the sibling tools.

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 and no output schema, the description carries the full burden of behavioral disclosure. It indicates a read-like retrieval action, but does not explain what 'top' means, how many offers are returned, whether results are ranked, or how freshness is determined.

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 with no filler. It front-loads the action and resource, and the additional context about source and location 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 no-parameter, read-only tool, the description is minimally adequate. However, it lacks details about ranking criteria, result count, or return format, and provides no differentiation from sibling tools, which limits completeness for an agent selecting among similar offer-related tools.

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 tool has zero parameters and the schema coverage is 100%, so there is nothing for the description to clarify. The baseline of 4 for zero-parameter tools applies here.

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 a specific action ('Retorna') and a specific resource: current top offers from Menor Preço Hoje in Lages, SC. This is specific enough to be useful, though it does not explicitly differentiate itself from sibling tools like best_price or compare_offers.

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?

There is no guidance on when to use this tool versus siblings such as search_offers, best_price, or compare_offers. The intended use case is implied by the name and description, but no explicit exclusions or alternatives are provided.

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