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

No annotations are provided, so the description carries the full behavioral burden. 'Calcula' implies a side-effect-free computation, but nothing states that this is read-only, whether the result is deterministic, whether antecipation changes the output, or what fees the 'custo real' includes.

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?

A single front-loaded sentence with no filler; the verb and the resource lead. It is appropriately sized for a simple two-required-parameter calculation tool.

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 no output schema, the description should at least characterize the return value, but 'custo mensal real' leaves open whether the result is a single number, a breakdown, or a comparison. For a low-complexity calculator it is minimally adequate but leaves the return shape unspecified.

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% with two fully documented enums, so the schema already explains brand and tier. The description's only added nuance is 'perfil específico' (mapping to tier) and the implication that antecipation affects the cost, which is marginal 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 states a specific verb (calcula) and resource (custo mensal real de uma maquininha) scoped to a specific profile, so an agent understands it produces a single-brand cost figure. It is clearly distinct from compare_brands in intent, though it never names the siblings to reinforce that distinction.

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 explicit when-to-use guidance, no mention of prerequisites (e.g. that brand/tier must come from get_brands/get_tiers), and no statement of when to prefer compare_brands instead. The agent must infer the routing 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?

No annotations are provided, so the description carries the full burden. It does disclose the output nature ('retorna o ranking de custo'), which is valuable given there is no output schema, but it says nothing about side effects, permissions, determinism, or rate limits for what is presumably a read-only computation.

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?

A single sentence that front-loads the action, the scope of comparison, and the return value with zero filler. Every clause 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 two-parameter comparison tool with no annotations and no output schema, the description covers what it does, what it takes conceptually (business profile), and what it returns (cost ranking). Only minor gaps remain, such as what dimensions the ranking is based on and whether results are ordered ascending by cost.

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 both parameters (tier enum, antecipation boolean) are already fully documented in the schema. The description adds only the loose phrase 'perfil de negócio', which maps to the tier parameter without adding syntax or meaning beyond the schema, so the baseline 3 applies.

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 gives a specific verb ('Compara'), a scope ('todas as marcas de maquininha') and a business-profile input, plus the output nature ('ranking de custo'). It is clearly distinct from calculate_cost (single-brand cost) by the word 'todas', though it never names that sibling explicitly.

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?

Usage is implied rather than stated: comparing 'all brands' for a profile signals a multi-brand comparison scenario, which implicitly contrasts with calculate_cost's single computation. There is no explicit when-to-use, when-not-to-use, or named alternative, so it stays at implied guidance.

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 behavioral burden. It discloses the return content (brands plus their MDR rates), which implies a safe, side-effect-free read, but never states read-only semantics, ordering, or whether the list is exhaustive/paginated.

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?

A single compact sentence that front-loads the action and resource, then the payload. No filler, no 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 zero-parameter, zero-side-effect listing tool with no output schema and no annotations, the description covers what it does and what it returns. Minor gaps remain around result ordering and whether the list is complete, but nothing critical to calling it is missing.

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 and the schema is empty, so there is nothing for the description to disambiguate. Baseline of 4 applies for a no-parameter tool.

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?

States a specific verb ('Lista') and resource ('marcas de maquininha disponíveis') and adds the payload ('taxas MDR'), so the agent knows exactly what comes back. It does not explicitly differentiate itself from siblings like compare_brands or get_tiers, which also operate on brand/tier data.

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?

Usage is only implied: 'todas as marcas disponíveis' suggests a discovery/enumeration call, typically a precursor to compare_brands or calculate_cost. There is no explicit when-to-use, when-not-to-use, or named alternative, so the agent must infer the routing.

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. It implies a read-only listing and names the returned fields (ticket médio, volume), but says nothing about whether the set is fixed, ordering, permissions, or response shape.

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?

A single front-loaded sentence with no filler; the resource is stated before the returned attributes. It is efficient, though the terseness borders on under-specification rather than tightened conciseness.

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 output schema, the description is minimally adequate: it names the enumerable tiers and the metrics returned. It leaves gaps around whether all tiers are always returned, ordering, and any auth/context requirements.

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 the baseline of 4 applies; there is no parameter syntax for the description to explain. The stated fields describe output rather than input, which is harmless but adds nothing parameter-wise.

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?

Uses a specific verb ("Lista") and a concrete resource (business profiles: MEI, pequeno, médio, grande) plus the fields returned. An agent can tell it apart from get_brands by the resource alone, though no sibling is named explicitly.

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 statement of when to call this versus get_brands, calculate_cost, or compare_brands, and no prerequisites or exclusions are given. Usage must be inferred purely from the resource name.

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