Consulta de Multas

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

Beyond the annotations (idempotentHint=true, destructiveHint=false), the description adds behavioral context: it describes the browser login flow, the difference between permanent and session-only authentication, and the behavior when called with no arguments (returns a link). No contradiction with annotations.

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 three sentences, informative and generally well-structured. The introductory phrase 'MCP.AI for IDE agents (Cursor, etc.)' adds context but could be trimmed without losing value.

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 an authentication tool with no output schema, the description covers the main use cases (permanent vs session, no-args behavior) and sufficient context for an agent. Return values are implied but not explicitly stated, which is a minor gap.

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%, so the description fully compensates by explaining that the 'token' parameter is a JWT for session-only login, and that omitting it returns the login link. This adds essential meaning beyond the raw 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 clearly states the tool's purpose: authenticate by logging in via browser and copying the access token. It distinguishes itself from siblings like connect and marketplace by focusing specifically on the authentication flow for IDE agents.

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 explains two usage modes: permanent configuration via header and session-only using the token parameter, plus the no-args case to retrieve the login link. It gives clear context on when to use each, though it doesn't explicitly mention alternatives among 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds behavioral context by describing the two output states (connected vs missing credentials), which helps the agent anticipate responses.

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 sentences with a front-loaded purpose statement and concrete examples. 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?

The tool is simple (no params, no output schema, safe). The description fully explains the expected result states, making it complete for an AI agent to invoke and interpret 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?

The tool has zero parameters, and the schema is empty with 100% coverage by default. The description correctly avoids adding parameter details, so the baseline of 4 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 clearly states that the tool 'Returns connection status and URLs' with concrete examples of output states (authenticated:true vs missing credentials). This distinguishes it from sibling tools like authenticate, which presumably initiates connections.

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 this is the tool to check connection status, but it does not explicitly name alternatives or provide when-not-to-use guidance. Sibling 'authenticate' suggests the natural counterpart, but no explicit comparison is 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?

Annotations already signal read-only, idempotent, and non-destructive behavior. The description adds useful context beyond annotations: the consultation is public, requires no RENAVAM, and lists the data categories returned.

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 three focused sentences with the core function front-loaded. It is appropriately sized, though the DETRAN comparison sentence adds a bit of redundancy with the 'PÚBLICA' point.

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 two-parameter read tool, the description covers purpose, public access, and output scope. It remains incomplete because 'completo' is left unexplained and no output format is hinted, which matters since there is no output schema.

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 0% and the description does not explain the 'completo' parameter. Only PLACA is contextually implied by 'pela placa', leaving the boolean parameter's meaning completely undocumented.

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 defines a specific verb and resource: public consultation of vehicle debits/status by license plate. It explicitly names covered data (IPVA, licensing, open fines, restrictions, vehicle data) and distinguishes itself by stating it does not require RENAVAM.

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 provides a clear typical use case ('consultar o próprio veículo') and contextual clues about public vs. authenticated access. However, it does not explicitly compare itself with sibling tools or state when not to use it.

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?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds context by specifying the official source and that it returns the owner's own cadastral data, which goes beyond structured data. No contradiction found.

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 is concise and front-loaded with the core purpose. No wasted words or redundant phrasing.

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 read-only query tool with no output schema, the description covers essentials (what, who, scope) but lacks details on the 'completo' flag and the response structure. Given the official base and safety annotations, it is minimally complete but leaves gaps in parameter usage.

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 description explains that CPF and CNPJ refer to the owner, adding meaning to those parameters. However, the 'completo' boolean parameter is not described, and with 0% schema coverage, the description only partially compensates for understanding the parameters.

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 consults vehicle history (SP) by owner's CPF/CNPJ in an official base. The verb 'Consulta' and resource 'histórico veicular' are explicit, and it distinguishes from sibling tools that focus on fines (multas) rather than full history.

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 implies usage for vehicle history queries by owner identifier but does not explicitly state when to use it over alternatives like multas_veiculos_proprietario. No exclusions or when-not-to-use guidance provided, though the scope (SP) is mentioned.

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?

Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful behavioral context beyond that: it is a public/official-base query, and it enumerates the returned fields. It does not cover pagination or failure behavior, but the read-only safety profile is already disclosed by annotations and reinforced by the description.

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 three short sentences, front-loaded with the main purpose, followed by return contents and access context. Every sentence earns its place and there is no redundant or filler wording.

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?

The description gives a solid overview, lists returned fields, and benefits from read-only annotations in the absence of an output schema. However, it is incomplete as a standalone guide because required TIPO and optional completo are not explained, and there is no explicit guidance on how this tool differs from the closely related multas sibling 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?

Schema description coverage is 0% and the schema has no parameter descriptions or enums. The description meaningfully explains PLACA and RENAVAM ('por placa + RENAVAM'), but it leaves the required TIPO parameter completely unexplained and does not describe the optional completo boolean. This is a significant semantic gap for a tool with sparse schema metadata.

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 specifies a public query for federal-highway traffic fines (PRF) by plate + RENAVAM, listing returned data such as notice, location, date, value, and status. This distinguishes it from sibling multas tools by naming the federal-highway/PRF scope and the required identifiers.

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 provides clear context: use for public consultation of federal highway fines when plate and RENAVAM are available, and it notes access is public/official and intended for vehicle owners. However, it does not explicitly state when not to use it or compare it with sibling tools like multas_historico_veiculo or multas_debitos_veiculo.

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?

Annotations already declare read-only and idempotent hints. The description adds context that the data comes from official SENATRAN/DETRAN channels and is the same as the owner accesses, plus a privacy guarantee. No contradictions with annotations.

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 sentences with no filler. The main verb and resource are front-loaded, and each sentence adds essential scope or privacy 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 simple query with two params, no output schema, and strong annotations, the description adequately covers purpose, scope, and data source. The main gap is the unexplained 'completo' parameter, which prevents a perfect score.

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 has 0% coverage and the description does not explain the optional 'completo' parameter. While CPF is implied, the 'completo' boolean is left ambiguous, and the description does not detail how it affects the query or response. The description only lists output fields, not parameter behavior.

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 queries the CNH status by CPF, listing the specific fields (registration number, category, validity, situation). It distinguishes from sibling tools about vehicle fines and history by focusing on the driver's own license.

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 indicates it's for the driver's own CPF and explicitly notes it does not expose third-party confidential data, implicitly telling agents not to use it for others' information. However, it lacks explicit comparison to sibling tools like 'multas_veiculos_proprietario'.

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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint. The description adds the behavioral note that it queries the titular's data, not third-party tracking, and that it uses an official base. This goes beyond the annotations, but it doesn't discuss potential authorization requirements or response details.

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, front-loads the main purpose, and includes a practical usage note. It is concise and well-structured, though it could be slightly shorter without losing meaning.

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 3-parameter tool with no output schema, the description covers purpose and typical usage but lacks parameter details and any hint about return format. The annotations handle safety, so the description is acceptable for basic invocation but not fully complete for an agent to infer expected outputs or all parameter semantics.

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%, and the description provides no information about the parameters. CPF and CNPJ are self-explanatory, but 'completo' is ambiguous and could mean full details vs. minimal list. The description should explain these, especially the 'completo' flag, to guide correct invocation.

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 lists vehicles registered under a CPF or CNPJ in an official database, using the verb 'lista' (lists) and the resource (vehicles under a document). It distinguishes itself from siblings like multas_debitos_veiculo (which queries debts per vehicle) by focusing on the owner's registration lookup.

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 states typical usage: the owner or fleet manager looks up plates before consulting debts/infractions, and clarifies it is for the data subject, not third-party tracking. This gives a clear context but does not explicitly mention alternatives or when not to use it, though the sibling list provides context.

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?

Annotations already indicate idempotency and non-destructiveness, so the description isn't burdened to repeat those. It adds the reproduction instruction, which is useful, but doesn't disclose other behavioral aspects like what happens after submission (e.g., ticket creation). No contradictions exist.

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 sentences, front-loaded with the primary purpose and a key usage instruction. No wasted words; each 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?

For a simple tool with three parameters and no output schema, the description covers the core purpose and one important usage detail. It could be more complete by elaborating on all parameters and what happens after reporting, but it's adequate for basic operation.

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%, so the description must compensate. It mentions the 'conversation' array for reproduction, but does not explain 'context' or provide details on the required 'message' beyond implying it holds the report content. Insufficient for full parameter clarity.

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 reports bugs, missing features, or feedback, using a specific verb and resource. It distinguishes from sibling tools, none of which handle feedback or bug reporting.

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 on when to use the tool (for bugs/features/feedback) and instructs to include the conversation array for reproduction. It does not explicitly name alternatives, but no siblings serve this purpose, so exclusions are implicit.

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?

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the description doesn't need to repeat safety. It adds context about the specific versions reported but does not describe any potential delays or response format nuances.

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?

Single, complete sentence with no filler. It is front-loaded and immediately conveys the purpose.

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 version query with no parameters and no output schema, the description is fully adequate. It tells the user exactly what information will be provided.

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, so there is nothing to explain. The schema covers everything by having an empty properties object. Baseline for no parameters is 4, and the description aligns with this.

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?

Description clearly states the tool shows current MCP platform and adapter versions. Verb 'Show' is specific, and it identifies the exact resource, distinguishing it from siblings like 'toolkit_info' which likely covers broader info.

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 use when version information is needed, but it does not explicitly mention when not to use it or alternatives. Sibling tools like 'toolkit_info' might serve similar purposes, but no guidance is provided.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description consistently describes a read-only operation. It adds useful context about the exact data returned (installed MCPs, statuses, accounts, tool counts), which goes beyond the raw annotations. No contradictions.

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 sentence, fully front-loaded with the verb 'Returns' and the object 'current toolkit state'. Every phrase adds value, listing the key aspects without unnecessary fluff.

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 read-only status tool with no parameters and no output schema, the description fully conveys the purpose and content of the returned state. It covers the main components (MCPs, statuses, accounts, tool counts) and needs no further elaboration.

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?

There are zero parameters, so the description adds no parameter-specific information, but that's appropriate. Since schema coverage is 100% (vacuously) and there are no parameters to explain, the baseline of 4 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 clearly states the tool returns the current toolkit state, listing specific components (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from sibling tools like connect or show_version, which focus on performing actions or showing version info.

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 the tool is for inspecting state but provides no explicit guidance on when to use it versus alternatives or any exclusions. It doesn't say, for example, 'use this to verify connections before authenticating' or note that it doesn't modify anything. Usage is only inferred from the clear purpose.

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