Regularidade de Transportadora ANTT

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

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds essential context: no credentials are required, the operation is paid with prepaid credits, and the data is public, not private or confidential. It also clarifies LGPD compliance responsibility, all of which are important for an agent's decision.

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 four sentences long, each contributing useful information: purpose, hosting/credentials/payment, data classification, and legal responsibility. It is somewhat detailed but not overly verbose for the content it covers.

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 has no output schema, so the description should cover the operation's purpose, cost, access mode, and data sensitivity, which it does adequately. The main gap is the ambiguous parameter guidance, especially the conflict between the description's implied alternatives and the schema's required fields, which could confuse an agent.

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 mentions 'por CPF, CNPJ ou RNTRC' and uses 'ou' (or), implying that only one of these identifiers is needed. However, the input schema marks all three as required, creating a mismatch. The 'completo' parameter is not described at all, leaving its purpose and effect unexplained, and schema coverage is 0%.

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 'consulta' (consults) the regularity of an ANTT-authorized carrier by CPF, CNPJ, or RNTRC, using a specific verb and resource. This distinguishes it from the unrelated sibling tools like authenticate or marketplace.

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 explains that no credentials are needed and that the consultation is paid with prepaid credits, giving clear context on when it is appropriate to use. It does not explicitly exclude alternatives, but the sibling tools are not similar query tools, so the absence of exclusions is minor.

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 include idempotentHint=true and destructiveHint=false, and the description adds useful context: header-based auth is permanent/non-expiring while pasted token is session-only, and no-args calls return a link. No contradictions, though it doesn't detail side effects or response 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 moderately verbose but every sentence serves a purpose: introducing the target environment, recommending the permanent header approach, and describing the session-only alternative. It is front-loaded with the most critical context and avoids 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 tool with one optional parameter and strong annotations, the description covers authentication flow, two usage modes, and no-arg behavior. It doesn't address return values or error cases, but since there is no output schema, this is acceptable.

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 bears full responsibility. It explains the 'token' parameter as a JWT for session-only login and clarifies that omitting it yields a login link, fully compensating for the schema's lack of property descriptions.

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 indicates the tool is for authenticating with MCP.AI, explaining the browser login flow and token usage. It distinguishes from sibling 'connect' by specifying the target service and method, though it doesn't explicitly state the core action in a single verb-object phrase.

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 provides two usage modes: permanent via header configuration and session-only via token parameter, and states that calling with no args returns a login link. This gives clear when-to-use guidance and explains the alternative approaches.

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. The description adds valuable behavioral details: when all providers are connected, it returns authenticated:true and empty pending[]; when credentials are missing, it returns connect_url and per-install URLs. This goes beyond the annotations without contradicting them.

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-loaded with the primary function, and each sentence provides essential information. The conditional logic is compactly conveyed without unnecessary detail.

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 explains the key return values for both all-connected and missing-credentials scenarios. It omits a potential partial-connection state, but the mention of 'empty pending[]' implies non-empty pending for partial states. Overall, it is sufficiently complete for a simple status-check tool.

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 zero parameters, so the description does not need to explain parameter meanings. The baseline for no parameters is 4, and the description appropriately focuses on the tool's output rather than inputs.

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: 'Returns connection status and URLs.' It distinguishes itself from the sibling 'authenticate' tool by focusing on status/URL retrieval rather than performing authentication. The conditional behavior further clarifies its role.

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 for when to use the tool: to check connection status and obtain URLs when credentials are missing. However, it does not explicitly name alternatives or state when not to use it. The presence of the 'authenticate' sibling implies a complementary relationship, but the description doesn't draw that contrast.

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?

Goes far beyond the annotations, disclosing that invoke runs tools one-off without installing, that auth/payment gaps produce connect/checkout links, and that writes require workspace owner/admin. Also explains installed_in_toolkit vs installed_in_workspace flags. 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 long but dense, with nearly every sentence adding behavioral or usage context. It lacks bullet points and is a single narrative block, but for a 23-parameter tool with multiple action modes, the length is largely justified.

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?

Despite no output schema and 23 parameters, the description comprehensively covers all major actions, the core invocation flow, auth/payment handling, permission requirements, and the separate prompt library. It is sufficiently complete for an agent to select and invoke the tool 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 0%, so the description must compensate. It explains the meaning of action values (search, describe, install, invoke, etc.), tool_id, mcp_id, arguments, prompt fields. However, parameters like limit, immediate, tier_slug, and conversation remain underspecified, so it is not perfect.

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?

Clearly identifies itself as the mcp.ai marketplace and catalog of MCP/tools. It describes the core flow with specific actions (search, describe, invoke, install) and differentiates from sibling tools by being the in-platform catalog and execution layer.

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?

Provides explicit guidance on when to use invoke vs install ('prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT') and mentions alternatives like request_mcp when nothing fits. Also explains when invoke returns connect/checkout links and to retry.

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 safety characteristics (readOnlyHint=false, destructiveHint=false, idempotentHint=true). The description adds the guidance about including the conversation array but does not disclose what happens after submission (e.g., ticket creation, confirmation). This adds some value beyond annotations but lacks deeper behavioral context.

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 concise, with two sentences that front-load the purpose and immediately follow with a usage instruction. No filler or redundant 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?

For a simple 3-parameter tool with no output schema, the description is largely sufficient. It states what the tool does and how to use it. A minor gap is not explaining whether a confirmation or response is returned, but this is not critical for a report-submission tool.

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%, so the description must compensate. It explains the 'conversation' parameter's purpose (for reproduction) but leaves 'message' and 'context' ambiguous beyond their names. Since it adds some meaning for one parameter but not all, a score 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 the tool's purpose with a specific verb ('Report') and resources ('bug, missing feature, or send feedback'). It is distinct from the unrelated sibling tools such as 'authenticate' and 'connect', so there is no ambiguity about when to select this tool.

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 explicit use cases (bug, missing feature, feedback) and instructs to include the conversation array for reproduction. It does not mention alternatives or when not to use, but the sibling tools are clearly unrelated, so clear context is provided without needing exclusions.

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 readOnly, idempotent, and non-destructive. The description adds specific detail about the two version categories (platform and adapter), which is useful beyond the generic annotations. No additional behavioral traits are needed for such a simple read 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 a single, concise sentence that front-loads the action and resource. Every word adds value, with 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?

Given the tool's simplicity, zero parameters, rich annotations, and lack of an output schema, the description is complete enough for an agent to select and invoke the tool 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?

The tool has zero parameters, so the baseline of 4 applies. The description correctly does not attempt to describe parameters that do not exist.

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 uses a specific verb 'show' and names the resource ('MCP platform and adapter versions'). It clearly distinguishes the tool from siblings like authenticate or report_bug, which have different purposes.

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 context is clear: use to display version information. No exclusions or alternatives are mentioned, but the tool's purpose is self-evident and differentiation from siblings is implicit through the specialization.

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. The description adds context beyond those hints by specifying what 'toolkit state' includes (installed MCPs, connection status, accounts, catalog tool counts), which is useful for setting expectations.

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 that gets straight to the point. Every phrase adds information ('installed MCPs', 'connection status', 'accounts', 'catalog tools'), with no wasted words.

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 simplicity (no params, no output schema), the description fully covers the return value by listing all key components. There is no missing context that an agent would need to know before calling.

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 at the parameter level. The baseline for 0 params is 4, and the description already clarifies what the tool reports, making additional parameter semantics unnecessary.

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 uses a specific verb ('Returns') and clearly identifies the resource ('current toolkit state'), enumerating the exact contents (installed MCPs, connection status, accounts, catalog tool counts). This unambiguously differentiates it from siblings like show_version and marketplace.

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 as an informational/status query but provides no explicit when-to-use guidance or alternatives. It does not state 'use this when you need the full toolkit state' or contrast with similar tools like 'show_version' or 'connect'.

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