ANTT: Transportador

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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds substantial behavioral context beyond this: it clarifies hosting, the absence of credential requirements, the pay-per-query prepaid model, that data equals what's publicly available to citizens, and LGPD controller responsibility. This enriches the agent's understanding of side effects, trust, and legal constraints without needing the 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 fits into a single run-on sentence but remains compact, packing hosting, credentials, payment, data source, and LGPD into roughly 50 words. It's not structured with bullets or separate sentences, which slightly harms scannability, but every clause carries meaningful information, keeping it appropriately concise.

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 there is no output schema and zero parameter documentation, the description needed to explain the operational contract—such as how to structure a query, what response to expect, or error behavior—but instead focuses on legal and business disclaimers. It's functionally incomplete for an agent to invoke successfully without prior knowledge.

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?

With a schema description coverage of 0%, the description should have compensated for the three parameters (cpf, cnpj, rntrc), but it provides zero explanation of their meanings, formats, or optionality. The agent is left guessing whether any combination is required or how the parameters interact, a critical gap for a data-lookup 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?

The description uses the verb 'consulta' (query) and specifies the resource as 'Transportes' from official Brazilian sources, making it clear this is a read-only data lookup tool. It distinguishes itself from generic siblings like 'authenticate' and 'marketplace' by being the only data-query tool, and it clearly states the scope ('fonte oficial').

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 implicit guidance: it mentions the tool queries official sources and is prepaid with platform credits, implying use cases around compliance and legitimate data access. However, it never explicitly states when to use this over alternatives, names no alternative tools, and offers no exclusions or prerequisites beyond the absence of platform credentials.

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?

The description goes beyond annotations by explaining the two login modes (permanent vs session) and the behavior of calling with no args (returns a link). It does not contradict annotations (readOnlyHint false, idempotentHint true). It adds useful context about token storage and expiration, though it does not detail failure outcomes.

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 long but well-structured: it starts with the tool's context, then lists the default best practice, then the session alternative. Every sentence adds value, and the format is clear. It could be slightly tighter but is appropriately detailed.

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, but the description sufficiently covers the use cases and parameter behavior. It lacks explicit details about the response or error handling, but for an authentication tool, the provided instructions and context are adequate given the simple scope and the presence of annotations.

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 schema has no description for the 'token' parameter, and schema coverage is 0%. The description compensates by explaining that 'token' is a JWT to paste, that it's optional (with no args returns a link), and by specifying the context (session-only login). This adds 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: to authenticate the user with MCP.AI via browser login and token exchange. It provides specific methods (config header or session token) and differentiates from the sibling tool 'connect' by focusing on authentication rather than connection setup.

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 explicitly explains when and how to use the tool: 'log in in the browser, copy the access token' and offers two usage modes with clear step-by-step instructions: adding to config as a permanent header or pasting a session token. It also notes the no-args call to get the link, giving clear 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?

Annotations already disclose read-only, idempotent, non-destructive. Description adds conditional behavior (all connected vs missing credentials) and return values, providing context beyond the safe operation hints.

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 compact sentences, front-loaded with main purpose, then scenario details. Zero 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?

With no params and no output schema, the description covers the two primary outcomes. However, partial connection states (some providers connected, some missing) are not explicitly addressed, leaving minor ambiguity.

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?

No parameters exist, so schema coverage is trivially 100%. Baseline for zero parameters is 4; description need not add anything.

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?

Clear verb 'Returns' with resource 'connection status and URLs'. Distinct from siblings like 'authenticate' and 'show_version' by focusing on connection state, not auth or version.

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 (check connection status), but does not explicitly contrast with alternatives like 'authenticate'. No exclusions or when-not-to-use 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?

Goes beyond annotations by explaining that invoke runs tools even when not installed, and that it may return connect or checkout links. It also discloses admin/owner requirements for write actions, adding significant behavioral context absent from the 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 dense and long, but necessary given the tool's 14 actions and two subsystems. It is logically organized from core flow to specific behaviors and prompt library, though it could benefit from bullet points for scannability. Every sentence adds 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?

Given the complexity and absence of an output schema, the description is quite complete: it explains all major actions, special cases (credentials, payments), and auth requirements. It does not detail return formats for each action, but the overall behavior is well covered.

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?

With 23 parameters and 0% explicit schema coverage, the description compensates by explaining the action enum and the general data flow (search → describe → invoke). It covers key parameters like tool_id and arguments, but does not individually document all parameters; however, the main usage patterns are clear.

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 defines the tool as the official mcp.ai marketplace, naming its dual role as catalog and execution engine. It lists specific actions (search, describe, invoke) and covers the prompt library, fully distinguishing it from sibling tools like authenticate or report_bug.

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 usage guidance: 'prefer invoke for a single/occasional use', 'use install only to make an MCP PERMANENT', and clarifies when to use list_tools or request_mcp. It also explains the behavior when credentials or payment are needed, and notes admin requirements for writes.

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?

The description adds value beyond annotations by explaining that the conversation array is needed for reproduction. It doesn't contradict annotations (readOnlyHint false, idempotentHint true), and the write nature is implied. It does not describe post-action behavior, but the annotation already indicates mutating operations.

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: the first declares the purpose, the second provides a key usage instruction. It is front-loaded, scannable, and contains no fluff. Every word 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?

Given the tool's simplicity, no output schema, and annotations that cover basic behavior, the description adequately explains the core usage. The only missing piece is the exact purpose of the 'context' parameter and the fact that 'conversation' is a JSON string. Overall, it is sufficient for an agent to use the tool correctly without external documentation.

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%. The description mentions the 'conversation array' but does not clarify that the schema stores it as a string (likely JSON), nor does it explain the 'context' parameter. 'message' is self-explanatory, but the general lack of parameter explanations means the description only partially compensates for the absent schema documentation.

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 action ('Report a bug, missing feature, or send feedback') and the resource (issues/feedback). It distinguishes itself from sibling tools like authenticate and marketplace, which have entirely 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 description provides context for when to use the tool by instructing to include the conversation array for reproduction. While it doesn't explicitly mention alternatives or exclusions, the guidance is clear enough for the intended use case, and there are no directly competing 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, which fully convey the behavioral profile. The description adds no extra context beyond the annotation-provided safety guarantees, so it meets the baseline without additional value.

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 concise sentence that fully conveys the tool's function without wasted words. It is appropriately front-loaded and easy to parse.

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 parameters, no output schema), the description fully covers what it does. Annotations already provide safety and idempotency context, so no further elaboration is needed.

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)Skip the schema coverage is 100% vacuously. The description needs no parameter details because there are none. Baseline of 4 is appropriate for zero-parameter tools.

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 shows current MCP platform and adapter versions, using specific verbs and a clear resource. It is distinct from siblings like connect or marketplace, which serve entirely 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?

Though no explicit when-to-use guidance is provided, the tool's purpose is self-explanatory—it is a simple informational command. For a version display with no parameters, usage context is implicit and unambiguous.

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 by enumerating the exact contents of the response (installed MCPs, connection status, accounts, catalog counts), which is useful beyond the annotations and clarifies what information the agent can 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 a single, well-structured sentence that efficiently lists the key output components without excess verbiage. It is fully front-loaded and contains no unnecessary 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?

For a simple read-only information tool with no parameters needing documentation anything, the description is complete. It explicitly lists all the information the agent will receive, which is sufficient for invocation and interpretation. The annotations further support safety expectations, and no output schema is present, so the description's enumeration is the primary source of response insight.

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 no parameters, and the description provides full coverage of what the tool returns. Since there are no parameters, the schema is trivially completeholistically, and the description adds no parameter-related meaning but also does not need to. The baseline for zero parameters is 4, which is justified.

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 with specific details (installed MCPs, connection status, accounts, catalog tool counts). It uses a specific verb and resource, and the scope is well defined. This distinguishes it from sibling tools like authenticate or connect, which are action-oriented.

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 does not explicitly state when to use this tool versus alternatives. However, the nature of the tool (read-only state inspection) is self-evident from the descriptionate. It implies usage for checking toolkit status, but no explicit exclusions or alternative recommendations are provided.

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