DETRAN RJ: GRT (Guia de Regularização de Taxas)

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

Annotations indicate idempotent (true) and destructive (false), but the description adds critical behavioral details: adding to config yields a non-expiring connection, while pasting gives a session-only login. It also mentions the process of getting the link, which goes beyond 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 concise but slightly verbose with multiple options, yet it remains well-structured: first the generic process, then the recommended permanent method, then the session-only alternative. It avoids redundancy and is 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?

The description provides enough context to use the tool correctly, including prerequisites (user must log in and copy token) and two usage modes. It does not specify the output/return value, but given the absence of an output schema and the nature of an authentication tool, 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?

The description fully explains the 'token' parameter: it is the JWT to paste, and it elaborates on the invocation scenario ('call with { token: "<jwt>" } after the user pastes'). Even though the schema lacks a description, the tool description compensates completely.

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 as authentication for MCP.AI with IDE agents, providing explicit steps (log in, copy token) and options for using it. It is distinct from the sibling tools (e.g., connect, show_version) by focusing on login/token management.

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 to use the tool: it recommends adding the token to the server config for a permanent connection, or pasting it for a session-only login. It also clarifies invocation patterns (with token or no args to get the link), giving clear usage 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 declare readOnlyHint and idempotentHint, so the description adds value by explaining the state-dependent return values: 'authenticated:true and empty pending[]' versus 'connect_url and per-install URLs'. This goes beyond the annotation hints and clarifies what the tool actually returns in different scenarios, though it could describe edge cases like partial connections.

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 core purpose, and every sentence adds essential behavioral detail. No filler or redundancy exists, making it 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 no parameters and no output schema, the description covers the primary states (all connected vs. missing credentials). It does not explicitly address partial connectivity or other edge cases, but the main use cases are sufficiently documented for an AI 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 description does not need to explain parameter syntax or meaning. The schema already covers 100% of parameters (none), and the description adequately describes the tool's input-independent behavior. A baseline of 4 is appropriate 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?

The description clearly states the tool 'Returns connection status and URLs', identifying the specific resource and action. It distinguishes itself from the sibling 'authenticate' tool by focusing on status rather than performing authentication, making the purpose unambiguous.

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 conditions ('When all providers are connected...' and 'When credentials are missing...') that indicate when the tool is useful for checking connection state. It does not explicitly mention alternatives or when to avoid using it, but the context implies it is the status-check tool among the siblings.

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 provides additional behavioral details beyond the annotations: it is a paid service (prepaid credits), requires no credentials, uses official Brazilian sources, and states that the data is not confidential and falls under LGPD with the client as controller. This goes beyond the simple read-only and idempotent 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?

The description is repetitive, saying essentially the same thing multiple times ('consulta em fonte oficial', 'consulta informação de fontes e órgãos oficiais brasileiros', 'não é dado sigiloso'). It lacks a clear, structured presentation and could be condensed into a single concise sentence 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?

The description does not explain what the tool returns, how to handle errors, or any specific usage details beyond the fact that it is a paid query. There is no output schema and the input parameters are not elaborated. The tool seems simple, but the description leaves many operational aspects unaddressed, making it incomplete for a user unfamiliar with GRT or the service.

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 lists cpf, cnpj, and renavam, but the description does not explain their roles or which are required. Although renavam is marked required in the schema, the description gives no guidance on how cpf/cnpj relate or are used. The field names are self-explanatory, but the lack of any additional meaning or usage context is a clear gap.

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 consults GRT (Guia de Regularização de Taxas) from DETRAN RJ, which is a distinct purpose compared to sibling tools like authenticate or marketplace. The verb 'consultar' and the resource 'GRT' are specific and unambiguous.

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 when one needs GRT information, but it does not explicitly state when to use this tool versus alternatives, nor does it provide usage scenarios or prerequisites. It mentions payment with prepaid credits, which is a relevant usage condition, but not comprehensive 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?

Despite annotations (readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false) not providing much depth, the description discloses critical behavioral traits: invoke runs uninstalled MCPs one-off without bloating the tool list, returns connect links for credentials or checkout links for payment, writes require workspace owner/admin, and search/describe flag installed status. This richly supplements 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 long but well-structured, starting with an overarching definition, then a 'Core flow' sequence, a 'KEY' emphasis on invoke, and then distinct usage guidance for install, list_tools, subscribe/cancel, and the prompt library. Each sentence adds value, but the text is dense and runs on in places; a slightly more scannable structure would improve it.

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 high complexity (14 actions, 23 parameters, no output schema), the description is exceptionally complete. It covers the main workflow, edge cases for auth/payment, permission requirements, the distinction between installed and one-off usage, and the additional prompt library subsystem. It even explains what describe returns (profile with tools, ids, params, pricing, auth) and how search flags installed status.

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 carries the full semantic burden. It explains the meaning of key parameters: action (enumerated flow), mcp_id, tool_id, arguments, prompt_slug, prompt_vars, etc. However, some parameters (limit, immediate, tier_slug, cancel_reason) are not explicitly described, leaving gaps. The compensation is strong for the core use cases but not exhaustive across all 23 params.

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 identifies the tool as 'The official mcp.ai marketplace' with a specific scope: cataloging and running MCPs/tools. It distinguishes itself from siblings by detailing a core flow (search → describe → invoke) and naming distinct actions like list_tools and prompt management. This is a specific verb+resource with strong 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?

Explicit guidance is abundant: 'prefer invoke for a single/occasional use' vs. 'Use install only to make an MCP PERMANENT'. It clarifies when each action is appropriate (e.g., 'list_tools lists what is callable right now', 'report_bug sends feedback', 'request_mcp asks us to build a NEW MCP when nothing fits'). This goes beyond general context and offers clear when-to-use versus 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?

Annotations already indicate readOnlyHint=false, destructiveHint=false, and idempotentHint=true, covering safety and idempotency. The description adds minimal behavioral context beyond stating the action (reporting) and the instruction to include conversation for reproduction. It does not describe side effects (e.g., ticket creation) or any rate limits, but given the annotations cover the basics, a score of 3 is appropriate.

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 core purpose, and contains zero filler. Every sentence earns its place—the first states the action, the second provides the key invocation detail. This is exemplary 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 simple tool with no output schema and basic annotations, the description covers the essential usage (reporting and including conversation) but omits explanation of the 'context' parameter and does not describe the expected response or outcome. It is sufficient for basic invocation but lacks completeness for fully informed use, especially given the absence of parameter descriptions in the 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%, so the description must compensate. It clarifies the 'conversation' parameter explicitly ('Include the conversation array...'), which is helpful. However, it does not mention the 'context' parameter at all, and 'message' is self-evident from the name. The description adds some meaning but does not fully cover all three parameters, so it partially compensates for the lack of schema 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 states the tool's purpose with a specific verb ('Report') and enumerates three distinct use cases (bug, missing feature, feedback). This is concise and unambiguous, and it clearly differentiates from sibling tools like 'authenticate' or 'marketplace' which serve entirely different functions.

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 gives explicit guidance to include the conversation array for reproduction, which helps the agent know how to invoke the tool. However, it does not explicitly state when NOT to use this tool or mention any alternative tool for similar purposes. Given the sibling tools are unrelated, the lack of exclusions is acceptable, but explicit caveats would be stronger.

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 known. The description adds no further behavioral context, but it does not contradict annotations. Since annotations cover safety, a baseline score of 3 is appropriate.

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 with no filler. It is efficiently structured and front-loaded with the key action and scope.

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 tool with no parameters, no output schema, and annotations covering safety, the description is sufficiently complete. It accurately informs the agent of the tool's purpose without requiring additional detail.

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 baseline for 0 parameters is 4. The schema has no properties to describe, and the description adds no parameter-related information needed beyond schema coverage.

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 MCP platform and adapter versions, using a specific verb and resource. It distinguishes from siblings by focusing on version information, though no explicit differentiation from toolkit_info is given, but the purpose is unambiguous.

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?

No guidance is provided on when to use this tool versus alternatives like toolkit_info. The description only states what it does, without any context on preferred usage scenarios or 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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds specific behavioral detail about what the toolkit state includes (installed MCPs, connection status, accounts, tool counts), which goes beyond the annotations without contradicting them. It does not mention rate limits or auth, but annotations cover the safety profile.

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 conveys all necessary information without waste. Every clause adds value, and there is no redundancy with the schema or annotations.

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, no output schema) and the detailed description of return content, the tool is sufficiently complete for an agent to select and invoke correctly. It does not describe return format or failure modes, but these are less critical for a read-only status endpoint.

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 an empty input schema, so the baseline is 4. The description adds no parameter information, but none is needed since there are no parameters to explain.

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 'Returns the current toolkit state' and enumerates the specific data points returned (installed MCPs, connection status, connected accounts, catalog tool counts). This is a specific verb+resource+scope that 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 implies usage when one wants to inspect toolkit state, but it does not explicitly state when to use this tool versus alternatives like show_version. No exclusions or alternative recommendations are provided, so the guidance is only implicit.

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