DETRAN MT: Impressão de CRLV

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

Annotations already indicate idempotent/non-destructive behavior; the description adds context about browser login, JWT token submission, permanent vs. session-only auth, and link generation. It does not mention token expiration or response details, but it covers the key behavioral traits.

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 and front-loaded, presenting the core authentication flow first and then necessary variants. Every sentence adds practical value 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?

For a simple one-parameter tool with no output schema, the description gives strong contextual coverage: how to launch, when to use config, when to use a token, and what no-args calls do. It stops short of describing exact response/return behavior, which would make it fully complete.

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 only defines `token` as a string with no description. The tool description fully compensates by explaining the token is a JWT, when to pass it, and what happens when the call is made with no arguments.

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 explains the tool's purpose: authenticating with MCP.AI via browser login and an access token. It distinguishes the tool from siblings by covering login link generation, token pasting, and config-based permanent authentication.

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 usage guidance: prefer config header for a permanent connection, use the tool with a token for a session-only login, and call with no args to get a login link. This effectively tells the agent when and how to invoke the tool.

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 clear. The description adds useful context about the two possible states (all connected vs. missing credentials) and the URLs returned, which goes beyond the annotations. However, it does not detail the exact structure of the response or any potential side effects, but given the annotations, this is adequate.

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 purpose, and every sentence adds value. It efficiently explains the two states and the URLs without any 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?

Given the tool has no parameters, no output schema, and simple annotations, the description is complete enough. It explains the two possible outcomes and the URLs, which is sufficient for an agent to understand what to expect. It could mention the format of the URLs or the exact response structure, but that is not critical for a 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 tool has zero parameters, so the description does not need to explain parameter semantics. The schema coverage is 100% (vacuously), and the description focuses on the output behavior, which is the relevant information for the agent. Baseline 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, and distinguishes it from siblings like authenticate and toolkit_info by focusing on status reporting. It could be more specific about the exact resource (e.g., 'connection status for the toolkit'), but it is not vague.

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 when to use it (to check connection status) but does not explicitly contrast with alternatives like authenticate or toolkit_info. It provides context about what it returns in different states, but no explicit when-not-to-use 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 readOnly/idempotent/non-destructive. The description adds valuable behavioral context beyond annotations: pay-per-query cost, non-confidential nature, and LGPD compliance responsibilities (client is data controller). This is meaningful supplementary information, though return format is not described.

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 (three sentences), front-loaded with purpose, and each sentence adds distinct information (purpose, cost/hosting, legal/confidentiality). No redundant wording, though it could be slightly more 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?

With no output schema, the description should explain what the tool returns (e.g., a printable CRLV document), but it does not. It covers payment, confidentiality, and legal responsibilities, but lacks parameter relationship context (e.g., renavam required with placa) and any indication of response format. It is adequate for a simple query tool but leaves important gaps.

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 compensate by explaining parameter meanings, required combinations, or example values. The parameter names (placa, renavam, cpf, cnpj) are somewhat self-explanatory but lack Brazilian-domain context that would help an AI agent correctly use them.

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: 'Impressão de CRLV, consulta em fonte oficial' (CRLV printing, query in official source). This specifies a unique resource (CRLV) and action (consult/print), and it is easily distinguished 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?

The description gives context that the tool requires prepaid credit and is hosted without platform credentials, and it clarifies the data is not confidential. However, it does not explicitly state when to use this tool over alternatives or provide exclusions, though siblings are unrelated platform utilities.

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 richly discloses behaviors beyond given annotations: invoke works without installing the MCP, returns connect links for missing credentials and checkout links for unpaid usage, and writes require owner/admin. It also explains how installed status is flagged in search/describe results.

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 dense paragraph that covers both MCP and prompt library functionality. It is long but information-dense with no fluff; however, a more structured layout would improve scannability.

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 covers most actions (search, describe, invoke, install, list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt library actions), but omits explicit details about 'resume' and 'uninstall'. It also doesn't address the 'conversation' parameter. Overall, it is quite complete for a complex 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?

With 23 parameters and 0% schema description coverage, the description must compensate. It explains the 'action' parameter and implies usage of mcp_id/tool_id/arguments, but does not detail the format or purpose of many parameters like limit, query, conversation, report_context, request_details, or prompt_vars. It provides only partial compensation.

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' and explains its dual role as catalog and execution engine. It distinguishes itself from siblings by explicitly covering capability discovery and execution, with a core flow of search → describe → invoke.

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 when-to-use guidance, including 'prefer invoke for a single/occasional use' versus 'install only to make an MCP PERMANENT', and mentions alternatives like list_tools for what is callable now. It also clarifies permission 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?

Annotations already establish that the tool is not read-only, not destructive, and idempotent. The description adds the useful behavioral cue to include the conversation array for reproduction, but it does not disclose what happens after submission, whether results are returned, or any side effects beyond what annotations convey.

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 concise sentences with the purpose front-loaded and the important reproduction guidance in the second sentence. Every sentence earns its place, and there is no filler or redundant repetition of schema details.

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 scalar parameters and no output schema, the description covers the core purpose and the most important reproduction detail. It leaves 'message' and 'context' semantics partly implicit, but the required message is reasonably inferable from the tool's purpose, making the description adequate overall.

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 for explaining parameters. It only explains the purpose of 'conversation' ('include the conversation array with recent messages for reproduction'); the required 'message' parameter and optional 'context' parameter receive no semantic explanation.

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 action: 'Report a bug, missing feature, or send feedback.' It names the verb and the resource/object (bug, feature request, feedback), making the purpose unambiguous and distinct from the unrelated sibling tools.

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 clear context for when to use the tool: whenever the user is reporting a bug, requesting a missing feature, or giving feedback. It does not explicitly list alternatives or exclusions, but the sibling tools are unrelated, so no strong competing tool is evident.

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 establish the safety profile. The description adds useful context by specifying exactly what version information is returned (MCP platform and adapter versions), going 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 a single concise sentence that directly states the tool's function without any filler or repetition. Every word earns its place, making it highly efficient.

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 parameterless, read-only, idempotent tool with no output schema, the description is complete. It specifies what the tool shows (current MCP platform and adapter versions), and given the annotations and sibling context, no additional details are required.

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 schema is already complete with 100% coverage. The description provides all necessary context for the parameterless interface, aligning with the baseline of 4 for 0-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 uses a specific verb 'Show' and clearly names the resource: 'current MCP platform and adapter versions.' This precisely distinguishes it from sibling tools like authenticate or marketplace, leaving no ambiguity about what the tool does.

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 this tool when you want to know the current platform and adapter versions. While it doesn't explicitly name alternatives or exclusions, the description implies the appropriate usage scenario, and given the simple nature of the tool, no further guidance is needed.

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 annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is known. The description adds value beyond annotations by specifying the exact contents of the returned state (installed MCPs, connection status, accounts, catalog tool counts). This gives the agent a clear idea of what to expect without repeating the annotation information.

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 is front-loaded with the core action ('Returns the current toolkit state') followed by the specific data items. Every phrase contributes meaning, with no redundancy or filler. It is concise 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 simplicity of the tool (no parameters, no side effects, no output schema required for such a straightforward read operation), the description fully covers what the tool returns. It lists all the key components of the state, which is sufficient for an agent to understand the tool's behavior. The description is complete for its context.

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 no parameters, there is nothing to document. The baseline for 0 params is 4, and the description does not need to add parameter details. It correctly implies that no input is required.

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 the current toolkit state. It specifies the exact information included (installed MCPs, connection status, connected accounts, catalog tool counts), making it distinct from siblings like 'show_version' (just version) and 'authenticate' (auth flow). The verb 'returns' is explicit and the resource is well-defined.

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 by stating what it returns, but it does not explicitly say when to use this tool versus alternatives. There is no mention of when not to use it or comparisons to sibling tools. For a simple info tool this might be acceptable, but explicit guidance on when to call it (e.g., 'use this to check connectivity before other operations') would be helpful.

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