DETRAN PA: Impressão de CRLV

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

The description discloses behavioral traits beyond the annotations: adding to config creates a permanent connection, pasting provides session-only login, and calling with no args returns a link. It implies side effects (e.g., updating server config) and expectations (user interaction). This goes beyond the idempotentHint and destructiveHint annotations, though it does not detail error handling or security implications.

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 somewhat wordy but conveys all necessary information. It front-loads the purpose and then explains the workflow. The structure is logical, though it could be streamlined (e.g., separating configuration steps from API call options). It is appropriately sized for the complexity of the authentication process.

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 the tool's purpose, usage steps, parameter semantics, and behavioral outcomes. It does not specify the exact return value format (e.g., the link structure) or address potential edge cases. However, given the schema simplicity and annotations, it is sufficiently complete for an authentication 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 schema only defines an optional 'token' string without description. The description adds meaning: if provided, it is a JWT for authentication; if omitted, the tool returns a login link. It also clarifies the token's role in permanent vs. session setup. This greatly enhances parameter understanding beyond the 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: authenticating the MCP server with an IDE agent. It explicitly explains the authentication workflow (browser login, token retrieval, adding to config or pasting for session-only). The verb 'authenticate' and resource context are evident.

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 usage instructions: 'call with { token: "<jwt>" } after the user pastes, or with no args to get the link.' It also contrasts permanent vs. session-only login methods. However, it does not explicitly compare this tool to alternatives (e.g., when to prefer one over another), though the context implies this is the primary authentication method.

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, establishing a safe, non-mutating operation. The description goes beyond these by specifying the exact response variants: 'authenticated:true and empty pending[]' when connected, and 'connect_url for the toolkit and per-install URLs' when credentials are missing. This enriches the agent's understanding of edge-case outputs without contradicting 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 just two sentences, with the primary action stated first and conditional details following. There is no redundancy or filler; every word adds value by clarifying output scenarios. 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 parameterless status checker, the description succinctly covers all normal and edge-case behavior: connected state, missing credentials, and the URLs returned. The rich annotations and straightforward schema mean no additional context is required. The description is fully sufficient for an agent to use this 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 no parameter-specific documentation is needed. Schema coverage is effectively 100%, and the description correctly focuses on output behavior rather than inventing parameter details. 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 opens with a clear verb and resource: 'Returns connection status and URLs,' which precisely states the tool's function. It further elaborates on conditional behaviors (authenticated:true vs. missing credentials) that make it distinct from siblings like 'authenticate' or 'show_version'. This fully differentiates the tool from its peers.

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 detailing what the tool does and when different outputs occur, giving clear context for an agent to decide when to call it. While it doesn't explicitly list exclusions or alternative tools, the purpose is unambiguous and the conditional explanations provide sufficient guidance for typical use cases. It falls short of a 5 because there's no direct mention of 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 mark the tool as read-only, idempotent, and non-destructive. The description adds meaningful operational context beyond annotations: payment model, lack of platform credentials, non-confidential nature of data, and LGPD controller responsibility. No contradiction with annotations was 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?

Three sentences cover the core purpose, cost/auth model, and legal framing with minimal fluff. The purpose is front-loaded, and each sentence contributes distinct information, though the middle sentence is slightly list-like.

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 query tool with three self-descriptive parameters and strong annotations, the description covers purpose, cost, credentials, and legal responsibility. It is slightly incomplete on parameter formats and expected output, but the low complexity and annotations reduce the need for more.

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 mention placa, renavam, or documento_proprietario at all. It therefore adds no parameter-level meaning such as expected formats (e.g., plate format, document type) or constraints, leaving the agent to rely only on parameter names.

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 ('consulta em fonte oficial') and the resource ('CRLV'/'DETRAN PA'), with added scope ('informação de fontes e órgãos oficiais brasileiros'). This is specific and distinguishes the tool from the unrelated platform-management siblings.

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 useful usage context: official source query, no platform credentials required, and prepaid per-query cost. It does not explicitly name alternatives or exclusions, but the sibling tools are platform-level utilities rather than similar query tools, so the context is sufficient.

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 well beyond annotations by explaining side effects (one-off vs permanent install), auth fallbacks (connect link), payment fallbacks (checkout link), and the difference between toolkit/workspace flags. Annotations are not contradicted; the description adds rich 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 a single dense paragraph with run-on sentences and lack of structural breaks. While information-dense, it is not appropriately sized or front-loaded; key points like the prompt library are buried mid-paragraph, making it difficult to scan.

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 23 parameters, no output schema, and 14 actions, the description covers the main flow well but omits details on output structures, the 'resume' action, and several parameter meanings. It is extensive but not complete for such a complex interface.

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 key parameters (action, mcp_id, tool_id, arguments, prompt_vars) via the core flow, but leaves many others (limit, immediate, tier_slug, cancel_reason, report_context, etc.) without explanation, making full parameter semantics incomplete.

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 run engine, with a distinct core flow (search → describe → invoke). It explicitly distinguishes itself from sibling tools by listing marketplace-specific actions like install, subscribe, and search_prompts.

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 when-to-use guidance: prefer invoke for one-off use, use install only for permanent additions, and resort to report_bug/request_mcp when nothing fits. Names alternatives and states permission requirements (workspace owner/admin) for write actions.

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 convey mutation safety (readOnly=false, destructive=false) and idempotency, so the description's main addition is the requirement to include conversation context. It doesn't disclose side effects, duplicate handling, or authentication needs, but the annotations cover the core risk 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 two tight sentences: the first states the action and scope, the second provides a key usage hint. No filler or repeated schema 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 tool with three parameters and no output schema, the description covers the primary purpose and one important parameter. However, it omits clarification of 'message' and 'context', so the tool is not fully self-contained for an agent without additional inference.

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 only clarifies the 'conversation' parameter and leaves 'context' completely unexplained; 'message' is implicit but not formally described. This is inadequate coverage for a schema with zero 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 starts with a specific verb ('Report') plus the resources (bug, missing feature, feedback), and clearly distinguishes this from sibling tools like show_version or authenticate. It concisely defines what the tool accomplishes.

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 enumerates three explicit use cases and adds practical guidance to include the conversation array for reproduction. While it doesn't mention when not to use it or point to alternatives, the stated scope gives clear context for selection.

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, covering the safety profile. The description adds specificity by naming what versions are shown (platform and adapter), but does not disclose additional behavioral traits beyond that. It does not contradict 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 a single, concise sentence that conveys the exact purpose without any wasted words. It is front-loaded and to the 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?

This is a simple version-reporting tool with no parameters, no output schema, and safety annotations. The description fully explains what the tool returns (platform and adapter versions), which is sufficient for an agent to select and invoke it 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, and schema coverage is 100% (vacuously). Baseline for 0 params is 4. The description does not need to compensate for any parameter gaps, and it does not.

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 'Show the current MCP platform and adapter versions' uses a specific verb ('show') and resource ('MCP platform and adapter versions'), clearly distinguishing it from sibling tools like authenticate, connect, and marketplace. It unambiguously states 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?

Usage context is implied by the tool's purpose: use when you need version information. However, there is no explicit guidance on when to use this tool versus alternatives, nor any conditions or prerequisites. It is simple enough that implied usage seems sufficient but not exceptional.

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 well covered. The description adds the specific content of the returned state (installed MCPs, connection status, accounts, catalog tool counts), which is useful but does not go beyond what annotations provide in terms of behavioral traits like side effects or performance.

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 lists all key information without any fluff. It is front-loaded with the main purpose and enumerates the specific data points returned, 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?

Given the tool has no parameters, no output schema, and strong annotations, the description is complete enough. It clearly states what the tool returns, which is sufficient for an informational read-only tool. It could potentially mention that it is a snapshot or that it may require prior authentication, but that is not critical given the 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 tool has zero parameters, and the schema description coverage is 100% (vacuously). The description does not need to explain parameters since there are none, and it clearly states what the tool returns, which is the main semantic content. 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 the current toolkit state, listing specific elements: installed MCPs, connection status, connected accounts, and catalog tool counts. This is a specific verb+resource combination that distinguishes it from sibling tools like authenticate or connect.

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 a read-only informational tool for checking the toolkit state, which is clear from the context. However, it does not explicitly state when to use it versus alternatives, such as when to use show_version or marketplace, though the purpose is distinct enough that usage context is reasonably clear.

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