DETRAN DF: Veículo (Mobile)

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

Annotations already indicate idempotent, non-destructive, non-read-only behavior; the description adds useful context about token permanence and session-only fallback. It does not disclose the exact response when a token is passed, but this is a minor gap for an authentication action.

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 informative, with three sentences covering flow, permanent setup, and session-only usage. It is slightly run-on, but every clause adds necessary operational 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 adequately covers the authentication workflow, both login modes, and the no-args behavior. Explicit return/error behavior is missing, but the low complexity and annotations make the description sufficiently 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?

Schema coverage is 0%, so the description fully compensates by explaining the optional token parameter is a pasted JWT for session-only login, and that calling with no arguments returns the browser login link. This gives the agent complete actionable semantics for the single parameter.

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 with MCP.AI by logging in via browser and obtaining/using an access token. It provides concrete invocation details, but it does not explicitly distinguish itself from the sibling 'connect' 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 gives explicit guidance on two usage modes: permanent config-based authentication via Authorization header versus session-only login by pasting a token. It does not mention when not to use the tool relative to siblings, but the mode-selection guidance is clear.

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 it as read-only and non-destructive. The description adds clarity on the return values in different scenarios, enhancing transparency without contradicting 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, using two straightforward sentences. Every word adds value, and it is 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 tool with no parameters and a simple purpose, the description fully covers expected behavior and return values. It is complete enough for an agent to understand what to expect.

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 is empty, so there are no parameters to explain. Baseline for zero parameters is 4, and the description doesn't need to add parameter details.

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 also details the two outcomes (authenticated true or connect_url), which is specific and distinguishes it from sibling tools like authenticate.

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 explains behavior but does not explicitly state when to use this tool versus alternatives. It implies usage for checking connection status, but lacks explicit guidance like 'use this instead of authenticate when checking connectivity.'

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 the tool is read-only, idempotent, and non-destructive. The description adds valuable context beyond annotations: it is a paid per-query operation, uses prepaid credits, requires no platform credentials, queries non-confidential official data, and includes LGPD/controller responsibilities. 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 starts with the purpose and keeps each sentence informative. Some legal and compliance details could be trimmed for a pure tool definition, but they provide useful operational context. Overall, it is reasonably concise and 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 2-parameter read-only tool, the description covers key operational aspects: official source, payment model, credentials, and legal responsibility. However, with no output schema and no parameter descriptions, the agent still lacks concrete information about the expected result and valid input formats, leaving meaningful 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?

The input schema has zero description coverage for both 'placa' and 'renavam', and the description does not compensate. It does not explain what RENAVAM is, expected formats, examples, or constraints. The parameter names are somewhat self-explanatory for a Brazilian vehicle tool, but the description adds no param-level meaning.

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 ('consultar') and resource ('DETRAN DF: Veículo (Mobile)'), making the core operation clear. It distinguishes this from the generic sibling tools like authenticate and marketplace, though it does not state exactly which vehicle information fields are returned.

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 useful usage context: this is a paid consultation using prepaid credits, requires no platform credentials, and queries official Brazilian sources. However, it does not explicitly state when to use this tool versus alternatives or when it should not be used.

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 discloses key behavioral traits: invoke runs tools even when not installed, returns connect/checkout links on missing credentials/payment, and requires write permissions for install/uninstall/subscribe/cancel. While annotations already indicate non-read-only and non-destructive, the description adds significant context about side effects and retry flows, with no contradiction.

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 packs a lot of information, but it lacks visual structure like bullets or action-by-action breakdown, making it less scannable. Still, each sentence adds relevant detail and there is no filler; it is appropriately sized for the tool's complexity.

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 main workflows (search/describe/invoke/install), billing actions, permissions, and the prompt library, including edge cases like authentication and payment. However, it omits some actions (e.g., 'resume') and parameters (e.g., 'immediate', 'tier_slug'), and doesn't describe return values for most actions, leaving some gaps for such 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?

The input schema provides zero descriptions, so the description must cover parameter meaning. It does explain the action parameter and links tool_id, arguments, prompt_vars, and prompt_slug to specific workflows, but many parameters (immediate, tier_slug, conversation, request_details) remain unexplained, leaving ambiguity for a 23-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 identifies the tool as the mcp.ai marketplace, the in-platform catalog and execution layer for MCPs/tools. It explicitly lists the core flows (search, describe, invoke, install) and example capability requests, making its purpose unambiguous and distinct from narrower 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 provides explicit guidance on when to use each action, e.g., 'prefer invoke for a single/occasional use' vs 'install only to make an MCP PERMANENT', and explains the list_tools action as listing what is callable now. It also details the auth/payment fallback behavior and owner/admin requirement for writes, giving an agent clear conditions for use.

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 provide readOnlyHint=false, destructiveHint=false, and idempotentHint=true, covering the core behavioral traits. The description adds the instruction to include conversation history but does not describe side effects or what happens after reporting. Since annotations are present, the description's minimal extra context keeps the score at baseline 3—it neither contradicts nor significantly enhances.

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 concise two-sentence structure, with the first sentence front-loading the purpose and the second providing actionable guidance. Every word is necessary, and there is no redundancy or fluff, achieving high efficiency.

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 is simple (3 parameters, no output schema, no nested objects), and the description covers the purpose and the key reproduction hint. Annotations supply the remaining behavioral context. It does not need to elaborate further, making it complete for the tool's complexity.

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 mentions the conversation array explicitly ('Include the conversation array with recent messages for reproduction'), adding meaning to the 'conversation' parameter. However, it does not explain the 'context' parameter, and 'message' is self-evident. The description partially adds value beyond the schema but leaves some parameters vague, warranting a middle score.

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 a bug, missing feature, or send feedback') and identifies the resource. It distinguishes itself from sibling tools like authenticate, connect, or marketplace by focusing on issue reporting, making it unambiguous for an agent to select.

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 explains when to use the tool (for reporting bugs, missing features, or feedback) and explicitly instructs to include the conversation array for reproduction. However, it does not explicitly state when not to use it or mention any alternative tools, though the context makes the usage clear.

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 minimal context about what information is shown (platform and adapter versions) but does not disclose any other behavioral traits such as authentication requirements or response format. With annotations providing the core safety information, the description adds some value but not extensive transparency.

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 clear sentence that states exactly what the tool does without any fluff. It is front-loaded with the action and resource, making it easily digestible. No unnecessary words or repetition.

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 version-checking tool with no parameters, no output schema, and safety annotations, the description is adequately complete. It conveys what the tool shows, and since there are no params or side effects, nothing else is strictly needed. However, it could hint at the return type or typical usage patterns, but given the simplicity, a score of 4 is appropriate.

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 description coverage is 100%. According to the rubric, the baseline for 0 parameters is 4. The description does not need to explain parameters, and it doesn't, so this score reflects the minimal requirement.

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 exact purpose: to show the current MCP platform and adapter versions. It uses a specific verb ('Show') and resource ('MCP platform and adapter versions'), making it distinct 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 provides no guidance on when to use this tool versus alternatives. It does not mention scenarios where checking versions is necessary, nor does it reference sibling tools or exclusions. A simple statement of purpose without contextual use cases warrants a low score.

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, idempotentHint, and destructiveHint false. The description adds concrete context about the returned state, including specific data elements (installed MCPs, connection status, accounts, tool counts). This exceeds what annotations provide and fully discloses the tool's 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 a single, well-structured sentence that front-loads the purpose ('Returns the current toolkit state') and lists the specific details without redundancy. Every clause 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 tool has no parameters, no output schema, and simple read-only semantics, the description fully explains what the tool returns. It covers all relevant aspects and leaves no ambiguity for the 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 tool has zero parameters, and schema coverage is trivially 100%. Baseline for zero parameters is 4, and the description appropriately does not need to elaborate on parameters. No additional semantic detail 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 uses a specific verb ('Returns') and resource ('toolkit state'), and enumerates the specific details (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from sibling tools like `authenticate` or `connect`, which perform actions.

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 toolkit state) but does not explicitly state alternatives or exclusions. It is clear enough from context, and no sibling shares similar functionality, so a clear usage context is present without explicit when-not guidance.

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