DETRAN MT: Veículo

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

Annotations provide minimal behavioral info (idempotentHint=true, readOnlyHint=false), so the description carries the burden. It discloses that calling with 'token' does a session-only login, with no args returns a link, and that config-based tokens are permanent/non-expiring. This adds meaningful context beyond the annotations without 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 reasonably concise, with the main purpose in the first sentence and clear breakdown of usage options in the remainder. Each sentence adds value, though the phrasing is slightly verbose (e.g., 'Best: add it to this server's config...'). Overall, it is well-structured and front-loaded.

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 (one optional param, no output schema), the description covers the essential scenarios: permanent vs session login, and how to obtain the link. It provides enough context for an agent to invoke it correctly, though it omits details about token expiration or error handling, which are not critical for basic usage.

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 one optional 'token' parameter with no description (0% coverage). The description compensates by explaining that it expects a JWT and its role in session-only authentication, and explicitly shows the call format '{ token: "<jwt>" }'. This gives the agent enough semantic understanding to use the parameter correctly, though it doesn't mention validation or error cases.

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 IDE agent to MCP.AI by logging in and obtaining an access token. It specifies the verb (authenticate) and the resource (MCP.AI), and distinguishes it from siblings like 'connect' or 'marketplace' by focusing solely on the authentication flow.

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 it: either add the token to the server config for a permanent connection, or paste a JWT for a session-only login, or call with no arguments to get a login link. It clearly communicates the three usage modes and their purposes, leaving no ambiguity about when to choose which.

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 (readOnlyHint, idempotentHint, destructiveHint) already cover safety profile, so the description adds value by describing the conditional behavior: returns authenticated:true and empty pending[] when connected, else returns connect_url. This provides concrete behavioral detail beyond 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 two sentences, front-loaded with the primary purpose ('Returns connection status and URLs') and immediately provides conditional outcomes. No fluff, every sentence 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 parameters, no output schema), the description covers both states (connected vs. missing credentials) and the key fields (authenticated, pending, connect_url). It is complete for a status-check tool, though it could mention if URLs differ per provider.

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 parametersholistically, and schema coverage is 100% (no parameters). Since the description explains output conditions thoroughly, it adds semantics for a tool with no inputs, matching the baseline for 0 parameters.

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 returns connection status and URLs, specifying details like 'authenticated:true' and empty 'pending[]' when connected. It distinguishes itself from sibling tools by focusing on connection status, though it could be more explicit about differentiating from '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 implies usage: to check connection status and retrieve URLs when credentials are missing. It provides context on when different outputs occur (all providers connected vs. credentials missing), but does not explicitly state when to use this vs. 'authenticate' or 'toolkit_info', which are 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?

In addition to the read-only/idempotent annotations, the description discloses important behavior: payment/prepaid credit requirement, absence of platform credentials, use of official non-confidential data, and LGPD responsibility. This materially improves an agent's understanding of side effects and obligations.

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 compact but dense paragraph that front-loads the core function, then adds necessary cost, auth, and legal context. Every sentence contributes useful operational information; there is no padding or redundant boilerplate.

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, the description conveys purpose, cost, auth, and legal expectations. However, there is no output schema and no mention of result contents, failure behavior, or parameter relationships, leaving some uncertainty about how to interpret the response.

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, cpf, or cnpj or their intended roles. The parameter names are somewhat self-explanatory, but the description provides no format, combination rules, or why CPF/CNPJ are optional, so it only partially compensates for the missing 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 a specific action ('consulta') and a specific resource ('DETRAN MT: Veículo') in an official source. This distinguishes it from unrelated sibling tools such as authenticate and marketplace, so an agent can see this is a vehicle data lookup.

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 usage context and prerequisites: it is hosted by the platform, requires no platform credentials, and is charged per query using prepaid credits. It does not explicitly state exclusions or alternative tools, but the context is sufficiently clear for the intended use case.

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?

Beyond the annotations (readOnlyHint=false, etc.), the description reveals critical behaviors: invoke runs one-off without installing the MCP, returns a connect link when credentials are needed, returns a checkout link when the wallet is empty, and that writes require workspace owner/admin. It also explains that install/subscribe/cancel modify billing and toolkit state, which is rich context the annotations do not provide.

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 dense and front-loaded with the core flow and key behavior. It efficiently covers 14 actions and two major domains (MCPs and prompt library) without wasting words, though a bulleted structure could improve scannability. Every sentence adds value, so it earns a high score.

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 complexity (23 parameters, no output schema, limited annotations), the description is exceptionally complete. It explains end-to-end flows, authentication/billing edge cases, permission requirements, and even the prompt library's shareable-link behavior. It gives agents enough context to select actions and handle typical scenarios 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?

Although the schema has 0% description coverage, the description compensates by explaining the core action parameter and key parameters like mcp_id, tool_id, arguments, and immediate within the context of the search/describe/invoke flow. It does not detail every parameter (e.g., cancel_reason, prompt_vars), but the action-oriented explanation makes the most important semantics 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 states this is the official mcp.ai marketplace catalog and execution engine, with specific verbs like 'search', 'describe', 'invoke', and 'install'. It distinguishes itself from siblings by covering discovery, one-off execution, permanent installation, billing, and prompt library actions, leaving no ambiguity about its role relative to the other 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 explicitly explains when to use invoke vs install, noting 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'. It also provides the core flow (search → describe → invoke) and mentions alternative actions like list_tools for currently callable tools, and request_mcp for building new ones, giving clear decision 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 indicate the tool is not read-only (readOnlyHint=false), is idempotent (idempotentHint=true), and non-destructive. The description adds guidance about including the conversation array, which is helpful, but it does not disclose what happens after reporting (e.g., whether a ticket is created, whether confirmation is returned). With annotations present, the description adds minimal behavioral context beyond 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, front-loaded sentence that states the purpose and the key parameter guidance. No filler or redundancy; 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?

For a simple feedback tool with 3 parameters, the description conveys the main purpose and the conversation requirement, but it does not explain the 'context' parameter or indicate what happens after submission (no output schema exists). It is minimally adequate but not fully informative.

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 explains the 'conversation' parameter ('with recent messages for reproduction'), leaving 'message' and 'context' undefined. The parameter list is three items, but the description is insufficient for two of 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 action and target: 'Report a bug, missing feature, or give feedback.' It also instructs to include conversation history, making the function unambiguous. It is distinct from sibling tools like 'authenticate' 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?

No explicit guidance is provided regarding when to use this tool versus alternativesais. There is no mention of when not to use it or any context such as 'if you encounter an error.' The description only states what it does, not when to invoke 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 declare readOnlyHint, idempotentHint, and destructiveHint, so safety profile is clear. The description adds the specific content (platform and adapter versions) beyond annotations, offering context about what the tool reports.

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?

A single, clear sentence that fully expresses the tool's function without fluff. Front-loaded with the action verb 'Show', no 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?

Given the tool has zero parameters accentric, simple purpose, and annotations cover safety, the description is adequately complete. No output schema is present, but for a trivial version info tool, not needed. It clearly states what information is returned.

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?

There are 0 parameters, so no parameter documentation is needed. Per the rubric, a 0-parameter tool gets a baseline of 4. No additional parameter semantics 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 ('Show') and resource ('current MCP platform and adapter versions'), clearly distinguishing it from siblings like 'toolkit_info' or 'connect'. It immediately conveys the tool's exact purpose.

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 this tool (when needing version information) and its simple scope. It doesn't explicitly mention alternatives or when-not-to-use, but given the tool's simplicity and zero parameters, this 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?

Annotations already indicate read-only and non-destructive behavior. The description adds context by detailing the returned data, which supplements the annotation information without contradicting it. No further side effects are implied.

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 immediately conveys the tool's purpose and output content without unnecessary verbosity or ambiguity.

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 fully specifies what the tool returns: installed MCPs, connection status, accounts per MCP, and catalog tool counts. This is sufficient for a getter without an output schema, and it stands alone even without explicit sibling comparisons.

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, so there is nothing to explain. The schema coverage is trivially 100% and the description correctly reflects that no input is needed.

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, including installed MCPs, connection status, accounts, and catalog tool counts. This is specific and distinct from sibling tools like show_version, which likely focuses on version info only.

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. It is implied as a general state inspection tool, but no clear guidance or conditions (e.g., 'use when you need an overview') are provided.

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