DETRAN PR: Licenciamento

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

Annotations already indicate this is not read-only, is idempotent, and not destructive. The description adds valuable behavioral context: it explains the login workflow, the option for permanent vs. session setup, and that calling with no args returns a link. It does not contradict any annotations, and the extra detail about the auth header and token usage enhances transparency beyond the baseline.

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 yet information-dense, with no fluff. It front-loads the purpose and then provides structured usage options (config vs. session, with/without token). Every sentence adds value, and the formatting (using code inline for variables) improves readability.

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 (one optional parameter, no output schema), the description covers all necessary context: the authentication flow, how to obtain and use a token, the difference between permanent and session logins, and the behavior when no arguments are given. It is complete for an agent to correctly invoke this 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 provides no description for the 'token' parameter (0% coverage), so the description must carry the full burden. It does so effectively: it explains that 'token' is a JWT obtained from the browser, when to pass it (after the user pastes), and that omitting it returns a login link. This entirely compensates for the schema gap and gives the parameter clear 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 clearly states the tool's purpose: authenticating an IDE agent (like Cursor) by logging in and obtaining an access token. It specifies the verb 'log in' and resource 'access token', and provides usage context. However, it does not explicitly distinguish itself from the sibling tool 'connect', leaving some ambiguity about when to use this vs. the alternative, which prevents a perfect score.

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 guidance on when to use different invocation modes: provide a token for session-only login, or no args to get a login link, and recommends putting the token in server config for a permanent connection. It does not compare itself to alternative tools like 'connect', but the usage scenarios for this tool are well articulated, so it earns a strong 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 indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description's job is lighter. The description adds useful context about what the response contains in different states, but it does not disclose any side effects or limitations beyond that. This adds some value, but not a rich behavioral context, so a 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 long, contains no filler, and front-loads the core purpose ('Returns connection status and URLs.') before diving into state-specific details. Every sentence carries meaningful information, making it highly 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?

Given that the tool has no parameters, no output schema, and the annotations already signal a safe read-only operation, the description provides sufficient information for an agent to understand when to call it and what to expect in the response. It covers both main states (connected and missing credentials), which is complete enough for this simple 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 doesn't need to explain parameter semantics. The schema coverage is 100% (there are no properties). The description correctly focuses on what the tool returns, which is the most important semantic information. A baseline 4 is appropriate for zero-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 clearly states the tool returns connection status and URLs, and explains the two possible states (all providers connected vs. missing credentials). This is a specific verb ('returns') with a clear resource, and it distinguishes itself from siblings like 'authenticate' by focusing on status rather than initiating 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 implies when to use it (to check connection status and get URLs when credentials are missing), but it does not explicitly state when not to use it or mention alternatives. It would be clearer if it noted that 'authenticate' is for initiating the connection process, while this tool is for checking status.

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, idempotentHint, and non-destructiveHint, and the description does not contradict those. It then adds real behavioral context: it is a paid query using prepaid credits, it requires no platform credentials, it returns non-confidential official data, and it places LGPD responsibilities on the customer. This exceeds what the annotations alone communicate.

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 four relatively short, front-loaded sentences. The first sentence quickly states the purpose, and the remaining sentences add operational/pricing/LGPD context without extraneous fluff. It is slightly fuller than minimum necessary but still 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?

There is no output schema, and the description does not disclose what the tool returns or how failures are presented, such as whether it returns a licensing status object, a deadline, or an error message. It also leaves the relationship between the required certificate and the actual query flow implicit. The description establishes the legal/billing context but does not show enough operational detail for a confident invocation.

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 0% description coverage, and the description never mentions renavam, pkcs12_cert, or pkcs12_pass. The phrase 'sem credenciais da plataforma' hints that the PKCS12 values are external credentials, but that is indirect. The description fails to explain the meaning or required format of the parameters, and there's no compensation 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 identifies the action and resource: 'DETRAN PR: Licenciamento, consulta em fonte oficial de Consulta informação de fontes e órgãos oficiais brasileiros'. It uses a specific, verb-like noun combination that distinguishes it from the sibling tools, which are platform utilities such as 'authenticate', 'connect', or 'marketplace'. This is a specific consulting operation for licensing data from the official DETRAN PR source.

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?

There is no explicit statement about when to use this tool versus alternatives, nor does it name alternative tools for the same task. It does imply usage by describing the operational context: the consultation is hosted by the platform, uses prepaid credits instead of platform credentials, and is the "same as made available to the citizen." This is usable but does not provide explicit when-to-use/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?

The description discloses many behavioral traits beyond the annotations: invoke works without installing the MCP, returns a connect link when credentials are needed, returns a checkout/top-up link for empty wallet, and requires retry after user actions. It also mentions install behind invoke requires permissions, and that search/describe flag installation status. This gives the agent a clear model of side effects and fallback 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 dense paragraph with no bullets or sections, but it front-loads the core purpose ('official mcp.ai marketplace') and then covers the full flow. Every sentence adds value, though the volume of information is high and could benefit from structure. The length is justified by the tool's 14 actions and prompt library, but it is not optimally scannable.

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 (23 parameters, 14 actions, no output schema), the description is remarkably complete: it explains the discovery-to-invoke flow, permission requirements, credential/payment handling, list_tools, billing, bug reporting, request_mcp, and the separate prompt library with search/get/publish. It covers operational caveats (retry after connect/checkout) and differentiates between installed vs. one-off usage. This is comprehensive for an agent to use 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?

With 0% schema description coverage, the explanation compensates strongly by patiently describing the meaning of the main 'action' parameter values (search, describe, invoke, install, etc.), the purpose of 'tool_id' and 'mcp_id', and the prompt library parameters. However, it does not explain several parameters like 'limit', 'immediate', 'tier_slug', 'arguments' format, or 'cancel_reason' enums, leaving gaps for the agent to infer.

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 is 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It enumerates specific actions (search, describe, invoke, install, etc.), establishes a core flow, and distinguishes its role as both catalog and execution platform. This is a specific verb+resource definition that sets it apart from siblings like authenticate or show_version.

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 when-to-use guidance: 'prefer invoke for a single/occasional use' vs. 'use install only to make an MCP PERMANENT.' It outlines the core flow (search → describe → invoke) and explains when to use each action, including alternatives: 'request_mcp asks us to build a NEW MCP when nothing fits.' It also clarifies prerequisites for writes (workspace owner/admin). No exclusions needed since siblings are unrelated.

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 are provided: readOnlyHint=false, idempotentHint=true, destructiveHint=false. The description adds that it sends a report and asks for reproduction context, which is additional behavioral context. However, it doesn't detail what happens after reporting (e.g., confirmation, response times), and it doesn't contradict annotations. The idempotentHint is consistent with a report operation, but the description does not elaborate on side effects.

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 and front-loaded with the primary purpose. It is concise and includes actionable guidance about the conversation array. Every sentence adds value, though it could be slightly more detailed within the same length.

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 is low (3 parameters, no output schema), the description covers the main intent and one parameter, but misses the 'context' parameter and potential use cases. The annotations cover safety aspects. The description is adequate but not complete for all parameter semantics.

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. The description mentions 'conversation array' which maps to the 'conversation' parameter, and it implies 'message' is the main text. However, it does not explain the 'context' parameter at all. With three parameters and only partial explanation, the description adds some meaning but leaves gaps for 'context'.

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: report a bug, missing feature, or send feedback, and specifies that the conversation array should be included for reproduction. It distinguishes itself from sibling tools, though it doesn't explicitly compare to them, 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?

The description implies when to use it (when there is a bug, missing feature, or feedback) and it mentions including the conversation array, but it does not provide explicit guidance on when not to use it or alternatives. Given siblings like 'marketplace' or 'toolkit_info', this tool is clearly for reporting issues, but no exclusions are mentioned.

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 tool's safety profile. The description adds minimal context beyond that (e.g., 'current' versions), but does not introduce contradictions. With annotations covering the core behavioral traits, the description doesn't need to elaborate further, so a 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 sentence with no filler. It is front-loaded with the purpose and contains only necessary information, achieving maximum 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?

Given the tool's simplicity—no parameters, no output schema, and annotations already present—the description is entirely sufficient for an agent to understand its function and decide when to invoke it. There are no missing pieces that would leave the agent confused.

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 empty. Per the rubric, the baseline for 0 params is 4. The description doesn't need to add parameter semantics since there are none, and it does not attempt to explain any, so the baseline is justified.

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 function: '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 toolkit_info or marketplace, which likely have 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?

The description implies usage (e.g., when you need version info) but does not explicitly state when to use it vs. alternatives. Since it's a self-explanatory informational tool, the guidance is implied rather than explicit, which corresponds to a mid-range 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=true and idempotentHint=true, and the description adds behavioral specifics: it reports the list of installed MCPs, their connection status, connected accounts, and catalog tool counts. This goes beyond the empty schema and gives a clear picture of the return payload.

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 entire description is a single, front-loaded sentence that leads with the action and then enumerates the exact data returned. Every word adds value—no filler.

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 zero parameters and no output schema, the description is the sole source of return-value documentation. It lists four specific components of the state object, which is sufficient for an agent to understand the output. However, it doesn't mention possible empty states or error conditions, which would be edge-case expectations.

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 accepts no parameters and the schema description coverage is 100% ('properties': {}). The description adds no parameter-specific semantics because none exist; the baseline of 4 for parameterless tools is appropriate.

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 the specific verb 'Returns' and clearly scopes the resource to 'current toolkit state', listing specific data points (installed MCPs, connection status, accounts, catalog tool counts). This clearly differentiates it from siblings like 'show_version' (version info) and 'connect' (an action).

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 for inspecting toolkit state but does not explicitly state when to choose it over 'show_version' or when not to use it. No alternatives or exclusions are mentioned, so guidance is only implied.

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