DETRAN GO: Veículo

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

Beyond the annotations, the description discloses meaningful behavior: token persistence semantics ('permanent, non-expiring' vs 'session-only') and no-arg behavior (return the login link). This adds useful context 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 front-loaded with the purpose and delivers actionable instructions in three compact sentences. The 'Best:'/'Or' structure makes the options scannable with 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?

For a simple tool with one optional parameter and no output schema, the description covers the full workflow: browser login, token retrieval, permanent vs session configuration, and no-arg behavior. The invocation semantics are complete and usable.

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 provides a bare optional string token with 0% description coverage, but the description compensates fully: it explains that token is a JWT for session-only login, and that omitting the token triggers the login-link flow. This is more than enough for correct invocation.

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 (authenticate) and resource (MCP.AI), and explains the login/token workflow. It is specific enough to distinguish this from sibling tools like connect or marketplace because it focuses entirely on access-token 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 options: permanent config header vs session-only token, and calling with no args to get the link. It does not explicitly mention when not to use this tool versus sibling tools, but the two modes are clearly differentiated.

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 the tool as read-only and idempotent, so the description's 'returns status' aligns. It adds value by explaining the output variations: it returns authenticated:true and empty pending[] when all providers are connected, and connect URLs otherwise. This clarifies behavioral outcomes beyond the annotations, though it doesn't mention side effects (none expected given read-only).

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 with the core purpose ('Returns connection status and URLs') followed by specific outcome details. It uses only two sentences, with no wasted words, and clearly communicates the dual outcomes.

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 is complete enough. It explains the response semantics sufficiently for an agent to know what to expect. However, it doesn't explicitly mention the read-only nature, but that's covered by annotations, so the description doesn't need to repeat it.

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 0 parameters, and the schema has 100% coverage (vacuously). The description provides no parameter info because none exist, so it correctly focuses on the output semantics, which is more useful. Since there are no parameters, the description's job is to explain what the status means, which it does effectively.

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 reports connection status and URLs, and it distinguishes its behavior by describing the two possible outcomes (authenticated with empty pending, or missing credentials with connect URLs). While it doesn't explicitly differentiate from siblings, 'connect' logically pairs with 'authenticate' as a read-only status check, which is implied.

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 the tool is used to check connection status and get URLs when credentials are missing, but it doesn't give explicit when-to-use or when-not-to-use guidance. It does not mention alternatives like 'authenticate' for initiating connections or 'toolkit_info' for general info, so the guidance is inferred but not stated.

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 adds behavioral context beyond the annotations: it mentions payment model (prepaid credit), absence of platform credentials, and LGPD data-handling responsibility. Combined with readOnlyHint=true and idempotentHint=true, the agent understands this is a safe read operation. It doesn't describe the return format, but the annotations already cover safety, so the added context is valuable.

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, with the core purpose stated in the first sentence, followed by relevant operational notes. It is not overly verbose and is structured as a short paragraph, making it easy to scan. However, it could be improved by front-loading the parameter 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?

Given the tool's complexity (6 parameters, no output schema, no annotation details for inputs), the description is incomplete. It explains the data source and payment, but does not describe what the tool returns, which parameters are needed, or any prerequisites (e.g., having credits). An agent would struggle to invoke this tool correctly without additional information.

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 6 parameters, 2 required, and 0% description coverage. The tool description does not mention any parameter names, types, or purposes. It fails to compensate for the lack of schema documentation, leaving the agent to guess what 'placa' and 'renavam' mean. This is a critical gap.

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: 'DETRAN GO: Veículo, consulta em fonte oficial' (vehicle consultation from official source). It identifies the specific resource (vehicle info from DETRAN GO) and the action (consulta), distinguishing 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 provides context on when to use the tool: it's hosted by the platform, requires no platform credentials, and is paid per query. While it doesn't explicitly exclude alternatives, the context is clear enough for an agent to understand this is the designated vehicle-query tool, and there are no contradictory usage hints.

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 adds substantial behavior beyond annotations. It discloses the key surprise: 'invoke works even when the MCP is NOT installed — it runs the tool pontualmente (one-off), without adding the MCP to the toolkit and without bloating the tool list'. It explains connect links for credentials, checkout/top-up links for empty wallets, and the permission requirement: 'Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin'. No contradiction with annotations (readOnlyHint=false, openWorldHint=true is consistent with the described 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?

For a tool with 14 actions and 23 params, the length is justified — every clause carries information. However, it's a single dense wall of text with en-dash run-ons and no paragraph breaks or bullets, which hurts scannability for an agent parsing quickly. The most important info is front-loaded (marketplace, core flow), but structure could be dramatically improved with sectioning per action group.

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 extreme complexity (14 actions, 23 params, no output schema), the description is remarkably complete: it covers the full discovery→invoke flow, the not-installed invoke behavior, connect/checkout redirects, permission requirements, and the entire prompt-library subdomain. The main gap: no description of return/response shape at all — with no output schema present, an agent cannot anticipate what the tool returns for any of the 14 actions. Minor params (immediate, conversation) also go unexplained.

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 bears full burden. It compensates strongly for the most important params: the entire action enum (all 14 values explained), mcp_id, tool_id, arguments, query intent, and all prompt params (prompt_slug, prompt_vars, prompt_body, prompt_title, prompt_targets, prompt_description). However, several params remain undefined: immediate, conversation, cancel_comment, report_context, request_name, request_details, and limit get no semantic explanation despite 0% schema coverage.

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?

Exceptionally clear purpose: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It explains the core flow (search → describe → invoke), enumerates the capability requests it handles ('find an MCP that does X', 'consulta um CPF'), and contrasts with siblings (marketplace catalog vs. direct tools). The breadth is appropriate because the tool itself is a 14-action dispatcher, and the description maps every intent to its 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?

Explicit when-to-use guidance throughout: 'prefer invoke for a single/occasional use' vs. 'Use install only to make an MCP PERMANENT in the active toolkit'; 'request_mcp asks us to build a NEW MCP when nothing fits'; 'list_tools lists what is callable right now'; 'subscribe/cancel handle per-MCP billing'. Also names the prompt-library sub-actions (search_prompts, get_prompt, publish_prompt) with distinct purposes.

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 indicate readOnlyHint=false (write operation), idempotentHint=true (repeatable), and destructiveHint=false (non-destructive). The description adds useful behavioral context by specifying that the conversation array is needed for reproduction, which goes beyond the annotations. No contradictions are present.

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 short sentences, front-loading the purpose and then providing a key usage tip. Every word is necessary, and it is efficiently structured without redundancy.

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 has three parameters with no schema descriptions and no output schema. The description only covers the conversation parameter, leaving the required message and optional context unexplained. It also does not specify what happens after reporting (e.g., acknowledgment, response). Given the low schema coverage, this is insufficient for correct 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?

Schema description coverage is 0%, so the description must compensate for all parameters. It only explains the purpose of 'conversation' (for reproduction). It does not explain the required 'message' parameter or the optional 'context' parameter, leaving the agent without guidance on what to fill in those fields. This is a significant gap.

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: 'Report a bug, missing feature, or send feedback.' It uses a specific verb ('report') with a clear resource (bug/feature/feedback), and the second sentence explains how to include reproduction context. This distinguishes it from sibling tools like authenticate, connect, or show_version, which serve 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 when to use the tool by its phrasing ('Report a bug...'), and it offers a concrete usage hint: 'Include the conversation array with recent messages for reproduction.' It does not explicitly name alternatives or exclusions, but given the sibling tools are unrelated, the context is clear enough.

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 'current' aspect, implying it returns live data, but does not disclose additional behavioral nuances (e.g., output format). With annotations handling safety, this is adequate but not exceptional.

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, succinct sentence that immediately states the action and subject. Every word earns its place, and there is no fluff or unnecessary detail. It is optimally front-loaded and compact.

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 annotations fully cover its safety profile, the description is complete enough. It explains what it does (show versions) and no further context is required. There is nothing missing that would hinder an agent from using 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 the schema is fully covered. Per the rubric, a baseline of 4 is appropriate for 0 parameters. The description adds no parameter-specific information because none is needed, making this a perfect score for the dimension.

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: showing current MCP platform and adapter versions. It specifies the exact resource (versions) and is distinct from sibling tools like authenticate or connect, leaving no ambiguity about its function.

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?

While there is no explicit statement of when to use it, the tool's name and description make it obvious for checking version information. There are no exclusions or alternatives, so the context is clear enough. A slightly higher score is justified because the purpose is so self-evident that explicit guidance is unnecessary.

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 the read-only, idempotent, non-destructive nature of the tool. The description adds meaningful context by specifying what data is returned (connections, accounts, catalog tool counts), going beyond the annotations. It does not cover edge cases like empty states or authentication dependencies, but the additional detail is valuable.

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, well-structured sentence leads with the action and then lists the specific data returned, making it immediately scannable. There is no redundant information or filler, so 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 low-complexity, zero-parameter read-only tool, the description adequately captures the primary return elements. It could improve by addressing potential empty results or the meaning of connection statuses, but these are minor gaps given the tool's simplicity and good annotation support.

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 input schema is trivially complete and there is no parameter documentation burden. The description correctly implies the tool acts on the entire toolkit without needing inputs, matching the baseline 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 uses the specific verb 'Returns' and clearly identifies the resource as 'current toolkit state,' then enumerates the exact components returned: installed MCPs, connection status, connected accounts, and catalog tool counts. This makes it easily distinguishable 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 the tool is used to obtain a high-level status overview of the toolkit, and the sibling context confirms its unique role. However, it does not explicitly state when to use this tool vs alternatives or mention any exclusions, leaving room for more explicit guidance.

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