DETRAN MS: Veículo

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

Annotations indicate idempotentHint=true and destructiveHint=false, which the description aligns with (no contradiction). The description adds context about the browser login flow and token handling, but doesn't disclose details like whether the token is stored, expiration, or side effects beyond the session. With annotations covering safety, this is adequate but not rich.

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 front-loads the purpose and then explains the two usage modes. It's efficient, though slightly run-on; every sentence 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's simplicity (1 optional param, no output schema), the description covers the essential flow: browser login, token acquisition, and both permanent and session-based usage. It's complete enough for an agent to invoke correctly, though it could mention what the response contains (e.g., success message or link).

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 'token' parameter as a JWT to paste for session-only login, and clarifies that calling with no args returns the login link. This adds meaning beyond the bare schema, but it doesn't specify token format validation or error handling.

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: to authenticate an IDE agent with MCP.AI by logging in via browser and obtaining an access token. It distinguishes itself from siblings by being the authentication entry point, though it doesn't explicitly name alternatives.

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: it explains the two modes (permanent via config header, session-only via token argument) and when to call with or without arguments. It doesn't explicitly state when not to use it, but the guidance is sufficient for an agent to decide.

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 readOnly, idempotent, non-destructive. Description adds the two distinct response scenarios (authenticated:true vs connect_url), which is useful beyond the annotations. 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?

Two sentences, front-loaded with the main purpose, then conditional details. No fluff.

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 no parameters and a simple output, the description covers the two plausible states (all connected vs missing credentials). It doesn't mention partial connection states, but for a connection status tool this is likely sufficient. The annotations cover safety traits, and the description adds the output structure, so completeness is adequate.

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?

No parameters exist, so baseline 4. Description explains the output in two states, effectively conveying what the tool returns without needing parameter 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?

Description clearly states it returns connection status and URLs, with specific details about authenticated state and pending array. This distinguishes it from sibling 'authenticate' and 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?

Provides behavioral context (when all connected vs missing credentials) but does not explicitly state when to use vs alternatives like 'authenticate' or other toolkit tools. It implies a status-checker role but doesn't give exclusion 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 declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavior context: payment is required per query, data comes from official public sources (not confidential), and the client is responsible for LGPD compliance. This goes beyond the annotations. It does not mention return format or rate limits, but that is not critical given the read-only nature.

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 paragraph of four sentences covering the tool's purpose, source, payment, and legal aspects. It contains no fluff and front-loads the core function. It could be more structured (e.g., separated into bullet points), but it remains 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?

The description explains the data source, payment model, and legal obligations, but it omits critical invocation details: parameter meanings, expected output, and how to handle optional credentials. With no output schema and 0% parameter coverage, the agent lacks sufficient information to confidently select and correctly invoke the 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 has 6 parameters with 0% description coverage, and the tool description does not explain any of them. While 'placa' and 'renavam' are somewhat self-explanatory, optional parameters like login_cpf, login_senha, pkcs12_cert, and pkcs12_pass are cryptic and unexplained. The description does not compensate for the lack of schema documentation.

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 'DETRAN MS: Veículo, consulta em fonte oficial' and 'Consulta informação de fontes e órgãos oficiais brasileiros', making it obvious this is a vehicle consultation tool for DETRAN MS. It is distinct from sibling tools like authenticate and marketplace, which serve generic platform functions.

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: hosted by the platform, requires prepaid credit ('pague por consulta com crédito pré-pago'), does not require platform credentials, and queries official Brazilian sources. It also mentions LGPD compliance, implying legitimate data use. However, it does not explicitly state when to use this tool over alternatives or mention exclusions.

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 the annotations by explaining critical behaviors: invoke runs tools even when not installed, returns connect/checkout links for auth/payment, and writes require workspace owner/admin. It also notes the distinction between installed_in_toolkit vs installed_in_workspace, adding valuable context that 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 dense and information-rich, but it is a single block of text that could be more scannable with bullet points or separation of the marketplace flow from the prompt library. Nevertheless, every sentence adds meaningful detail, and the length is justified by 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?

Given the tool's complexity (14 actions, 23 parameters, no output schema), the description is remarkably complete. It covers the core flow, auth requirements, error handling (connect/checkout links), installed status flags, and even introduces the prompt library. This provides enough context for an agent to correctly select and invoke the appropriate action in most scenarios.

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 description compensates for the 0% schema coverage by explaining the main action values and their purposes, which directly informs how to use related parameters. However, it does not address every parameter explicitly (e.g., immediate, tier_slug, cancel_reason, conversation), relying on self-explanatory names or inferred context. Given the large parameter count, more detail would be beneficial, but the action-based guidance is already strong.

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, serving both as a catalog of MCPs/tools and a way to run them. It provides a concrete action-oriented overview (search, describe, invoke) and distinguishes itself from sibling tools by describing its scope and core flow, making its purpose unmistakable.

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 invoke vs. install, stating 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT.' It also clarifies the roles of list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt library actions, giving clear context for choosing among alternatives within this tool.

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=false, destructiveHint=false, and idempotentHint=true. The description adds the useful context that the conversation array is used for reproduction, but it does not disclose what side effects occur after reporting (e.g., ticket creation or data transmission), so transparency beyond annotations is limited. No contradiction with annotations is 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 focused sentences: the first states the purpose, the second gives key operational guidance. Every sentence earns its place, with no filler or 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?

For a simple 3-parameter string-input tool without an output schema, the description covers the core intent and the reproduction instruction. However, the 'context' parameter is not explained, and nothing mentions what response or outcome to expect after the report is submitted. It is adequate but leaves clear 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?

Schema description coverage is 0%, so the description must compensate. It explicitly mentions only the 'conversation' parameter ('Include the conversation array with recent messages for reproduction'), and 'message' is implicitly clear from the tool's purpose. The 'context' parameter is left completely unexplained, and no format or semantics details are given beyond the schema itself.

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 'Report a bug, missing feature, or send feedback,' using a specific verb and clearly defining the resource/scope. None of the sibling tools (authenticate, connect, marketplace, etc.) overlap with this purpose, so no sibling differentiation is needed.

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?

It gives clear usage context: report bugs, missing features, or feedback, and instructs to include the conversation array for reproduction. It does not provide explicit exclusions or alternative tool mentions, but since no sibling performs a similar function, the lack of when-not-to-use guidance is not a material gap.

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 that it shows both platform and adapter versions, which is a small behavioral detail. It doesn't describe output format or any side effects, but with strong annotations, the bar is lower. 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 sentence, front-loaded with the verb and resource. Zero waste, perfectly concise for a simple tool.

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 params, no output schema, strong annotations), the description is complete enough. It tells the agent what it does. It could mention that it returns version strings, but that's not necessary given the tool's obvious purpose. A 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% (vacuously). The description doesn't need to explain parameters because there are none. Baseline for 0 params is 4, and the description is sufficient.

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: showing current MCP platform and adapter versions. It uses a specific verb ('Show') and resource ('MCP platform and adapter versions'), which is clear and distinguishes it from sibling tools like authenticate or connect. However, it doesn't explicitly differentiate from 'toolkit_info', which might also provide version info, so it's not a 5.

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: when you need to know the current versions. It doesn't explicitly state when not to use it or mention alternatives, but given the tool's simplicity and the sibling list, it's reasonably clear. No explicit exclusions or alternative recommendations, so it's adequate but not explicit.

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. The description adds useful detail about what the state includes (MCPs, statuses, accounts, catalog counts), which is extra context beyond the annotations and helps set expectations for the response content.

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 that front-loads the core purpose ('Returns the current toolkit state') and then lists what it includes. Every word contributes value with no redundancy or 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?

The tool is a simple no-parameter read operation with strong annotations. The description fully explains what the output contains, so the agent knows what information it will receive, and no other context is needed for correct use.

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 empty, so the baseline is 4. The description does not need to explain any parameters because there are none, and it correctly focuses on the output instead.

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?

Description states a specific verb+resource: 'Returns the current toolkit state' and enumerates exact contents (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from siblings like authenticate, connect, and report_bug, which serve different functions.

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 for inspecting toolkit state, with no mention of exclusions or alternatives. Given the sibling set, its purpose is unambiguous and users can infer when to call it, though explicit guidance like 'use this when you need to check connectivity' is missing.

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