DER SP: Indicação do Condutor Infrator

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

The description discloses the key behavioral aspects: it initiates a browser login, returns a link when called with no arguments, and supports persistent vs. session auth. Annotations indicate idempotent=true and non-read-only, which aligns with the described token-setting side effects. It does not contradict annotations, and adds useful context about token handling.

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?

Three sentences cover purpose, two authentication flows, and invocation syntax. While slightly dense with inline code, every clause provides value and the information is front-loaded. Could be slightly trimmed, but remains easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers both login modes and the no-arg behavior, which is sufficient for a simple auth tool. It omits error cases, token expiry, and response details, but given the simplicity and lack of output schema, this is acceptable. A short note on what happens after successful auth would push it to a 5.

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 contains only an optional 'token' field with no description, so the description carries the full burden. It clearly explains that 'token' is a JWT pasted by the user after browser login, and that calling with no arguments returns the login link. This fully compensates for the 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?

Clear and specific: the description identifies the tool as authenticating MCP.AI for IDE agents, and explains the login flow (browser, token copy, config header vs. session-only). This distinguishes it from siblings like 'connect' and leaves 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?

The description clearly explains when to use the tool (for authentication) and provides two usage paths: permanent via config header and session-based via token paste. It also mentions the no-args option. However, it does not explicitly contrast with the sibling 'connect' tool, though it is unambiguous enough for most agents.

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

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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds useful context about what happens in different states: authenticated:true with empty pending[] when connected, and connect_url plus per-install URLs when credentials are missing. This goes beyond the annotation 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 two sentences, front-loaded with the main purpose, and every clause contributes meaningful information about the tool's outputs. No wasted words or repetition of schema fields.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple, has no parameters or output schema, and the description covers the main behavior and conditional outputs. It is complete enough for an agent to know what to expect, though it could clarify the exact shape when only some credentials are missing.

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 zero parameters, so the baseline is 4 per the rubric. The description does not need to explain any parameter semantics and correctly focuses on what the tool returns.

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, which is specific and distinguishes it from sibling tools like authenticate and toolkit_info. It also describes the two distinct output states based on whether all providers are connected.

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 indicates when the tool is useful—for checking connection status and retrieving URLs—but it does not explicitly say when not to use it or name alternative tools. The behavioral states imply usage, but no direct comparison or exclusion is given.

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 context about pay-per-query, no credentials, and LGPD responsibilities, but these are more operational than behavioral. It does not describe what happens on success or failure, or any side effects, but since read-only, that's fine. The description aligns with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph, relatively concise, and front-loads the purpose. It includes extra context about payment and LGPD, but that is necessary for an agent to understand usage constraints. Could be structured with bullet points, but it's acceptable.

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?

With 5 required parameters and no output schema, the description should explain what inputs are needed and what the response contains. It only mentions the purpose and legal aspects, but gives no guidance on required fields like placa, ait, cpf, cnh, or cnh_validade, nor what the result looks like. This is insufficient for an agent to 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?

Schema has 5 required parameters (ait, cnh, cpf, placa, cnh_validade) and one optional (file_pdf), but description provides no explanation for any parameter. With 0% schema coverage, the description fails to clarify what these fields mean or their format. 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 performs a query ('consulta') for 'Indicação do Condutor Infrator' from DER SP, an official source. It specifies the resource and differentiates from general-purpose sibling tools like authenticate and 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?

It explains the context of use: hosted platform, no credentials needed, pay-per-query with prepaid credits, and that it queries official Brazilian sources. However, it doesn't explicitly contrast with alternatives or state when not to use it, though siblings are unrelated general tools.

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?

Exceptional disclosure beyond the sparse annotations: explains that invoke runs one-off without installing or bloating the toolkit, that missing credentials return a connect link while empty wallets return a checkout link with 'then you retry', that writes require workspace owner/admin, and that search/describe flag installed_in_toolkit vs installed_in_workspace states. No contradictions with readOnlyHint=false or openWorldHint=true — the description actually enriches the open-world semantics by detailing auth, payment, and permission behaviors.

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 ~350-word undifferentiated wall of text with semicolon-separated ideas and parenthetical asides. The content is genuinely information-dense with every sentence earning its place, and the core flow is front-loaded, but the lack of sections, bullets, or action breakdowns makes an agent scan laboriously across run-on sentences. For a 14-action mega-tool this structural density actively harms usability despite strong raw content.

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 enormous complexity (14 actions, 23 params, no output schema, minimal annotations), the description is remarkably complete for the core MCP discovery/execution flow, including auth link behavior, payment retry flow, permission requirements, and the separately-scoped prompt library domain. Gaps remain: resume is in the enum but never explained, the immediate and conversation parameters are silently omitted, and return shapes for search/describe are only implied rather than stated. Still well above average for a tool of this scale.

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 across 23 parameters, the description carries the full burden but only partially compensates. It thoroughly explains the action enum values (search/describe/invoke/install/subscribe/cancel/report_bug/request_mcp/prompt actions) and touches tool_id/arguments/prompt_vars/prompt_slug, yet leaves several parameters (arguments format, immediate, conversation, prompt_targets, prompt_category, request_details, report_context, cancel_comment) entirely unaddressed. The action enumeration does heavy lifting, but a 23-parameter dispatcher needs systematic param mapping to score higher.

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 defines the tool as the official mcp.ai marketplace catalog and execution platform, explicitly stating the core flow (search → describe → invoke) and distinguishing it from siblings like authenticate/connect and the standalone report_bug tool. While the purpose is clear and specific, the tool doubles as a prompt-library handler and a 14-action dispatcher, which inherently spreads the purpose across multiple domains.

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?

Strong when-to-use guidance embedded throughout: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT', plus explicit clarification that list_tools lists what's callable now and that report_bug/request_mcp serve different intents. It names alternatives and gives the preferred path, but doesn't explicitly address when NOT to use marketplace in favor of a sibling tool beyond the implicit action-level distinctions.

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 state readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description adds context that the conversation array is for reproduction, which is helpful. It does not disclose any additional behavioral details (e.g., whether a report is persisted or confirmation is returned). 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, front-loaded sentence that states the purpose and provides essential usage guidance. Every word earns its place; there is 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 simple (3 parameters, no output schema), and the description covers its main purpose and the conversation parameter. However, it omits any mention of the 'context' parameter and does not describe what happens after reporting (e.g., acknowledgment or return value), which would be useful given the lack of an output schema.

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 explains the 'conversation' parameter ('Include the conversation array with recent messages for reproduction') and implicitly ties 'message' to the bug report content. However, the 'context' parameter is left unexplained, leaving a gap in parameter understanding.

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 'Report' and clearly states the resource: 'a bug, missing feature, or send feedback.' It also explains the need for the conversation array, distinguishing this tool from all sibling tools, which none are related to bug reporting.

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 context on when to use the tool ('Report a bug, missing feature, or send feedback') and gives usage guidance on including the conversation array. It does not explicitly mention alternative tools, but given the sibling list, this tool is clearly the only one for reporting issues, so no exclusions are necessary.

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

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is well established. The description adds the specific detail that both platform and adapter versions are shown, which is useful context beyond 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 a single, concise sentence that leads with the verb and directly states the resource. Every word earns its place, with no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, read-only, idempotent tool, the description is complete. It clearly states what the tool does, and with no output schema, the description adequately conveys the expected result: version 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?

There are zero parameters, so the baseline is 4. The description does not need to explain any parameters, and the empty schema is fully consistent with the description's claim of simply showing versions.

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' with a clear resource 'current MCP platform and adapter versions'. It is instantly clear what the tool does and distinguishes it from sibling tools (none of which relate to version information).

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 implicitly conveys when to use this tool: whenever one needs to know the platform or adapter versions. No exclusions are necessary because it is a simple informational tool and no siblings serve a similar purpose.

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 read-only, idempotent, and non-destructive behavior. The description adds no further behavioral details (e.g., auth requirements, rate limits, or side effects). Given the existing annotations, the description is adequate but does not go 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, concise sentence that efficiently lists the returned information. It is well-structured and to the point, with no redundant wording or unnecessary details.

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 lack of parameters and output schema, the description adequately explains what the tool returns. It enumerates the key components of the toolkit state, which is sufficient for users to understand the tool's output and usage context. No critical information is missing.

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 takes no parameters, so the input schema is inherently 100% covered. The description does not need to explain any parameters, and it correctly omits any mention of them. This is a perfect score for parameter semantics.

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: returning the current toolkit state. It specifies the exact information provided (installed MCPs, connection status, connected accounts, and catalog counts), making the purpose unambiguous and distinct from potential sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide any guidance on when to use this tool versus alternatives. It merely describes what it does, without contextual cues or comparison to sibling tools. Users are left to infer usage scenarios from the description alone.

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