DPRF Nada consta: Multas Pagas

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

Beyond annotations (idempotent, non-read-only, non-destructive), the description explains session-specific vs permanent login, that calling with no args returns a link, and that using a token creates a session. This adds meaningful behavioral context about state and token handling that isn't in 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?

Two sentences deliver all key information without fluff. Details are front-loaded ('log in in the browser, copy the access token'), and the prose is efficient despite the parenthetical audience note. Every clause contributes actionable 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?

For a single-parameter optional-auth tool with no output schema, the description covers user actions, token handling, session behavior, and configuration steps. It leaves no ambiguity about how an agent should invoke it, making it complete for its complexity.

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 0% description coverage for its sole optional 'token' parameter. The description fully compensates by explaining that the token is a JWT pasted by the user, how it's used in the call, and what happens if omitted. This adds essential meaning beyond the raw schema.

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 specific verbs and resources: 'log in in the browser, copy the access token' and clearly distinguishes this as the authentication tool for MCP.AI IDE agents. It clearly differentiates from siblings by focusing on token-based login and linking, setting it apart from generic 'connect' or 'marketplace' 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 explicit usage scenarios: 'Best: add it to this server's config... Or paste it here for a session-only login' and details exactly when to call with or without arguments. It covers the primary use cases and even gives a recommended approach, though it doesn't mention alternatives from sibling tools, that's not needed here as it's an authentication flow with distinct methods.

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 behavioral nuance about response format (authenticated:true, pending[], connect_url), but doesn't disclose additional traits like rate limits or permission requirements. It doesn't contradict 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?

Two concise sentences, front-loaded with the purpose and clear conditions. 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?

The tool has no output schema, but the description explains what the response contains (authenticated:true, pending[], connect_url). It doesn't explain how to interpret partial connectivity or error scenarios, but given the simplicity and zero params, it's sufficiently complete.

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 parameters. The baseline of 4 is appropriate as the description adds no parameter info but that's fine given no params exist.

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's function: checking connection status and providing URLs. It distinguishes itself from siblings like authenticate and toolkit_info by focusing on connection status rather than initiating auth or general toolkit info.

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 checking connection status, but does not explicitly state when not to use it or contrast with alternatives like 'authenticate' for initiating connections. There is enough context to understand when to call, but no 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 reveals that the tool requires prepaid credit and does not need platform credentials, which are important behavioral traits not covered by annotations. It also states that the data is not confidential and the client is responsible for LGPD compliance, adding some transparency. However, it does not explicitly mention that it is read-only (though annotations already indicate that) or any 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 repetitive ('consulta em fonte oficial' and later 'consulta informação de fontes e órgãos oficiais') and includes legal disclaimers that are not directly relevant to the tool's function. It could be more concise and structured, focusing on what the tool does and its key operational 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?

There is no output schema, so the description should indicate what the tool returns (e.g., a certificate, a status, an error). It also does not mention any edge cases, error handling, or the format of results. The payment mechanism is mentioned but not detailed. Overall, the description lacks essential context for a user to fully understand the tool's behavior.

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 includes parameters 'placa', 'renavam', 'pagina', and 'estrangeiro' but the description does not explain any of them. There is no description for what each parameter means or its expected format, leaving the user to guess (e.g., pagination, foreign vehicle flag). 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 it is a query tool for checking 'nada consta' (no outstanding issues) regarding paid fines from official Brazilian sources. The tool name and parameters (placa, renavam) reinforce this. However, it could be more explicit about the exact purpose (e.g., 'checks if a vehicle has no pending fines') without the legal disclaimers.

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 guidance on when to use this tool versus alternative tools. It only describes what the tool does, not the appropriate context or scenarios. No mention of prerequisites like prepaid credit or when a user would prefer this over another 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?

Even with annotations present, the description adds substantial non-obvious behavior: invoke runs uninstalled MCPs one-off, credential needs return a connect link, empty wallet returns a checkout/top-up link followed by retry, and install has a hidden 'one-off install behind invoke' effect. Nothing contradicts 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 long but well structured, moving from purpose to core flow, then key invoke behavior, install-vs-invoke guidance, permissions, and the prompt library. Each section earns its place for a multi-action tool, though some wording is redundant and the sentence about capability-request examples could be trimmed.

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 highly complex 23-parameter dispatch tool with no output schema, the description covers the major contextual gaps: discovery flow, per-tool profile contents, one-off execution, auth and payment outcomes, permission requirements, billing action semantics, and the prompt library. It is genuinely complete for agent decision-making.

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 and 23 parameters, the description adds real meaning to the core action enum (search, describe, invoke, install, list_tools, etc.), tool_id, mcp_id, arguments, and prompt-related parameters. However, several parameters like limit, immediate, cancel_reason, and prompt_vars are not explicitly explained, so it does not fully compensate for the schema 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 identifies the tool as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' which is a specific verb+resource statement. It also lays out the core search→describe→invoke flow, distinguishing it from sibling tools 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' versus 'Use install only to make an MCP PERMANENT in the active toolkit,' and clarifies that 'list_tools lists what is callable right now.' It also states that writes require workspace owner/admin, which is critical selection context.

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

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

Annotations already indicate the tool is not read-only, not destructive, and idempotent, so the description doesn't need to restate those. However, it adds minimal behavioral context beyond the parameter instruction; it doesn't disclose what happens after a report is submitted, such as ticket creation or data 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?

The description is two sentences long, front-loaded with the core purpose, and contains no filler or redundant restatements of the tool name. 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?

For a simple tool with three parameters and no output schema, the description is mostly complete: it states the purpose and provides the key usage hint about the conversation array. The unexplored 'context' parameter and lack of any post-submission behavior note keep it from being fully complete.

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 meaningfully clarifies the 'conversation' parameter ('recent messages for reproduction') and implies 'message' is the bug/feedback text, but it does not explain the 'context' parameter at all, leaving a 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 uses a specific verb ('Report') with clear objects ('a bug, missing feature, or send feedback'), making the tool's purpose immediately recognizable. It also distinguishes this tool from siblings like authenticate, marketplace, and show_version, 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 provides clear context: use this tool to report bugs, missing features, or feedback. It also gives explicit guidance to include the conversation array for reproduction, but does not mention when not to use it or name alternative tools for related tasks.

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 read-only nature is covered. The description adds no additional behavioral context like data sources or side effects, but for a simple version lookup this is acceptable.

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?

One sentence, front-loaded with the verb and resource. Every word is meaningful and there is no redundant 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 the trivial complexity, empty schema, and strong annotations, the description fully covers what the tool does and what the agent should expect. An output schema is not needed for a simple version response.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and the schema is empty, so the description is not required to elaborate on parameter details. Baseline 4 applies since there are no parameters to document.

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 'Show' with a clear resource: 'current MCP platform and adapter versions.' This precisely distinguishes the tool from siblings like report_bug or marketplace, 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 gives no guidance on when to use this tool versus alternatives such as toolkit_info. There is no mention of troubleshooting or version-checking contexts, nor any exclusions, so the agent must infer usage from the name alone.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering safety. The description adds valuable context about what data is returned (installed MCPs, connection status, accounts, count of catalog tools), which goes beyond the annotations. No contradictions exist.

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 effectively encapsulates the tool's functionality without any redundant words. It is front-loaded with the action and result, and every word 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?

The description covers the key aspects of the tool's output (installed MCPs, connection status, accounts, catalog tool count), which is sufficient for a simple read-only status tool. It does not describe the response format or structure, but that is not strictly required given the straightforward nature of the tool and the absence of an output schema. A slightly higher score might be warranted, but the lack of format details prevents 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 tool has zero parameters, so the baseline is 4 per the rubric. The description does not need to explain parameters, and the input schema is empty. The description sufficiently explains what the tool returns, which is the primary semantic content.

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: returning the current toolkit state with specific details (installed MCPs, connection status, accounts, catalog tool counts). The verb 'returns' is specific, and the resource is well-defined. It distinguishes itself from sibling tools like connect and authenticate, which are action-oriented.

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 checking status but does not explicitly state when to use it versus alternatives. It does not mention exclusions or scenarios where another tool would be more appropriate. Given the sibling names, it's clear this is informational, but the lack of explicit guidance prevents a higher score.

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