DPRF Nada consta: Multas em Aberto

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

Beyond the annotations (idempotent, non-destructive), the description discloses important behaviors: calling with no args returns a login link, calling with a token performs session login, and config header creates a permanent connection. This adds useful workflow context.

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 dense sentences, front-loaded with purpose and audience. Each sentence contributes unique information, though the config-header detail adds some length. Overall efficient 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?

For a tool with one optional parameter and no output schema, the description covers the primary call modes and expected link response. It lacks explicit return/error semantics, but the low complexity keeps this gap minor.

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 lists a bare `token` string with no description. The description compensates well by explaining the token is a JWT pasted by the user, how to pass it, and the no-args case. This is meaningful guidance 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?

The description clearly states the tool authenticates MCP.AI for IDE agents, with explicit actions: getting a login link or using a token. It is specific about the resource (MCP.AI auth) but does not differentiate from sibling tools like 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 two distinct usage modes: permanent setup via config header and session-only login via token or no-args link. The intended users (IDE agents) are stated, but no alternative tools or exclusions are mentioned, so it stops short of full alternative 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 disclose readOnly, idempotent, and non-destructive behavior. The description adds valuable context by explaining the two distinct response scenarios (all providers connected vs. missing credentials) and the fields returned (authenticated, pending, connect_url), enhancing transparency 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 only two sentences, effectively front-loaded with the primary purpose. Every clause adds meaningful information 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?

For a simple status-checking tool with rich annotations and no output schema, the description fully explains the different return states. It is complete enough for an agent to understand what to expect without additional elaboration.

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 no parameters, so the baseline is 4. The description does not need to add parameter semantics, and the empty schema matches the tool's no-input design.

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 with a specific verb ('Returns') and resource ('connection status and URLs'). It also distinguishes from sibling tools like 'authenticate' by indicating this is a status check rather than an authentication 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 usage for checking connection status but does not explicitly mention when to use this tool versus alternatives like 'authenticate'. No exclusions or alternative recommendations are provided, leaving some ambiguity.

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?

Beyond the readOnlyHint annotation, the description discloses payment requirements, lack of platform credentials, and data controller responsibilities under LGPD. This adds meaningful transparency about operational and legal aspects, though it does not explain potential side effects (none expected given 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 moderately concise, with clear sentences covering purpose, payment, and data handling. It could be trimmed slightly, but it avoids unnecessary jargon and is well-structured for an API description.

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?

While the description explains the tool's purpose and some operational details, it omits any indication of return format or output structure, which is important since no output schema is provided. It also lacks parameter explanations, making the overall context incomplete for a user.

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 four parameters (placa, pagina, renavam, estrangeiro) but the description provides no explanation for any of them. Since schema coverage is 0%, the description fails to compensate, leaving parameter meanings unclear.

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: consultar multas em aberto (query open fines) from official Brazilian sources. It uses a specific verb (consultar) and identifies the resource (multas), distinguishing it from generic process tools and sibling tools like authenticate or marketplace.

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 some context (e.g., no platform credentials, paid per query) but does not indicate when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. It lacks explicit guidance on selection.

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 only say readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false; the description adds substantial behavioral context beyond those flags. It discloses that invoke can run an MCP even when not installed, that it performs a one-off install, that credential/payment gaps surface as connect/checkout links, and that writes require workspace owner/admin. It also explains that search/describe flag installation state. There is no contradiction with the annotations; the readOnlyHint=false is consistent with the documented write actions.

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 unusually dense; nearly every sentence introduces a distinct behavioral fact. It front-loads the core flow and then covers writes, prompt library, and auth. The main weakness is that it is one continuous block rather than scannable bullets, which increases cognitive load, but the content is not padded or redundant.

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 very high complexity (14 actions, 23 parameters, no output schema), this description is remarkably complete. It covers what actions exist, the canonical orchestration flow, installation semantics, auth requirements, payment/connect edge cases, tool-list awareness, and the separate prompt-library subdomain. It even describes return payloads for key actions ('returns a connect link', 'returns a shareable mcp.ai/p/<slug> link'). There are small gaps (e.g., `immediate`, `tier_slug`) but not enough to undermine the overall completeness for an agent.

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 23 parameters, no required params, and 0% schema description coverage, the description carries a heavy burden. It does add meaning for the central `action` enum by explaining each action's role in the core flow (search → describe → invoke) and for parameters like tool_id, prompt_vars, and prompt_slug. However, many parameters (limit, immediate, tier_slug, cancel_reason, conversation, report_context, etc.) receive no semantic guidance beyond their names or enums, leaving the agent to infer their purposes.

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 goes beyond a vague label by enumerating the core actions (search, describe, invoke, install) and explicitly distinguishes itself from sibling tools by explaining that report_bug is an action within it while a sibling named report_bug exists. It is specific about both the resource (MCPs/tools) and the operations (discover, inspect, run, install).

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 guidance on when to use which path: 'use install only to make an MCP PERMANENT in the active toolkit' and 'prefer invoke for a single/occasional use.' It also explains when invoke should be retried (after connect or checkout links), when to use request_mcp ('asks us to build a NEW MCP when nothing fits'), and what list_tools does ('lists what is callable right now'). Sibling alternatives are named and contrasted.

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 the operation is not read-only, not destructive, and idempotent. The description adds the instruction to include conversation context, which is useful. However, it doesn't disclose what happens after submission (e.g., where the report goes) or side effects beyond basic expectations.

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, punchy sentence that communicates the core action and a key instruction. It's appropriately concise, though it could be slightly restructured to front-load the tool's breadth (bug/feature/feedback) more naturally.

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 feedback tool with no output schema, the description covers what the tool does and the primary usage hint (include conversation). It's sufficiently complete for an agent to invoke correctly, though it omits any error or response 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?

Schema description coverage is 0%, so the description must clarify parameters. It does explain the 'conversation' parameter by mentioning the conversation array for reproduction, but it provides no hints for 'message' or 'context'. Partial value added, but not comprehensive.

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.' This uses a specific verb (report) and resource (bugs/feedback), and it distinguishes from sibling tools like 'marketplace' or 'show_version' by its focus on issue 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 implies when to use the tool (for any bug, missing feature, or feedback) and gives explicit guidance to include the conversation array for reproduction. It doesn't mention alternatives or exclusions, but for a feedback tool the usage context is clear.

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 agent knows this is a safe, non-destructive read operation. The description adds minimal behavioral context beyond that, but it does specify what versions are shown (platform and adapter). No contradiction 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 sentence, concise, and front-loaded with the action. Every word earns its place. No fluff 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?

Given the tool's simplicity (no parameters, no output schema, clear annotations), the description is complete enough. It tells the agent exactly what the tool does. The only minor gap is that it doesn't specify the format of the version output, but that's not critical for a version-check 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, and the schema description coverage is 100% (vacuously). The description doesn't need to explain parameters since 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 'toolkit_info' which likely provides broader 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 implies usage: when you need to know the versions of the MCP platform and adapter. It doesn't explicitly state when not to use it or mention alternatives, but given the tool's simplicity and the sibling context, it's adequate. No explicit exclusions or alternative references are provided.

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 description is not obligated to repeat these. The description adds context about what specific state is returned (installed MCPs, status, accounts, tool counts), which enriches the agent's understanding beyond the annotations. No contradiction exists.

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 primary action ('Returns the current toolkit state') and then enumerates the specific components of that state. Every phrase contributes useful information 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?

Given the tool's simplicity (no params, no output schema), the description fully covers the return content by listing the main categories (MCPs, connection status, accounts, catalog tool counts). The annotations confirm it is read-only and idempotent, so no additional safety or side-effect documentation is needed.

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 and fully covers (100%) the parameter space. According to the rubric, the baseline for 0 parameters is 4, and the description does not need to add parameter semantics since there are none to explain.

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 verb 'returns' and the resource 'current toolkit state', listing specific elements: installed MCPs, connection status, accounts, and catalog tool counts. This is distinct from sibling tools like 'authenticate' or 'connect', which perform actions, while this one is a read-only introspection tool.

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 makes it evident that the tool is used to retrieve an overview of the toolkit's connections and tools, which is clear context for when it would be valuable. However, it does not explicitly state when to use it or mention alternatives, though its name 'toolkit_info' and read-only nature make this fairly unambiguous.

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