ECRVSP Multas RENAINF: Por Placa

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

The description adds value beyond annotations by clarifying the two flows (link retrieval and token submission), the permanence of config-based vs session-only auth, and the idempotent nature of calling with no args. Annotations already declare idempotentHint=true, and the description aligns without contradiction. It does not detail side effects like token storage, but the context is sufficient for a simple auth tool.

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, front-loading the audience and core purpose. It is organized into two alternatives (config vs session) without fluff. It is slightly long due to conversational tone, but every sentence adds value and the structure is clear.

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 a single optional parameter and no output schema, the description adequately covers both invocation modes and the outcomes (link or token acceptance). It does not describe return values, but that is acceptable given the simplicity and lack of output schema. It provides enough context for an agent to decide and invoke 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?

With schema coverage at 0%, the description compensates by explaining the 'token' parameter as a JWT to be pasted, and that omitting it yields a link. This clarifies the parameter's purpose and usage, though it could be more explicit about optionality and expected format. Still, it adds meaningful meaning beyond the bare 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 clearly identifies the tool as an authentication mechanism for IDE agents, with specific actions: logging in via browser, copying a token, and either adding it to config or passing it as a parameter. It distinguishes from siblings like 'connect' by focusing on token-based auth.

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 explicitly explains when to use each mode: 'Best: add it to this server's config...' for permanent sessions, or 'call with token' for session-only, and 'with no args to get the link'. It gives clear conditional instructions and alternative approaches, leaving no ambiguity about invocation.

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 annotations, the description explains how output differs based on provider connection state: authenticated:true with empty pending[] when connected, or connect_url for toolkit and per-install URLs when credentials are missing. This adds useful behavioral context not provided by the structured annotations alone.

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 extremely concise: two sentences with no filler. The primary purpose is front-loaded, and the second sentence adds essential conditional behavior 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?

Given zero parameters, rich annotations, and no output schema, the description covers the necessary state-based return scenarios well. It could be even stronger with an example output or explicit note about when to use this over `authenticate`, but it is largely 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 input schema is already fully understood. The description adds no parameter details nor does it need to; the baseline of 4 applies given the minimal parameter surface.

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 specifies that the tool returns connection status and URLs, using a concrete verb and resource. It also differentiates the tool from siblings like `authenticate` by describing the authenticated:true state and pending URL behavior.

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 explicitly state when to use this tool versus alternatives such as `authenticate` or `toolkit_info`. While it describes states and outputs, it provides no direct guidance on selection criteria or when not to use it.

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, openWorldHint=false, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context: queries official Brazilian government sources, returns the same data available to citizens, is not confidential data, involves prepaid per-query billing, and imposes LGPD responsibilities on the client as data controller. This exceeds what annotations provide without 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?

Four sentences cover purpose, hosting/billing, data source, and legal obligations. The information is logically ordered and front-loaded with the primary purpose. Minor deduction for the dense acronyms (ECRVSP, RENAINF) and boilerplate LGPD language that could be replaced with parameter-related guidance.

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 high complexity (8 params, 5 required, no output schema, no parameter descriptions), yet the description provides no information about return values, date formats, auth parameter roles, or how 'exigibilidade' affects the request. The legal and billing disclaimers, while relevant, do not help an agent construct a correct call or interpret the response, leaving critical gaps for a typical integration workflow.

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% across 8 parameters, and the description fails to explain any of them. Only 'placa' is inferable from the tool name, while a3, a3_pin, login_cpf, login_senha, data_inicio, data_fim, and exigibilidade remain entirely undocumented. The phrase 'sem credenciais da plataforma' gestures at authentication but is too vague to compensate for the lack of parameter 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?

Describes the tool as querying Brazilian traffic fines by license plate ('Por Placa, consulta em fonte oficial'), making the core verb and resource clear. Distinguishes from siblings in that no sibling is a similar query tool, though the purpose is somewhat buried under promotional and legal text. Loses a point for unnecessary jargon and extraneous detail.

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?

No explicit guidance on when to use this tool versus alternatives, no prerequisites beyond paying with prepaid credit, and no exclusion criteria. The mention that it queries the same data available to citizens implies access limits but does not help an agent decide between this and another tool. Score 2 due to the complete absence of comparative or conditional usage 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?

The description discloses important behavior beyond annotations: invoke works even if the MCP is not installed, runs one-off, does not bloat the tool list, may return connect or checkout links, and writes require workspace owner/admin. It also explains the permanent-toolkit effect of install. No contradiction with the annotations 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 long but every clause earns its place given the tool's 14 actions and complex semantics. It front-loads the marketplace's role and core flow, then adds key distinctions and prompt-library coverage 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?

Despite no output schema and a very large input schema, the description covers the main flows, key return shapes, permissions, authentication/payment edge cases, and prompt-library behavior. It is complete enough for an agent to select the right action and invoke the tool 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?

Given 0% schema description coverage and 23 parameters, the description compensates partially by explaining action flows, tool_id/arguments, prompt vars, and key return links. However, many parameters remain unexplained—limit, immediate, tier_slug, cancel_reason, conversation, request_details, and several prompt_* fields—so the agent would still need to infer their meaning from defaults and names.

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 marketplace as the mcp.ai catalog and execution layer, with specific verbs and resources: search, describe, invoke, install, and prompt-library actions. It distinguishes itself from sibling tools like authenticate/connect by explaining it is the in-platform catalog and runtime, not a single-purpose helper.

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 guidance is given for when to use invoke versus install: 'prefer invoke for a single/occasional use' and 'use install only to make an MCP PERMANENT'. It also covers list_tools, describe, subscribe/cancel, report_bug, request_mcp, and the prompt-library actions, giving the agent a clear decision framework.

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 idempotentHint=true and destructiveHint=false, so the safety profile is known. The description adds the important behavioral note that the conversation array should be included for reproduction, which goes 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 tightly written in two sentences, leading with the core purpose and then adding the key usage detail. There is no redundant content, and every word serves a purpose.

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 low complexity (simple feedback mechanism, no output schema, one required parameter), the description is sufficient. It explains the purpose and the key reproduction requirement, though it could optionally clarify what happens after reporting (e.g., that a report is created).

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 explicitly mentions the 'conversation' parameter and its purpose (for reproduction), which adds meaning beyond the schema. However, it does not explain the 'message' (required) or 'context' parameters, and since schema description coverage is 0%, the description only partially compensates for the missing parameter 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 the action (report) and the resource (a bug, missing feature, or feedback). It also includes specific guidance to include the conversation array for reproduction, which distinguishes it from unrelated 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 clearly indicates when to use the tool: for reporting bugs, missing features, or sending feedback. It does not explicitly state when not to use it, but given the sibling tools are entirely unrelated, there is no ambiguity about the appropriate 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 (readOnlyHint, idempotentHint) indicate a non-destructive, read-only operation, and the description's verb 'show' aligns perfectly. The description adds specificity about what versions are displayed, going beyond what annotations imply. 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?

A single, front-loaded sentence containing all essential information. No fluff or repetition; every word contributes meaning.

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 such a trivial tool with no inputs and no output schema, the description fully covers what it does. It specifies both 'platform' and 'adapter' versions, giving the agent enough context to invoke correctly without needing more detail.

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?

Since there are no parameters shadows, the schema coverage is 100%, leaving nothing undocumented. The baseline for 0-parameter tools is 4, and the description correctly omits parameter details as none exist. It adds no redundant parameter information.

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 precise verb 'Show' and identifies the resource ('current MCP platform and adapter versions'), distinguishing it from sibling tools like connect or authenticate. It clearly states what information is retrieved without ambiguity.

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 it doesn't explicitly contrast with alternatives, the description makes it obvious when to use this tool (e.g., to check versions). There are no exclusions or caveats. For a tool this simple, explicit when-not guidance is unnecessary, and the purpose implies its usage context clearly.

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 read-only, idempotent, non-destructive behavior. The description adds useful context by enumerating what the state includes, which helps set expectations without contradicting annotations. It does not mention side effects (none needed), but the added detail justifies a score above 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 a single, concise sentence that packs all necessary information without redundancy or fluff. It is well-structured and 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?

There is no output schema, so the description must explain what the tool returns. It does so explicitly by listing the components of the toolkit state, making the return value fully understandable.

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 coverage is complete. Since there are no parameters to describe, the baseline of 4 applies, and the description does not need to add parameter details.

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 the current toolkit state and specifies the exact information included (installed MCPs, connection status, accounts, catalog tool counts). This is a specific verb + resource, and it stands apart 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 usage for checking overall toolkit status but does not explicitly mention when to use this tool versus alternatives. It lacks explicit guidance on scenarios where this would be preferred over other tools, making it merely implied rather than clearly stated.

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