SERPRO RADAR: Veículo

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

Annotations indicate idempotentHint=true, destructiveHint=false, and readOnlyHint=false. The description adds important context: it initiates a browser login flow, can be called with no args to get a link, or with a token for session login. It also mentions the permanent alternative (config header). This goes beyond annotations by explaining the user interaction flow. However, it doesn't disclose potential side effects like session expiration or security considerations beyond what annotations hint.

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 but quite long and detailed. It front-loads the primary purpose and then explains the two usage modes. It's structured logically, though the sentence is complex. Could be broken into multiple sentences for clarity, but it's informationally dense 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 the tool's complexity (one optional parameter, no output schema, no nested objects), the description covers the main scenarios: browser login with permanent config, session token paste, and no-args link retrieval. It doesn't explain what the return value looks like (e.g., success message or token preview), but since there's no output schema, the description could be more explicit about what to expect. Still, for an authentication flow, the guidance is substantial.

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 one optional string parameter 'token' with 0% description coverage. The description explains that the token is a JWT to be pasted for session-only login, and that omitting it yields a login link. This adds meaning beyond the schema, which only defines it as a string. However, it doesn't delve into token format validation or edge cases. With only 1 parameter and clear context, the baseline is moderate, but the description does explain the parameter's role effectively.

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 for MCP.AI IDE agents via browser login and token. It distinguishes from siblings by focusing on authentication specifically, though it doesn't explicitly mention alternative authentication tools (e.g., 'connect' might be similar).

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 provides guidance on when to use this tool: when needing to log in, with two methods (permanent config header or session-based token paste). It doesn't explicitly state when not to use it, but the context is clear. It could mention alternatives like 'connect' if relevant.

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 covered. The description adds value by disclosing conditional return shapes: authenticated:true with empty pending[] when all providers are connected, and connect_url plus per-install URLs when credentials are missing. This goes beyond the annotations and helps the agent understand expected outcomes.

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 core purpose, and every clause adds useful information. It avoids fluff, repeated terms, or schema redundancy. The conditional details are placed logically after the main statement.

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 parameter-less, read-only status tool, the description covers the main connected and missing-credential cases and describes the relevant return fields since no output schema is present. However, it does not address partial connection states (some providers connected, others not), which may be a realistic edge case. Overall it is reasonably complete but has a small ambiguity gap.

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 parameter semantics are largely irrelevant. Per the baseline rule, a parameter-less tool gets a 4. The schema itself documents 100% coverage with an empty properties object, and the description does not need to clarify any inputs.

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 starts with a specific verb and resource: 'Returns connection status and URLs.' It clearly distinguishes this status-checking tool from the sibling 'authenticate' tool, which presumably initiates or completes authentication. The conditional return details further clarify exactly what the tool does.

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 by describing both fully connected and missing-credential scenarios, but it never explicitly contrasts it with siblings like 'authenticate' or states 'use this to check status before authenticating.' It provides enough behavioral context to infer usage, but not explicit selection 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?

Beyond the annotations (readOnlyHint=false, openWorldHint=true, etc.), the description reveals important behavioral traits: invoke works even when the MCP is NOT installed, performs one-off runs without bloating the tool list, and writes require workspace owner/admin. It also explains the distinction between installed_in_toolkit vs installed_in_workspace. No contradictions 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 dense wall of text, but given the tool's 14 actions and two distinct domains (MCP marketplace and prompt library), every sentence contributes necessary information. It front-loads the core purpose and flow, then covers edge cases and permissions. It could benefit from bullet-point structure, but it remains efficiently worded for its 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?

The description is remarkably complete for a tool this complex: it covers the main flow, invocation mechanics, auth/payment handling, permission requirements, the prompt library, and how search/describe flag installation status. There is no output schema, but the description gives return behavior for key actions (e.g., 'describe returns one MCP's full profile'). No critical context is missing for selecting and invoking 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?

With 0% schema coverage, the description compensates by explaining the core 'action' enum values (search, describe, install, invoke, etc.) and their purposes, plus tool_id and mcp_id roles. However, it does not explicitly detail all 23 parameters (e.g., limit, immediate, prompt_vars, cancel_reason), though many are self-explanatory from names. It adds significant meaning to the most critical parameters but leaves some gaps.

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: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It goes beyond a generic verb by detailing the core flow (search→describe→invoke) and explicitly distinguishing from sibling tools like report_bug and list_tools. The mention of the prompt library adds a second but clearly separated purpose, so no 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?

The description provides explicit when-to-use guidance: 'use install only to make an MCP PERMANENT in the active toolkit...; prefer invoke for a single/occasional use' and outlines the core flow with action=search, describe, invoke. It also gives conditional behaviors for auth and payment: 'invoke returns a connect link' and 'invoke returns a checkout/top-up link (the user opens it, then you retry).' This effectively guides selection among the tool's many actions.

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 adds useful context beyond annotations by instructing users to include the conversation array, implying that the tool expects relevant context for reproduction. It does not explicitly mention side effects, but the annotations already indicate it is not read-only and is idempotent. The description is consistent with the annotations and provides some additional behavioral insight.

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 conveys all necessary information without redundancy. It is well-structured and easy to understand.

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 straightforward reporting tool, the description is sufficiently complete. It covers the main action and the required input. However, it does not mention potential outputs or error handling, but given the absence of an output schema and the simplicity of the tool, this is acceptable.

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 explains the purpose of the 'conversation' parameter ('Include the conversation array with recent messages for reproduction') and implies that 'message' is the core content (bug report or feedback). However, it does not clarify the 'context' parameter at all. Given that the schema provides no descriptions, the description adds partial value but leaves one parameter undefined.

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.' It specifies the action and the type of input expected (conversation array for reproduction), making it unambiguous what the tool does.

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 indicates when to use the tool (when reporting a bug, missing feature, or providing feedback) and provides a specific instruction on how to use it (include the conversation array). This gives clear usage guidance without needing to reference alternative 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?

Beyond the readOnly and idempotent annotations, it discloses no platform credentials required, prepaid credit cost, non-confidential data nature, and LGPD responsibility, adding valuable behavioral 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?

The description is moderately concise but includes some redundant phrasing (e.g., 'Hospedado pela plataforma, sem credenciais da plataforma') that could be streamlined without losing 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?

It provides sufficient context about the official source, cost model, data classification, and legal responsibility, though it omits usage scenarios and any limitations.

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 parameters 'placa' and 'renavam' are not explained at all in the description or schema, and the description does not compensate for the missing schema 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?

The description clearly states the tool performs vehicle consultation from an official source, which is specific and distinguishes it 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 does not specify when to use this tool versus alternatives, nor does it provide any usage scenarios or restrictions beyond the inherent 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 disclose the safety profile (readOnlyHint: true, idempotentHint: true, destructiveHint: false), and the description is fully consistent with these, adding the clarification that both platform and adapter versions are returned. The description doesn't provide further behavioral details, but the annotations lowered the bar. No contradiction exists with 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, front-loaded sentence with zero waste. Every word earns its place. For such a simple tool, this is ideal—no filler, just a clear statement of what the tool does.

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 trivial nature (no parameters, no output schema, read-only annotations), the description captures the essential behavior completely. It could theoretically elaborate on the output format, but the return value (version strings) is self-evident. This is a strong, appropriate description for its scope.

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 zero parameters and 100% schema coverage, there is no parameter documentation burden on the description. Per the rubric, 0 parameters warrants a baseline of 4 as long as the description doesn't confuse parameter semantics, which it doesn't.

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') paired with a clear resource ('the current MCP platform and adapter versions'), making the tool's function immediately obvious. It's a clear, unambiguous statement of what the tool does. However, it doesn't draw any contrast with sibling tools, so it earns a 4 rather than 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?

Usage is implied by the description's straightforward purpose—you'd use this when you need version information. However, there's no explicit guidance on when to use this over siblings, nor any exclusionary language or alternative suggestions. It's perfectly functional but does no more than imply usage.

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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is established. The description adds useful behavioral context by specifying the granularity of the returned state (installed MCPs, per-MCP connection status, accounts, catalog tool counts), which goes beyond simply saying 'returns toolkit info.'

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 efficiently lists all returned state components without repetition or filler. Every phrase adds 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 a zero-parameter, read-only state inspection tool with no side effects, the description fully explains what the tool returns and covers the necessary context. No output schema exists, but the description enumerates all key return components, making it complete enough for this simple 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, so the schema provides complete coverage and the description has no parameter burden. The baseline of 4 is appropriate because no parameter semantics could add significant value beyond the empty 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 the specific verb 'Returns' and names a clear resource—the current toolkit state—while enumerating its exact contents (installed MCPs, connection status, accounts, catalog tool counts). This sufficiently distinguishes it from sibling tools like show_version 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 states what the tool returns but gives no explicit guidance on when to choose it over alternatives or when not to use it. Usage is only implied by the nature of the tool as a state/status inspection endpoint.

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