ECRVSP Documentos: Opções de Placa

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

Annotations indicate this is a safe, non-destructive, idempotent write operation (readOnlyHint false). The description adds context about the non-expiring permanent connection and session-based option, which enrich the behavioral picture without contradicting the annotations. Minor gap: no mention of error handling or invalid token behavior.

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 tight sentences deliver a complete workflow: browser login, token capture, two integration paths, and the fallback to obtain the link. No fluff, all information front-loaded and directly relevant.

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 single-optional-param tool with no output schema, the description covers all user actions, both modes, and the meaning of each parameter. It is self-sufficient for an IDE agent to correctly invoke the tool in any scenario.

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 fully compensates by explaining the optional 'token' parameter: what it is (a JWT pasted by the user), when to provide it, and that omitting it triggers a login-link response. This is clear and actionable 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 defines the tool's purpose: to authenticate an IDE agent to MCP.AI. It specifies the verb 'log in' and the resource (access token), and distinguishes itself from siblings like 'connect' and 'marketplace' by focusing on authentication flow.

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 explicitly explains two usage modes: permanent config via header and session-only via token parameter. It also instructs calling with no args to retrieve a login link, providing unambiguous when-to-use guidance and even a recommended approach.

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?

Despite annotations (readOnlyHint, idempotentHint) already indicating safety, the description adds valuable conditional response details (authenticated:true vs connect_url) that the annotations don't cover. This enhances transparency about dynamic behavior.

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. The first states the primary purpose, the second explains conditional outputs. No filler or redundant 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 zero-parameter read-only tool, this description fully explains expected responses. No output schema is provided, but the description covers key return fields and edge cases, making it complete for its simplicity.

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?

No parameters exist, and schema coverage is 100% (vacuously). Baseline 4 applies as there is no additional parameter information needed.

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?

Clearly states it returns connection status and URLs, with specific response variations. Distinguishes itself from siblings like 'authenticate' and 'show_version' by focusing on connection diagnostics.

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?

Implies when to use (to check connection status/URLs) but doesn't explicitly mention alternatives or exclusions. Context is clear from the conditional behavior described.

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 relevant behavioral context such as requiring prepaid credits, being hosted by the platform, and not requiring platform credentials. It also clarifies that the data is not confidential and is subject to LGPD, which helps set 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 dense sentence that includes multiple pieces of information, which can be hard to parse. It could be organized into separate sentences for clarity, but it is not excessively long.

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 lacks information about what the tool returns or how to interpret the output. It also fails to explain the parameter requirements, making it incomplete for an agent to use effectively.

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 lists six parameters (a3, cpf, cnpj, a3_pin, chassi, opcoes, login_cpf, login_senha) but the description provides no explanations for any of them. Without parameter descriptions, agents cannot correctly populate the 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 clearly states that this tool performs a query (consulta) on official sources for plate options (Opções de Placa). It explicitly mentions it queries official Brazilian data, giving a concise purpose.

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 compared to alternatives. It provides some context about payment and credentials but lacks explicit usage guidance or scenarios.

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 (openWorldHint, non-readonly, non-idempotent), the description discloses that writes require workspace owner/admin, that invoke runs a tool one-off without adding it to the toolkit, and that missing credentials/payment yield connect/checkout links. 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 text is dense and front-loaded with the key purpose, but it is one long paragraph covering many actions and edge cases, making it hard to scan. Bulleting or separating the marketplace core from the prompt-library section would improve structure without adding length.

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 23-parameter, 14-action router with no output schema, the description covers a lot: core flow, install vs invoke tradeoffs, permissions, credential/payment outcomes, and the separate prompt library. It omits return formats for each action, but the breadth of coverage is strong.

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 adds meaning for action values (search, describe, invoke, install, prompt actions) and explains the tool_id/mcp_id relationship, but with 23 parameters and zero schema descriptions many parameters (limit, query, arguments, immediate, cancel_reason, prompt_targets) are only indirectly covered or left unexplained. This is a partial but incomplete compensation.

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 catalog and runtime, then specifies the core search→describe→invoke flow. This distinguishes it from sibling tools (authenticate, connect, show_version) and resolves the otherwise generic name '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?

It gives explicit guidance: use invoke for one-off use, install for permanent toolkit membership, and request_mcp when nothing fits. It explains when invoke returns a connect/checkout link and says to retry afterward, making tool-selection decisions concrete.

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 indicate idempotent and non-destructive behavior, and the description adds that the conversation array is for reproduction. However, it does not clarify side effects (e.g., whether the report is sent to a server) or any additional behavioral nuances, so transparency is moderate.

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, clear sentence with no redundant details. It is well-structured and easily understood.

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's purpose and basic usage are covered, but the description lacks details about the expected format of the conversation array, the nature of the 'message' field, and any output or error handling. It is adequate but not comprehensive.

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 provides no descriptions for the three parameters. The description only mentions that the conversation array should contain recent messages, leaving 'message' and 'context' ambiguous. Parameter semantics are largely undocumented.

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 explicitly states the tool's purpose: reporting bugs, missing features, or sending feedback. It is distinct from all sibling tools (authenticate, connect, marketplace, etc.), which handle unrelated operations.

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 bug reports or feedback) and includes a specific instruction to include the conversation array for reproduction. It does not explicitly state when not to use it, but no alternative tool exists, so the guidance is sufficient.

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 minimal behavioral context beyond the word 'current,' which implies live queries. It does not mention return format, network calls, or other behavioral aspects.

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 short sentence of 9 words, front-loaded and free of fluff.

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 no-parameter version tool, the description sufficiently explains the output and purpose. Annotations cover safety, and no output schema exists, requiring the description to indicate return values, which it does.

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?

No parameters exist, so the schema covers 100% of parameters. With 0 params, the baseline is 4; the description need not explain any 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 with a specific verb ('show') and resource (MCP platform and adapter versions). It distinguishes from siblings like authenticate or report_bug, 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 implies usage for checking version information, but does not explicitly compare against siblings like toolkit_info, which may provide similar info. No when-not-to-use guidance is 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?

The annotations (readOnlyHint=true, destructiveHint=false, idempotentHint=true) already cover the read-only nature. The description adds value by detailing exactly what is returned (installed MCPs, connection status, accounts, and catalog tool counts), which is useful for an agent planning next steps. 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, well-structured sentence that lists the key components without unnecessary verbiage. It is front-loaded with the main verb and immediately conveys the scope, making it 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?

Given zero params and no output schema, the description is complete for its purpose. It covers what the tool reports and hints at the structure of the return value. An agent can infer the tool is a read-only state query, which is sufficient 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?

There are zero parameters, so the description doesn't need to explain parameter semantics. The schema is empty, and the description compensates by clarifying the tool's output and purpose, making it a useful baseline.

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 what the tool does: 'Returns the current toolkit state' and enumerates its components (installed MCPs, connection status, accounts, catalog tools). It is specific and distinguishes from siblings like authenticate and connect, which are action-oriented, whereas toolkit_info is informational.

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 state, but does not explicitly state when to use it versus alternatives. However, given the sibling tools are mostly action-oriented, the description's clear intent to provide a snapshot of the toolkit is sufficient context for an agent.

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