ECRVSP Documentos: Primeiro Emplacamento

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

The description discloses behaviors not covered by annotations: the permanent, non-expiring connection when adding to server config, and the session-only nature of token use. It also implies side effects (modifying server config) and provides a recommendation ('Best:').

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 reasonably concise but slightly redundant in the opening sentence ('MCP.AI for IDE agents (Cursor, etc.): log in in the browser, copy the access token') and repeats the 'call with token or no args' idea. Still, it is well-structured with clear two-option flow.

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 complete for an authentication tool: it covers both authentication flows, their consequences, and the input parameter. No output schema exists, so return values need no explanation. Given the simple complexity, all needed context is present.

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 lists one optional 'token' parameter with no description. The tool description explains that providing it authenticates with that token, while omitting it yields a login link, giving full semantic meaning to the parameter.

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 by either providing a token or generating a login link. It is distinct from sibling tools (connect, show_version, etc.) and specifies the authentication mechanism.

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 explicit usage instructions: call with a token to authenticate, or with no arguments to get the login link. It also distinguishes between permanent (server config) and session-only authentication, effectively telling when each mode is appropriate.

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 and idempotentHint, but the description adds valuable conditional return details (authenticated:true, pending[], connect_url). It explains what happens in different states, going beyond the annotation hints.

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, immediately states the primary purpose, and explains the two key states without any 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?

For a simple status tool with no parameters and no output schema, the description adequately covers the return behavior in the main scenarios. It sufficiently explains what to expect 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?

With zero parameters, the schema is trivially covered and there is nothing to clarify. The baseline for 0 parameters is 4, and the description doesn't need to add 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 clearly states the tool 'Returns connection status and URLs', specifying both the action and resource. It distinguishes itself from siblings like 'authenticate' by focusing on status retrieval rather than performing authentication.

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 on when to use the tool by describing behavior in two key scenarios (all providers connected vs. credentials missing). It does not explicitly mention when not to use it or alternatives, but the conditional behavior strongly implies its use as a status check.

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 read-only, idempotent, non-destructive behavior. The description adds value beyond annotations by disclosing the payment model, the official-source nature, that the data is citizen-accessible rather than confidential, and the LGPD data-controller responsibility. It does not contradict 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 compact and front-loaded with the core purpose. The legal and payment notes are relevant to safe use, though some wording is slightly redundant. Overall, it is appropriately sized for the high-level content it conveys.

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?

This is a complex tool with 34 parameters, 13 required, no output schema, and no parameter descriptions. The description covers purpose and legal framing but omits essential invocation details such as what each required field means, how to format inputs, and what result the agent should expect. It is not complete enough for reliable selection and invocation.

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%, and the tool has 34 string parameters with no per-parameter documentation. The description mentions no parameter meanings, required fields, formats, or relationships. Since the schema itself provides only names like 'a3', 'chassi', and 'tipo_restricao', the description completely fails to help the agent invoke the tool correctly.

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 operation as a consultation ('consulta') against a specific official Brazilian source for first-time vehicle licensing ('Primeiro Emplacamento'). It also differentiates the tool from generic sibling tools like authenticate, connect, and marketplace by naming the exact domain and data source.

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 useful context about when this tool is relevant: official-source consultation for first vehicle registration, with no platform credentials needed and prepaid per-query billing. It does not explicitly name excluded cases or alternative tools, but the sibling set is general platform tooling, so the guidance is reasonably 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?

The description discloses important behaviors beyond the annotations: invoke runs non-installed MCPs one-off without bloating the toolkit, credential gaps return a connect link, empty wallet returns checkout/top-up, and write operations require workspace owner/admin. It also explains the prompt library share-link behavior. None of this 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 front-loaded with the core value proposition and every sentence adds distinct functional or behavioral information. It could be more scannable with bullets per action group, but for a 23-parameter hub tool, the density is justified and there is little 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?

Despite no output schema and 23 parameters, the description covers the main flows, return-link behaviors (connect/checkout/shareable prompt link), authorization requirements, and the prompt library. It gives enough detail for an agent to select actions and understand consequences, with only minor gaps on less common parameters.

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, the description carries the full burden and largely succeeds: it explains the action enum via the search/describe/invoke/install/prompt flows, implies query/mcp_id/tool_id/arguments usage, and describes prompt-related params (prompt_body, prompt_vars, publish link). However, some params like limit, conversation, tier_slug, report_context, and cancel_reason are not semantically explained.

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 as the official mcp.ai marketplace: the catalog of MCPs/tools and the execution layer for running them. It names the core sub-actions (search, describe, invoke, install, list_tools, prompt library) and gives concrete example queries, so there is no ambiguity about 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 provides explicit when-to-use guidance: prefer invoke for one-off use, install only for permanent inclusion, request_mcp when nothing fits, and list_tools for what is callable now. It does not explicitly distinguish the marketplace's report_bug action from the sibling report_bug tool or explain when to use sibling authenticate/connect instead, but the internal alternatives are well covered.

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 idempotentHint=true, readOnlyHint=false, and destructiveHint=false, but the description adds no behavioral context beyond input guidance. There is no mention of submission behavior, confirmations, or side effects, which is a gap for a write-oriented 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 two sentences, with the purpose stated first and a single actionable instruction second. It is efficient, front-loaded, and contains no 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?

The purpose is clear and the conversation parameter guidance helps, but the description lacks explicit when-to-use guidance, behavioral outcomes, and explanation of the context parameter. For a simple tool, it is minimally complete but not thorough.

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, the description must compensate. It explains the 'conversation' parameter explicitly and implies 'message' is the report content, but the 'context' parameter is left undocumented. Partial 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 states the tool reports a bug, missing feature, or sends feedback, using the specific verb 'Report' with explicit targets. It distinguishes from sibling tools like authenticate, marketplace, and show_version, which have 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 instruction to include the conversation array with recent messages provides clear context on how to use the tool effectively. However, it does not explicitly mention when to prefer this tool over alternatives or any exclusion cases.

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 clear. The description adds that the tool reports both platform and adapter versions, but it does not describe return format or any edge-case behavior. It doesn't contradict the annotations, and is sufficient but not especially revealing.

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 entire description is a single, front-loaded sentence: 'Show the current MCP platform and adapter versions.' It avoids any wasted words and conveys the core semantics immediately.

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 version inquiry tool, the description is sufficient. It states what is shown (MCP platform and adapter versions) and is accompanied by strong annotations that remove safety ambiguity. The lack of an output schema is acceptable because the tool is simple.

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 properties list is empty. With no parameters to explain, the description does not need to add parameter semantics; the baseline 4 applies for parameter-less tools.

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' and identifies a clear resource: 'current MCP platform and adapter versions.' It is easily distinguished from sibling tools like authenticate or toolkit_info, 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 implies the tool is for checking current version information but offers little explicit guidance on when to use it or which alternatives might be better. Since there are sibling tools like 'toolkit_info' and 'marketplace', a bit more context would help, but the use case is fairly self-evident.

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 read-only, idempotent, and non-destructive behavior, so the bar is lower. The description adds specifics about the returned state (MCPs, accounts, catalog counts) which are useful. No extra behavioral traits like auth needs or side effects are necessary for this simple read action.

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 front-loads the core purpose and then lists the Main features with a colon and comma-separated list. Every element is necessary and informative, with no 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 zero-parameter read-only state getter, the description fully captures the tool's functionality and output. There is no output schema, but the description enumerates all returned data categories. Nothing more 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?

There are zero parameters, and the schema is empty. Per the rubric, this yields a baseline of 4. The description accurately details what information the tool returns without needing to explain parameters.

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' with a clear resource ('current toolkit state') and details the exact data points (installed MCPs, connection status, accounts, catalog tools). This distinguishes it from sibling tools like 'authenticate' or 'connect' which imply different actions.

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 implicitly suggests this is for inspecting toolkit state, but it does not explicitly mention when to use this tool over alternatives, nor does it provide exclusions or compare with siblings. It is clear for a state-query tool, but lacks explicit when-to-use guidance.

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