ECRVSP Documentos: Placas de Primeiro Emplacamento

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

The description goes beyond the annotations (which already indicate idempotentHint=true, readOnlyHint=false) by explaining that it generates a browser login link, that the token can be stored permanently in config, and that the session-only option is non-expiring when configured. It also mentions the requirement for the user to paste the token, and the optional token parameter. This is comprehensive and adds significant context beyond the structured data.

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 concise and front-loaded: it starts with the tool's purpose and immediate instructions, then details the two use modes. It uses effective formatting with a colon introducing the code snippet for the config header, and the sentence structure is efficient—each clause adds necessary 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 tool with only one optional parameter and no output schema, the description is remarkably complete. It covers all possible modes of operation (config-based, session-based with token, and no-args to get the link), the authentication flow, and provides a concrete example of the required header format. The complexity is low, but the description leaves no ambiguity.

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 only one optional parameter (`token`) with 0% coverage in the description, but the description explicitly explains the token parameter's purpose: it expects a JWT string when the user has pasted it, and that calling with no args will provide the link. This fully compensates for the schema's lack of description, effectively documenting the only 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: authentication via browser login and token retrieval, with options for permanent config-based or session-based authentication. It specifies the resource (MCP.AI for IDE agents) and the action (log in, get access token, authenticate), distinguishing it from sibling tools like connect 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?

It provides explicit guidance on when to use this tool: for initial authentication, and even explains the two modes (permanent via config header, session-based via token parameter). It also tells the agent what to do: call with token after user pastes, or with no args to get the link. This is more actionable than typical tool descriptions and clearly implies when to use it versus alternatives like connect (which likely handles other connection aspects).

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 value by detailing the two output scenarios (all providers connected vs credentials missing) and the specific fields returned, giving agents insight into response behavior without contradicting 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 two sentences, front-loaded with the primary action, and every clause adds meaningful behavioral detail. There is no wasted wording or redundancy with annotations or schema.

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 status tool with no output schema, the description adequately explains return values in the two primary states. However, it does not account for partial connection states or detail the contents of the pending array, leaving a minor gap. Overall, it is sufficient for the tool's 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?

This tool has zero parameters, so the schema already covers everything. The description adds no parameter-specific information, but none is needed. Baseline 4 is appropriate.

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 clearly states the tool provides connection status and URLs. It distinguishes itself from sibling tools like 'authenticate' by describing a read-only status check rather than an action. The conditional output details (authenticated:true with empty pending[] vs connect_url when credentials are missing) make the purpose unambiguous.

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 connection status, but it does not explicitly state when to use it versus alternatives like 'authenticate' or when it should be called before other tools. There is no exclusion criteria or 'use this when' guidance, only implied 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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds context about payment (prepaid credits), data source (official Brazilian sources), and LGPD responsibilities, which is useful. However, it doesn't disclose details like rate limits, response format, or what happens on failed queries, but given the annotations, the bar is lower and the added context is adequate.

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 paragraph, reasonably concise, and front-loaded with the main purpose. It includes necessary context about payment and LGPD without excessive verbosity. However, it could be more structured (e.g., bullet points) but is acceptable.

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 (17 parameters, 9 required, no output schema, no parameter descriptions), the description is insufficient. It does not explain the meaning of key parameters, the expected input format, or the output structure. The description covers the business context but leaves the agent without enough information to correctly invoke the tool. The lack of output schema and parameter documentation makes this a significant 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?

Schema description coverage is 0%, and the description provides no parameter-level details. With 17 parameters and 9 required, the description does not explain what each parameter means (e.g., a3, a3_pin, login_cpf, chassi, categoria, etc.). The description only mentions the general purpose, leaving the agent to guess parameter semantics. This is a significant gap given the high parameter count and zero 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 queries official Brazilian sources for first registration license plates (ECRVSP Documentos: Placas de Primeiro Emplacamento), with a specific verb 'consulta' and resource. It distinguishes from siblings by mentioning the specific domain and official source, though it doesn't explicitly contrast with other tools.

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 querying official vehicle registration data, and mentions payment via prepaid credits and LGPD compliance, but does not explicitly state when to use this tool versus alternatives or when not to use it. It provides context about the service but lacks clear usage boundaries.

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 behavioral nuances beyond annotations: invoke works even when the MCP is not installed, performs a one-off execution without bloating the toolkit, and returns connect/checkout links when credentials or payment are missing. It also reveals the hidden install behind invoke and the permission requirement for all 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 text is a dense single paragraph but logically organized: purpose, core flow, KEY note, usage guidance, permission note, and prompt library. Each sentence adds information, though bullet points or section headers would improve scanning for such a multi-action tool.

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 14-action, 23-parameter tool with no output schema and minimal annotations, the description covers core actions, permissions, auth/funding fallbacks, and prompt-library features well. It still omits parameter-specific details and return-value expectations, leaving some gaps for the agent to infer.

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 high-level action flow and the conceptual meaning of mcp_id, tool_id, and prompt variables, but it leaves most of the 23 parameters undocumented in prose. With 0% schema coverage, the description partially compensates by explaining the core orchestration, yet many fields remain opaque.

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 opens with a precise 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' stating the resource and core capability. It enumerates distinct sub-actions (search, describe, invoke, install, prompt library) and clarifies their roles, setting it apart from sibling tools like toolkit_info and authenticate.

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 decision rules: 'prefer invoke for a single/occasional use' vs. 'Use install only to make an MCP PERMANENT in the active toolkit.' It also explains when to use search vs describe vs invoke, when to use request_mcp, and notes that writes require workspace owner/admin.

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 idempotentHint=true, readOnlyHint=false, destructiveHint=false. The description doesn't contradict these. It adds that the tool expects a conversation array for reproduction, which is useful context. However, it doesn't disclose any other behavioral traits like whether it creates a ticket, sends an email, or what happens after submission. With annotations providing some safety profile, the description adds moderate value but not deep transparency.

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 purpose, and every word earns its place. It's concise and structured effectively.

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 (3 params, no output schema, no nested objects), the description provides enough for a basic understanding. It includes purpose and a key usage hint. However, it could mention what happens after reporting (e.g., response format) but this might be unnecessary given the tool's nature. The completeness is adequate for a feedback 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?

Schema description coverage is 0%, so the description must compensate. It mentions 'Include the conversation array with recent messages for reproduction' which explains the 'conversation' parameter, but doesn't explain 'message' or 'context' beyond their names. The description adds minimal additional meaning over the schema, leaving the agent to infer that 'message' is the main content. Given only one required parameter, it's acceptable but could be better.

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 uses a specific verb 'report' and resource (bug/feedback), and distinguishes from siblings like 'show_version' or 'toolkit_info' by focusing on user feedback. It also provides an additional hint about including conversation for reproduction.

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 indicates when to use this tool: when reporting bugs, missing features, or feedback. It doesn't explicitly state when not to use it or name alternatives, but given the sibling tools are mostly unrelated (authenticate, marketplace, etc.), the context is clear. It also gives a guideline about including the conversation array, which helps the agent know how to use it effectively.

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-mutating operation. The description adds the scope (platform and adapter versions) but no additional behavioral traits such as rate limits or output specifics. It does not contradict 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, clear sentence that immediately conveys the tool's purpose. No wasted words, front-loaded with the verb 'Show' and the object. Excellent conciseness.

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 version-info tool with no parameters and no output schema, the description is fully self-contained. It tells the user exactly what information will be displayed, and the richness of annotations covers safety aspects. Sibling tools are distinct enough that no further context 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 input schema has zero parameters, so the baseline is 4. The description has nothing to add beyond the schema since there are no parameters to explain. No further information is necessary.

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' and clearly identifies the resource: 'current MCP platform and adapter versions.' This unambiguously states what the tool does and distinguishes it from 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 implies usage: use when you want to see version information. However, it does not explicitly mention when not to use it or provide alternatives, even though a sibling tool like 'toolkit_info' might also contain version details. Thus the guidance is inherent but not explicit.

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, establishing a safe read operation. The description adds value beyond this by specifying exactly what 'state' means (MCPs, connection status, accounts, catalog tool counts), enriching the agent's understanding of the response content without contradicting 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?

A single, well-structured sentence that front-loads the verb 'Returns' and the object 'current toolkit state', followed by a colon-delimited list of the four data categories. Every word earns its place with zero waste.

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 info tool with rich annotations and no output schema, the description is largely sufficient, covering what is returned. Slightly docked because it doesn't hint at the structure of the return value (e.g., flat vs. nested, field naming), though this is a minor gap for an info 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?

Zero parameters means no schema gaps to compensate for, so the baseline of 4 applies. The description does the necessary work here by telling the agent what the output will contain, which is more relevant than parameter docs for a no-arg tool.

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?

Clear verb 'Returns' plus specific resource 'current toolkit state' enumerated as installed MCPs, connection status, connected accounts, and catalog tool counts. The level of specificity (listing all four data points) leaves no ambiguity about the tool's function and distinguishes it from the informational sibling 'show_version'.

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 this is the go-to for inspecting toolkit state, but it never explicitly addresses when to use this over 'show_version' or other sibling tools, nor does it mention any alternatives or exclusions. Usage is implied rather than stated.

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