DETRAN MG: Pontuação CNH

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

Annotations already provide idempotentHint and destructiveHint. The description adds meaningful context: pasted tokens are session-only, no-args returns a login link, and config-based tokens are permanent and non-expiring. It does not detail return values or failure modes, but the added context goes beyond 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 three sentences with clear structure ('Best:', 'Or:') and front-loaded purpose. It is slightly dense but every sentence contributes necessary context 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 one-parameter authentication tool with no output schema, the description covers the login flow, token usage, and the permanent-config alternative. It lacks error-handling or prerequisite details, but the core usage is sufficiently 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?

Schema description coverage is 0%, so the description must compensate. It fully explains the single optional token parameter as a JWT pasted by the user, and that omitting it triggers the login-link flow. This is complete and unambiguous.

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 authenticates IDE agents to MCP.AI via browser login and token exchange. It distinguishes itself from siblings by focusing on authentication and explicitly describing the two login modes (config header vs session token).

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 recommends adding the token to the server config for a permanent connection versus using the tool for a session-only login. It also clarifies when to call with a token versus with no arguments to get the login link.

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 readOnly and idempotent, and the description adds behavior details such as returning 'authenticated:true' and connect URLs. This goes beyond the annotations to explain what the tool actually does in different states, fully disclosing its read-only nature.

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 (two sentences) and well-structured, covering the main purpose and two key outcomes without unnecessary detail. It is easy to read and 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?

Given no output schema, the description sufficiently explains the return values by specifying the two possible outcomes (authenticated with empty pending[] or connect URLs). This covers what the caller needs to know about the result, making it complete 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 no parameters, so schema coverage is 100%. The description does not need to explain any parameters, and the baseline of 3 applies as no additional parameter semantics are required.

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, with explicit scenarios for all providers connected and missing credentials. It distinguishes itself from siblings like 'authenticate' by focusing on status checking 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 implies usage for checking connection status before deciding on authentication, but does not explicitly mention alternatives or when not to use it. The scenarios provide some guidance on conditions (e.g., when credentials are missing), which is implicit but not as direct as the high-quality example.

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 meaningful behavioral details beyond the annotations: it mentions the tool is hosted by the platform, requires prepaid credit, involves official sources, and notes LGPD compliance (client is data controller). It also clarifies the data is not confidential. These details enhance 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 somewhat repetitive, repeating phrases like 'consulta em fonte oficial' and 'fontes e órgãos oficiais brasileiros' and mentioning LGPD twice. It could be more concise, though 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 essential information for practical use: it does not specify what the parameters represent, what the return value is, or how the query is performed (e.g., required authentication flow). The general context about official sources and payment is present, but the operational details are missing.

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 provides no explanation of the five parameters (login_cpf, login_senha, pkcs12_cert, pkcs12_pass, registro_cnh). The schema has zero coverage for these properties, and the description does not compensate, leaving users to guess what each parameter means.

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 queries CNH points (Pontuação CNH) from an official source, which is specific enough. However, it could be more explicit about the exact function (e.g., retrieving a driver's point balance) and does not mention the output format.

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 some usage context: it requires prepaid credit and does not need platform credentials. It also indicates the data is from official Brazilian sources. However, it does not explicitly state when to use this tool over alternatives, nor does it explain any prerequisites beyond payment.

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 reveals key behavioral traits beyond the sparse annotations: invoke runs one-off without installing, credential gaps produce connect links, empty wallets produce checkout links, and writes require workspace owner/admin. It also notes installed_in_toolkit vs installed_in_workspace flags and the login-free prompt share link, giving the agent important operational 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 highly information-dense but is delivered as a single run-on paragraph with heavy capitalization, semicolons, and compressed clauses. Every sentence adds value, but the lack of bullets, sections, or line breaks makes it harder to parse than necessary for such a complex 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 23-parameter, 14-action tool with no output schema, the description covers the core flows, permissions, billing/auth redirects, prompt library outputs, and the key distinction between one-off invoke and permanent install. Gaps remain around exact return shapes, error handling, and less-common actions like resume, immediate, and tier_slug, but the overall context is largely sufficient.

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 and 23 parameters, the description does substantial compensating work by explaining the meaning of action values and key parameters like tool_id, arguments, mcp_id, and prompt_* fields. However, several parameters such as immediate, tier_slug, conversation, cancel_reason, and cancel_comment are never explained, so the agent must infer their 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 identifies the tool as the official mcp.ai marketplace catalog and execution layer, and it explains the core search → describe → invoke flow. It is broad and hub-like rather than a single verb+resource, and it does not explicitly differentiate itself from the sibling report_bug tool, but its overall purpose is unmistakable.

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 guidance is explicit and extensive: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', and 'list_tools lists what is callable right now'. It clearly contrasts invoke vs install, describes the search/describe flow, and distinguishes prompt-library actions from MCP 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?

Annotations already indicate readOnlyHint=false, destructiveHint=false, and idempotentHint=true, covering the safety profile. The description adds context about including the conversation for reproduction, but does not disclose any additional behavioral details (e.g., side effects, internal processes). This is acceptable given annotation coverage.

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 sentences, both purposeful. The first states the purpose, the second gives a specific actionable instruction. 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?

The tool is simple (3 parameters, no output schema), and the description covers purpose and one parameter. However, missing explanations for 'message' and 'context' leave gaps. It is adequate for a low-complexity tool but not 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?

Schema description coverage is 0%, so the description must compensate, but it only explains the 'conversation' parameter (for reproduction). It does not clarify the meaning of 'message' (the required field) or 'context' (the defaulted string). This is insufficient for an agent to correctly populate all 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 clearly states the tool's function: 'Report a bug, missing feature, or send feedback.' This is specific verb+resource, and none of the sibling tools (authenticate, connect, etc.) relate to bug reporting or feedback, so it is well distinguished.

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 usage context: it is for reporting issues, and it instructs the agent to include the conversation array for reproduction. It does not mention when not to use it, but since there are no alternative tools for this purpose, this is adequate.

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 is consistent with the annotations (readOnly, idempotent, not destructive). It doesn't elaborate on side effects, but the annotations already cover these aspects, and the description adds no contradictory information.

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 appropriately sized for the tool's simplicity.

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 and lack of output schema, the description fully covers what the tool does. It is complete and leaves no ambiguity about its purpose.

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 no parameters, so the schema coverage is complete. The description correctly omits any parameter explanations, as there is nothing to add beyond the 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 states the tool's function: showing current MCP platform and adapter versions. It uses the verb 'show' and specifies the resource, distinguishing 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?

While the description doesn't explicitly state when to use this tool over alternatives, the purpose is unambiguous and there is no competing tool for retrieving version info. The context of sibling tools makes usage obvious.

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, idempotentHint, and destructiveHint, so safety info is covered. The description adds valuable context about the return payload details (installed MCPs, connection status, accounts, tool counts), which is not deducible from annotations alone. No contradictions.

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?

Single sentence, front-loaded with the main purpose, and every clause earns its place by specifying a distinct aspect of the returned state. No fluff or 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 status tool, the description fully captures the scope and return contents. No output schema exists, but the description enumerates all key data points an agent would need. Sibling tools are diverse but none overlap with this functionality.

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 0 parameters, so the description does not need to explain parameter usage. Baseline for 0 params is 4, and the description correctly focuses on the output rather than nonexistent 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 uses a specific verb ('Returns') and specifies the resource ('current toolkit state') and the exact components covered (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from siblings like show_version (version info) and authenticate/connect (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 implies when to use this tool: for inspecting the overall toolkit state without side effects. It doesn't explicitly mention alternatives or when not to use it, but the zero-parameter design and read-only intent make the context clear. Lacks an explicit 'use instead of X' pointer.

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