DETRAN PR: CNH

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

Annotations show idempotent (idempotentHint=true) and non-destructive (destructiveHint=false). The description adds context beyond these by detailing the two modes: permanent config header (modifies config) and session-only login (sets a temporary token). It explains the login flow and token storage 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?

The description is moderately long but well-structured, starting with the purpose then 'Best:' and 'Or' to guide the agent. Each sentence adds value—the login process, the two authentication modes, and invocation patterns. It avoids redundancy and maintains a logical 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?

Given the authentication flow and absence of an output schema, the description covers both usage modes and the expected response when calling with no args (getting the link). It explains the token parameter's purpose and when to use each method, making it sufficient for an agent to act 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?

Schema has one optional parameter 'token' with 0% description coverage, so the description must compensate. It does so fully by explaining that token is the JWT to paste for session-only login and that omitting it returns the login link. No other parameters exist, so this is complete.

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 to MCP.AI by logging in the browser and copying an access token, with two methods (permanent config header or session token). It specifically identifies the resource and action, and differentiates from siblings like 'connect' by its authentication focus.

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 usage context: 'Best: add it to this server's config as a header' for permanent setup and 'Or paste it here for a session-only login' for session use. It also instructs to call with or without the token ('call with { token: "<jwt>" } after the user pastes, or with no args to get the link'). However, it does not explicitly mention alternatives or when not to use, missing a full 'when-not' clause.

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 non-destructive, so safety is covered. The description adds value by explaining the output semantics in different scenarios (all providers connected vs missing credentials), which goes beyond the annotation fields.

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 word adds value. It avoids redundancy and is well-structured.

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 read-only status tool with no output schema, the description covers the main states (authenticated and missing credentials). It might miss edge cases like partial connectivity, but overall it provides sufficient context for an agent to understand the tool's behavior.

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 is empty and coverage is 100%. The description does not need to explain parameters, and it appropriately focuses on the return behavior. Baseline 4 for zero 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 returns connection status and URLs, with specific details about the two response cases (authenticated:true vs connect_url). This distinguishes it from sibling tools like authenticate, which likely initiates authentication rather than querying status.

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 explaining its behavior for connected vs missing credentials, but it does not explicitly mention alternatives or state when not to use it. There is no comparison with sibling tools like authenticate or toolkit_info.

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 read-only and non-destructive annotations, the description discloses the paid, prepaid-credit model, hosting context, and LGPD data-control responsibilities. It also clarifies data is not confidential, adding useful legal and 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 brief and front-loaded with the tool's purpose, then adds service and legal context in two additional sentences. No wasted words, though the paragraph structure could be improved.

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 requiring PKCS#12 certificates and multiple Brazilian ID numbers, the description omits crucial instructions on obtaining or formatting these values. The lack of output schema or return-value details further limits an agent's ability to judge success.

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 zero information about the six required parameters, which are only listed as bare names like 'modelo' and 'validade_cnh' with no format or purpose explained. With 0% schema coverage, this is a critical gap that prevents correct parameter population.

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 it as a consultation tool for CNH data from DETRAN PR ('consulta em fonte oficial'), distinguishing it from generic sibling tools. However, it does not list specific use cases or return data, leaving scope slightly ambiguous.

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?

No guidance is given on when to prefer this tool over alternatives; it only provides service details like payment and legal compliance. The description does not mention exclusions or prerequisites for use, though the sibling list contains no direct equivalent.

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?

Adds rich behavior beyond annotations: invoke works even when the MCP is not installed, runs one-off without bloating the toolkit, returns a connect link for credentials, and returns a checkout link for empty wallets. It also notes that writes require workspace owner/admin and that search/describe flag installed_in_toolkit vs installed_in_workspace.

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 dense; every sentence carries distinct information such as catalog, core flow, invoke-vs-install, auth requirements, and prompt library. It is a single block paragraph, which slightly hurts scannability, but the content justifies its 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 high-complexity tool with no output schema, it covers search/describe/invoke, install vs invoke, list_tools, billing operations, request_mcp, report_bug, and prompt library search/get/publish, plus auth requirements. Minor specifics like the resume action are omitted, but overall it is remarkably 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?

The description adds meaning to the central 'action' enum and core fields (tool_id, arguments, prompt_vars) through the flow explanation. However, with 0% schema coverage and 23 parameters, several payload fields (limit, immediate, tier_slug, cancel_reason, prompt_targets, etc.) remain underspecified and rely on inference.

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 marketplace as the catalog and execution layer for MCPs, with a concrete search→describe→invoke flow. It distinguishes itself from siblings by covering catalog discovery, one-off invocation, and prompt library functionality.

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?

Provides explicit guidance: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'. It also explains when list_tools, subscribe/cancel, report_bug, request_mcp, and prompt-library actions apply, including the search→describe→invoke decision flow.

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 provide idempotentHint=true, readOnlyHint=false, and destructiveHint=false. The description adds the instruction to include the conversation array for reproduction, giving extra context. However, it doesn't clarify side effects, authentication requirements, or what happens after reporting. 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 two sentences long, front-loads the core purpose, and includes only essential information. Every word contributes to understanding the tool's function 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 bug-reporting tool with no output schema and simple parameters, the description provides the key operational detail (include conversation for reproduction). It could mention expectations post-submission or any side effects, but given the tool's simplicity and the annotations covering safety, it is reasonably 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 mentions 'conversation array with recent messages for reproduction,' which partially explains the 'conversation' parameter. However, the required 'message' field is not described, and 'context' is ignored. The description falls short of adequately explaining parameter meaning given the complete lack of 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 starts with 'Report a bug, missing feature, or send feedback,' clearly stating the tool's purpose with a specific verb and resource. It effectively conveys what the tool does, and while it doesn't explicitly distinguish from siblings, the siblings are unrelated, so the purpose is 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 provides no guidance on when to use this tool vs. alternatives or under what circumstances to avoid it. It implies usage through 'Report a bug,' but there are no explicit exclusions or references to sibling tools, leaving the agent without decision support.

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, covering the safety profile. The description adds the semantic detail of what the version query returns (platform and adapter versions) but does not go further, such as response structure or potential network calls. 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, efficient sentence that contains no filler words or redundant information. It is front-loaded with the action 'Show' and quickly specifies the object, making it easy to scan.

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 has no parameters, rich safety annotations, and no output schema, a short description suffices. The description fully captures the tool's function—displaying current MCP and adapter versions—without requiring additional context about return values or side effects.

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 description is not required to explain parameter details. The baseline for zero parameters is 4, and the description meets this by being clear about the tool's purpose, leaving no ambiguity about 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 the specific verb 'Show' with a precise resource: 'current MCP platform and adapter versions.' It clearly distinguishes this version-inquiry tool from the sibling tools, which are action-oriented (authenticate, connect, marketplace, report_bug).

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?

No explicit guidance is provided about when to use this tool versus alternatives, but the read-only, informational nature of version display makes the use case intuitively clear. It gives no exclusions or alternative recommendations, so it remains at the implied level.

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 establish the tool as read-only, idempotent, and non-destructive. The description adds value by disclosing the contents of the returned state—installed MCPs, connection status, connected accounts, and tool counts—which goes beyond the annotation fields. It does not discuss potential edge cases, but annotations already cover the safety profile.

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 conveys all essential information without any wasted words. It uses a clean list structure to enumerate the return contents, making it easily scannable and memorable.

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, parameterless read-only information tool with no output schema, the description is complete: it fully explains what the tool returns and implies its role as an inspection/status utility. The annotations cover behavioral safety, and the description covers the observable result.

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 input schema is empty with 100% schema description coverage. The baseline for zero-parameter tools is 4 because no parameter semantics are needed; the description appropriately does not attempt to invent parameter details.

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 a clear resource ('current toolkit state'), then enumerates exactly what that state includes: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from sibling tools like show_version by focusing on broader state rather than version info.

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: this is the tool to inspect the overall toolkit status. It does not explicitly state when not to use it or compare with alternatives like show_version, but the specificity of the returned data makes the usage intention clear and leaves no exclusions.

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