DETRAN RS: Infrações

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

Annotations already indicate the tool is mutating and idempotent. The description adds behavioral context beyond that: it explains the two-step flow (get link → paste token) and the difference between permanent (config header) and session-only (token arg) authentication. It does not contradict the annotations and offers useful details about the login process.

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, two sentences, and front-loads the purpose. It efficiently covers the primary action and both usage modes without redundancy. Every sentence contributes to understanding, making it highly concise and 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?

The tool has a moderate complexity due to the two-step authentication flow, and the description explains both modes (permanent and session). It does not explicitly state what happens after a successful token submission (e.g., confirmation message), but it's implied by 'session-only login'. For a simple auth tool with no output schema, the description is mostly complete, though a note on return values would elevate it.

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 one optional parameter 'token' with no description (0% coverage). The description fully compensates by explaining its meaning: 'call with { token: "<jwt>" } after the user pastes' and clarifies that calling with no args yields the link. This adds crucial semantics 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 states the tool's purpose: to authenticate an IDE agent with MCP.AI. It specifies the action (log in, get token) and the resource (MCP.AI server for IDE agents). It distinguishes from siblings by focusing on authentication only, and the wording is specific and non-tautological.

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 instructions: call with no args to get a link, or call with a token for session-only login. It also mentions the best practice for a permanent connection via config. However, it does not explicitly mention when to avoid this tool or compare it to alternatives like 'connect', so it lacks explicit exclusions but gives sufficient 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 mark the operation as read-only, idempotent, and non-destructive. The description adds consistency by explaining the two observable output states, including the behavior with missing credentials and connection URLs, which goes slightly beyond what annotations alone provide.

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 immediately states the key behavioral cases. Every sentence contributes useful 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 zero-parameter, read-only status tool with no output schema, the description sufficiently covers the main expected results and the special case of missing credentials. No critical behavior is left unexplained.

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 schema coverage is effectively complete. The description confirms no input is required and focuses on what the output means, so there is no parameter semantic gap to compensate for.

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 states the tool 'returns connection status and URLs', which is a clear verb+resource pairing. It also differentiates itself from sibling tools like authenticate by describing what this status check returns rather than performing authentication or managing credentials.

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 conditional context for interpreting output: when all providers are connected versus when credentials are missing. It does not explicitly say when to use this tool instead of siblings like authenticate, so usage guidance is implied rather than 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 indicate readOnlyHint=truehol, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds valuable context that this is an official source, hosted by the platform, requires prepaid credit per query, and involves LGPD data controller responsibilities—important for legal and cost implications. It also clarifies that data is not confidential, which is useful.

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 of three sentences, which is reasonably concise. However, it front-loads the source and platform details but omits usage specifics, leading to some redundancy. It could be more structured, but it effectively communicates key selling points. No waste, but not perfectly formatted.

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 complexity (8 parameters with mixed auth methods) and lack of output schema, the description does not explain how to authenticate (login/password vs certificate), what 'guia_pagamento' is, or what the response contains. However, the description covers the essential context: official source, credit-based payment, LGPD compliance, and non-confidential data. It misses return format details but that's compensated by the clarity of the tool's 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?

Schema description coverage is 0%, but the description does not explain any parameter semantics. However, the schema includes a mix of identifiers (placa, renavam, cnpj) and authentication credentials (login_cpf, login_senha, pkcs12_cert, pkcs12_pass) and a 'guia_pagamento' parameter. Without explanation, the agent may not know which parameters are needed together (e.g., certificate vs login). A baseline of 3 is set because the schema provides property names, but the description does not add meaning beyond that.

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 it consults DETRAN RS infractions from an official source, but it lacks specificity about the exact operation (e.g., what kind of query: by plate, by fine ticket, etc.) and does not differentiate from siblings. The verb 'consultar' is clear but vague, and sibling tools are not similar, so there's no direct need to distinguish.

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?

There is no explicit guidance on when to use this tool versus alternatives. It mentions it is from an official source and requires prepaid credits, but does not state when one should prefer this over other methods. Siblings include unrelated tools like 'connect' and 'authenticate', so there is no explicit exclusion.

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 significant behavioral context missing from annotations, such as invoke running one-off without installing, returning connect/checkout links based on credential/payment status, and requiring workspace owner/admin for writes. It also discloses the prompt library's behavior with shareable links.

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 long, unstructured paragraph that packs in a large amount of detail without section breaks or bullet points. While each sentence adds information, the overall delivery is dense and could benefit from clearer organization.

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 14 actions and 23 parameters, the description covers the main user workflows, access control, and the prompt library admirably, including specific return behaviors like connect links and published prompt slugs. However, it stops short of describing return structures for search/describe and leaves several parameters unexplained.

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?

Because the schema has 0% description coverage, the description is the sole source of parameter meaning, and it does explain the action enum and the relationship between mcp_id, tool_id, and arguments in the invoke flow. However, it does not cover the remaining 23 parameters (limit, query, immediate, prompt_* fields), leaving many semantics to 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 explicitly states it is the 'official mcp.ai marketplace' and outlines a clear core flow: search → describe → invoke, along with additional actions like install, subscribe, and prompt operations. This distinguishes it from sibling tools and makes the tool's purpose 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?

The description provides explicit when/when-not guidance: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT in the active toolkit.' It also indicates when to use list_tools and request_mcp, giving clear alternatives for different situations.

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 false, destructiveHint false, and idempotentHint true, covering the safety profile. The description adds context about using the conversation array for reproduction but does not disclose what happens after submission or any auth requirements. 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 two concise sentences, front-loaded with purpose and followed by a necessary usage instruction. No redundant or filler content.

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 feedback tool with no output schema and minimal parameters, the description covers the core purpose and key usage guidance. It could elaborate on the 'context' parameter and post-submission behavior, but given annotation coverage, it is generally adequate.

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 partially compensates: it clarifies 'conversation' as recent messages for reproduction and implies 'message' is the report content, but leaves 'context' undefined. More parameter-level detail would help.

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 specific verbs 'Report' and 'send' with clear targets (bug, missing feature, feedback), making the tool's purpose immediately obvious. This distinctly sets it apart from unrelated sibling tools like 'detran_rs_infracoes_consultar' 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?

The description provides clear context on how to use the tool: report issues and include the conversation array for reproduction. However, it does not explicitly mention when not to use the tool or compare to alternative sibling tools, though the context implies this is the go-to for feedback.

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 the tool as read-only, idempotent, and non-destructive. The description merely restates the action of showing versions without adding any additional behavioral context (e.g., authentication requirements, output format, or side effects). No contradiction exists, but no value is added beyond 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 a single, concise sentence that directly states the tool's purpose. It contains no unnecessary words or fluff, making it highly efficient.

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 tool with no parameters and no output schema, the description adequately conveys what the tool does and what it returns (versions). It could specify the output format, but given the low complexity, this is a minor gap and the description is generally 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 tool has zero parameters, and the schema coverage is 100% (empty properties). This satisfies the baseline for 0-parameter tools, making the description sufficient without needing to elaborate on 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 a specific verb ('show') and clearly identifies the resource ('current MCP platform and adapter versions'). It is distinct from sibling tools like 'authenticate' or 'marketplace', 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 tool is a simple version query with no alternative flows or exclusions. While it doesn't explicitly state when to use it, the intent is clear and aligned with its name. It provides adequate context without explicit when-not-to-use guidance.

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 context about what 'state' means (installed MCPs, connection status, accounts, catalog tools) without contradicting the annotations. It is consistent with a safe, non-mutating operation.

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 packs in the essential purpose and content without any filler. It is immediately scannable and front-loaded with the key verb and object.

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 read-only info tool, the description adequately covers what the tool returns (installed MCPs, connection status, accounts, catalog tool counts). It does not specify formatting or edge cases, but that is not critical for basic usage. Slightly more detail on how accounts/statuses are represented could push it higher.

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 is empty (100% coverage). With no parameters to describe, the description correctly focuses on the returned information. Baseline 4 is appropriate for a no-parameter 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?

The description uses a clear action verb ('Returns') and specifies the resource ('current toolkit state') with concrete elements (installed MCPs, connection status, accounts, catalog tool counts). It clearly distinguishes this from siblings like 'authenticate' and 'show_version' by focusing on a state overview.

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 (whenever the current state of the toolkit is needed) and clarifies what will be included. It does not explicitly mention when not to use it or name alternatives, but the context is clear enough for typical selection.

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