DETRAN MS Guia Flex: Multas

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

The description discloses key behavioral traits beyond annotations: it describes the interaction flow (opens browser, expects user to copy token), the two modes (permanent via config header vs session-only via token param), and the optional nature of the token parameter. The annotations indicate idempotentHint=true and readOnlyHint=false, and the description's emphasis on token-based login aligns with these cues.

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, dense paragraph that is front-loaded with the most critical information (authentication flow) and then details the two options. Every sentence adds value: the opening identifies the target, the middle explains the permanent option, and the end covers the session-only variant. No filler 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?

The tool is simple (one optional param, no output schema), and the description fully covers its behavior: what happens with no args, what happens with a token, and the recommended permanent setup. It also addresses prerequisites (browser login, copying token). The context signals show no complexity that requires additional disclosure.

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 coverage is 0% for the single parameter 'token', so the description must compensate. It does so by explaining the token's purpose (JWT for session-only login) and how to obtain it ('paste it here for a session-only login'). It also clarifies that calling with no args returns a link, which is additional semantics beyond the bare schema. Slight deduction because the description doesn't specify the token's format precisely beyond 'jwt', but it's sufficient.

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: authenticate with MCP.AI for IDE agents. It specifies the verb 'authenticate', the resource (MCP.AI), and the target audience (IDE agents like Cursor). It distinguishes from siblings like 'connect' by detailing the authentication flow (browser login, token copy, config or session-only login).

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 guidance: it explains when to use this tool (for login), how to use it (login in browser, copy token, add to config or pass as token), and provides alternative options (permanent via config vs session-only via paste). It also implies when not to use it (when already authenticated permanently via config).

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, destructiveHint, and idempotentHint. The description adds context about output states (authenticated:true with empty pending vs connect_url), which enriches behavioral understanding 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?

Two concise sentences cover the tool's purpose and behavioral variants without redundancy. Every clause adds meaningful information about return values and states.

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 having no output schema, the description fully explains the return values and their conditions. It covers the main scenarios (all providers connected vs missing credentials), making the tool's behavior complete for an agent.

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 description correctly avoids any parameter explanation. Baseline for no params is 4, and since the description does not need to compensate for missing schema documentation, this score applies.

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?

Description states it returns connection status and URLs, with specific details about the authenticated state and pending list. This clearly differentiates it from sibling 'authenticate' which likely performs the connection, making 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 usage for checking connection status by describing its return behavior, but does not explicitly state when to use it versus alternatives like 'authenticate'. No when-not or alternative guidance is provided.

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 and destructiveHint=false. The description adds meaningful context about authentication (no platform credentials), payment (prepaid credit per query), data classification (not confidential), and LGPD compliance. This goes beyond annotations and helps the agent understand the operational and legal 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 front-loaded with the core purpose ('Multas, consulta em fonte oficial') and is relatively concise. Each sentence adds some context, though the LGPD/data-controller sentence is more legal boilerplate than operational guidance.

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?

With no output schema and no parameter descriptions, the description should provide more functional detail about what the query returns and how the optional auto_infracao parameter works. The payment and legal context is useful, but the core invocation/response behavior is under-specified for an agent.

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 does not explain any parameters (placa, renavam, auto_infracao) or their expected formats. Since the schema only provides names and types, the description leaves full burden unmet; the agent cannot know what values are valid or how they affect the query.

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 DETRAN MS fines from an official source, and the name includes 'consultar' (query). It distinguishes itself from sibling tools (authenticate, marketplace, etc.) as a data consultation service, though it doesn't explicitly state it returns fine details for plate/renavam.

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 context: it queries official Brazilian sources, requires no platform credentials, and is paid per query. However, it does not explicitly state when to use this tool versus alternatives or mention any exclusions/prerequisites beyond the payment model.

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 goes well beyond annotations, disclosing key behaviors: 'invoke works even when the MCP is NOT installed', 'If the MCP needs a credential/login, invoke returns a connect link; if it is paid and the wallet is empty, invoke returns a checkout/top-up link', 'Writes (install/uninstall/subscribe/cancel ...) require workspace owner/admin', and the prompt shareable link 'opens without login'. These are critical runtime behaviors not captured by 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 appropriately structured for the tool's complexity: it starts with an overview, then explains the core flow, highlights key behaviors with 'KEY:', and separates MCP-related and prompt-library functionality. It earns its length, though some sentences could be tightened without losing value.

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 23 parameters, no output schema, and minimal annotations, the description is remarkably complete. It covers the search/describe/invoke/install lifecycle, authentication and payment fallbacks, permission requirements, prompt library operations, and billing actions. It provides enough context for an agent to decide how to use the tool correctly in most scenarios.

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 effectively compensates by explaining the meaning of the 'action' parameter values and their typical parameter usage (e.g., 'tool_id', 'arguments' implied in invoke, 'mcp_id' in describe). However, not all 23 parameters are explicitly defined (e.g., 'limit', 'immediate', 'tier_slug', 'prompt_vars'), though the core flow is well covered.

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 core function: 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It explicitly covers the main actions (search, describe, invoke, install) and even includes the prompt library, making it unambiguous what this 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 guidance: 'Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile ... → invoke RUNS that tool.' It also gives clear when-to-use advice: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'. Alternative actions within the tool (subscribe/cancel, report_bug, request_mcp) are described, and the prompt library usage is separated with its own 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 and destructiveHint=false, which already signal a safe, repeatable operation. The description adds behavioral context by instructing to include the conversation array for reproduction, which is useful for understanding expected input and purpose. 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 two short sentences, front-loaded with the core purpose and immediately followed by the key usage detail. Every word earns its place; 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?

The tool is simple with 3 params and no output schema, and annotations cover safety hints. The description gives essential purpose and one important parameter hint, but it could add more context about what happens after reporting (e.g., no response body, or that the message is sent to maintainers). Still, for a bug-report tool, this is passable.

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 the conversation array's role in reproduction but does not explain 'message' or 'context' beyond what the property names imply. The description adds some meaning but not enough to fully offset the 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 clearly states the tool reports a bug, missing feature, or feedback, and mentions including the conversation array for reproduction. This is a specific verb+resource pairing, though it doesn't strongly distinguish from siblings because sibling tools are unrelated (e.g., marketplace, authenticate), so differentiation isn't critical here.

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 (when reporting issues/feedback) and gives a key usage detail (include conversation array). It does not explicitly state when not to use it or mention alternatives, but the context is reasonably clear given the sibling set.

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, covering the safety profile. The description adds that it shows MCP platform and adapter versions but does not describe return format or any additional behavioral characteristics beyond what annotations convey.

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 of nine words, front-loaded with the verb and resource. There is no unnecessary information or repetition.

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 zero-parameter, read-only version tool with no output schema, the description fully covers the purpose and scope. Annotations provide safety guarantees, so no additional context is needed for an agent to invoke it 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?

There are zero parameters, and the schema already covers this completely. The baseline for 0 params is 4, and the description does not need to add anything about parameters since none exist.

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 a specific verb ('Show') and resource ('current MCP platform and adapter versions'), making it obvious what the tool does. It clearly distinguishes itself from sibling tools like authenticate or marketplace, which serve very 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 usage when version information is needed, but it does not explicitly state when to use this tool versus alternatives or provide exclusions. For a trivial zero-parameter tool, this is acceptable but lacks explicit 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 readOnly=true, idempotent=true, destructive=false, so the safety profile is covered. The description adds context about what the state includes (installed MCPs, connections, accounts, tool counts), which clarifies the tool's scope. 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 a single sentence that front-loads the primary action ('Returns the current toolkit state') and efficiently lists the key elements after a colon. There is no wasted wording.

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?

With no output schema, the description carries the burden of explaining return values, and it does so clearly by enumerating what the state includes. For a zero-parameter, read-only tool, this is sufficient and 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, so schema_description_coverage is 100% trivially. Per rubric, 0 params = baseline 4; the description need not explain parameters, and it doesn't, so a 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 clearly states the tool 'Returns the current toolkit state' and enumerates specific contents: installed MCPs, connection status, accounts, and catalog tool counts. This specific verb and resource scope distinguishes it from siblings like authenticate/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?

The description implies when to use this tool—whenever you need an overview of toolkit state—and the sibling names suggest other tools serve different actions. It does not explicitly name alternatives or exclusions, but the context is clear enough.

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