SENATRAN: Meus Veículos - Possuidor (Detalhes)

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

Adds valuable context beyond annotations: differentiates permanent vs. session-only login, explains the effect of providing a token vs. no args (returns a link). Annotations already signal non-read-only, idempotent, and non-destructive, so the description complements rather than repeats. Minor gap: doesn't explicitly state the output format or any side effects on server state, but the mode distinction 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?

Three sentences that are informative but slightly verbose. Each clause serves a purpose—introducing the tool, recommending permanent setup, and describing session login—so no waste, though a more streamlined structure could improve readability.

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 covers all necessary usage scenarios: how to get a link, how to pass a token, and the trade-offs between permanent and session-based auth. It fully equips an agent to decide when and how to invoke 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?

Despite 0% schema coverage, the description fully explains the 'token' parameter (expects a JWT) and the no-arg alternative (returns a login link). This adds meaning far beyond the schema's bare property definition, making the intended use 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?

Clearly states the tool authenticates the user for MCP.AI in IDE agents, with a specific verb (authenticate/login) and resource (MCP.AI). It distinguishes itself from siblings like 'connect' and 'marketplace' by focusing on credential acquisition and token handling.

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 when-to-use guidance: recommends adding the token to config for a permanent connection, or pasting it for session-only login. It also explains exactly how to call the tool (with token or no args) and the purpose of each mode, offering clear alternatives.

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 readOnly and idempotent annotations, the description adds details about the exact outputs (authenticated:true, empty pending[], connect_url) for different credential states, providing transparent behavior. 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 concise, only two sentences, and clearly structured to state the main purpose then conditional outcomes. No unnecessary words.

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 lack of an output schema, the description adequately explains return values for two common scenarios, but does not mention other possible states (e.g., partial connection). It is mostly complete for a status check 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 in the input schema, so no additional semantics are needed. The description does not need to explain any 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, and specifies two distinct scenarios. It distinguishes from sibling tools like authenticate and report_bug by focusing on status rather than 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 explains what the tool does and the two possible outcomes, but does not explicitly state when to use this tool over siblings (e.g., before authenticate to check if credentials are missing). It implies usage but lacks direct 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?

The description richly discloses behaviors beyond annotations: invoke works without installation, returns connect/checkout links on missing credentials/payment, writes require owner/admin, and flags installed status. This is significant context not present in 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 long paragraph but every sentence adds value, covering flow, auth, billing, and prompts. It is front-loaded with the core purpose, though it could benefit from bullet points to improve scannability 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 tool with 23 parameters, 14 actions, and no output schema, the description covers the major operational contexts: catalog search, describe, invoke, install, list_tools, subscriptions, bug reports, requests, and prompt library. It addresses auth, permissions, and billing, making it highly 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?

With 0% schema description coverage, the description compensates by explaining the action enum and the purpose of key parameters (mcp_id, tool_id, arguments) through the flow. However, it does not detail every parameter (e.g., limit, query, immediate, prompt_* fields), so it is not fully exhaustive.

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 marketplace as the official catalog of MCPs/tools and the way to run them, with a specific core flow (search → describe → invoke). It distinguishes itself from siblings like toolkit_info by describing its broader scope and the invoke action.

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 advises when to use invoke (single/occasional use) vs install (permanent addition), mentions list_tools for immediate callable tools, and indicates request_mcp for building new MCPs. It also discusses prerequisites like auth and wallet top-up, giving clear alternatives and conditions.

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 a behavioral note about including the conversation array for reproduction, which is useful. However, it does not disclose what happens after the report is submitted (e.g., whether a confirmation or ticket is returned, whether it is asynchronous). Annotations already provide idempotency and non-destructiveness, but the description does not expand on side effects or system impact beyond that.

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 tool's purpose, and ends with a specific guideline. No filler or redundancy, every word earns its place.

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 3-parameter tool with no output schema, the description adequately covers the purpose and the key parameter guidance (conversation for reproduction). It does not explain return values, but for a bug report tool, the action itself is the primary outcome, so this is not a major gap. Siblings are unrelated, so it stands alone well.

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 conversation parameter by explaining it should contain recent messages for reproduction. However, since schema coverage is 0%, the message and context parameters remain unexplained beyond their schema definitions. The description partially compensates but not fully for the lack of parameter documentation.

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.' This is a specific verb ('Report') with a clear resource (bugs/feedback), and it naturally distinguishes itself from sibling tools like authenticate, connect, and marketplace, which serve unrelated 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 explicitly lists the three use cases (bug, missing feature, feedback), giving clear context for when to invoke the tool. It does not explicitly state alternatives or when-not-to-use scenarios, but the sibling tools are clearly unrelated, so there is little ambiguity. A slight gap remains: no guidance on edge cases like general questions.

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 annotations, the description discloses several behavioral and policy traits: 'sem credenciais da plataforma', 'pague por consulta com crédito pré-pago', 'não é dado sigiloso', and LGPD responsibility. These add useful context about authentication, cost, and data handling that the annotations do not cover. No contradictions exist.

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 mixing purpose, payment, source, and legal compliance. It is not excessively long, but it lacks clear separation between core functionality and compliance boilerplate. The main purpose is front-loaded, which is good, but the overall structure could be more scannable.

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 no output schema, so the description must indicate what to expect. It vaguely says 'a mesma disponível ao cidadão' but does not describe the actual response shape, error cases, or prerequisites beyond parameters. The description covers source and legal aspects but leaves operational details (e.g., what exactly is returned, how credentials are used) unspecified.

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 0% description coverage, yet the description never explains any of the parameters (login_cpf, login_senha, placa, renavam). It does not clarify the meaning of the login fields, whether they are the vehicle owner's credentials, or the relationship between placa and renavam. The description fails to compensate for the absence of schema-level parameter documentation.

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 names the resource and operation: 'SENATRAN: Meus Veículos - Possuidor (Detalhes), consulta em fonte oficial.' It identifies a specific verb ('consulta') and a well-scoped resource (Brazilian vehicle holder details). Since sibling tools are generic platform utilities, there is no ambiguity about 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 operational context such as the official source, prepaid payment model, and lack of platform credentials, but it does not give explicit when-to-use or when-not-to-use guidance relative to alternatives. Usage is implied ('consulta informação de fontes e órgãos oficiais brasileiros') but not contrasted with other tools.

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 readOnly, idempotent, and non-destructive behavior; the description adds no further behavioral context, but given the simple read operation, this is sufficient.

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?

One concise sentence directly conveying the purpose 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?

The description sufficiently conveys what the tool outputs (versions) and given no output schema, it's complete for the context.

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?

No parameters exist, so the description doesn't need to explain them; schema coverage is 100% (vacuously), so baseline score of 3 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?

Clearly states the tool's function: showing platform and adapter versions. The verb 'show' and specific resource make it distinct from siblings like toolkit_info, which may cover broader 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 does not explicitly state when to use this over other tools, but the purpose is self-explanatory. Missing exclusions or alternative guidance, so it's adequate 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 readOnly, idempotent, and non-destructive behavior. The description adds no additional behavioral details but does not contradict the annotations. Since the operation is read-only, the lack of side-effect disclosure is acceptable; the description is transparent about the output.

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 clearly lists all elements of the returned state. It is well-structured and front-loaded with the main purpose, making it easy to 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 that there is no output schema and no parameters, the description fully explains what the tool returns and covers all necessary context. It is complete for an agent to use the tool effectively.

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 schema coverage is 100% (vacuous). The description does not add any parameter-related meaning beyond the schema, which is trivial. Per the rubric, baseline 3 applies when schema does the heavy lifting.

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 the tool returns the current toolkit state and enumerates the specific details included (installed MCPs, connection status, accounts, catalog tool counts). This is specific and distinguishes it from sibling tools like 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 does not explicitly state when to use this tool versus alternatives. While the purpose is clear, there is no guidance on when it is appropriate to call this function (e.g., when needing an overview). This is a minor gap.

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