DETRAN RJ: Nada Consta

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

Beyond annotations, the description reveals that a config-level token is permanent and non-expiring, a passed-in token is session-only, and a no-arg call returns the login link. This meaningfully informs the agent of the behavior's consequences.

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 information-dense and front-loaded with the purpose, with all sentences contributing to use or setup. There is minor redundancy and a somewhat run-on structure, but nothing superfluous.

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 single-optional-parameter tool with no output schema, the description adequately covers the key usage paths: getting the auth link, submitting a JWT, and setting up a permanent header. It does not describe the response after passing a token, but that is not critical at this complexity.

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 schema has 0% description coverage, but the description compensates by explaining that token is an optional JWT, what happens when it is passed, and what happens when it is omitted. More detail on token origin or validation would help, but the essential meaning is clear.

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 centers on authentication and covers both obtaining a login link and submitting a token. However, it mixes user/setup instructions with tool-call semantics, so the core verb+resource statement is not as crisp as it could be.

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 is explicit about two invocation modes: call with {token} for session-only login and call with no args to get the link. It also mentions a permanent configuration alternative, though it does not explicitly exclude or compare sibling tools like connect.

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 transparently details both possible outcomes (authenticated:true with empty pending, or connect_url for missing credentials) and aligns with the readOnly and idempotent annotations, adding context 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 concise (two sentences) and well-structured, providing all necessary information without redundancy or extra fluff.

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 lacking an output schema, the description fully explains the two possible return states (authenticated:true with empty pending, or connect_url), making the tool's behavior complete and understandable.

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 does not need to explain parameters. Per rubric, 0 params yields a baseline of 4, and the description provides sufficient context for what the tool does without 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 clearly states that the tool returns connection status and URLs, which is specific and distinct from sibling tools like authenticate or 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 implies usage for checking connection status, but does not explicitly mention when to use it vs. alternatives like authenticate. It is clear enough to infer, but lacks an explicit alternative instruction.

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 valuable context beyond that: no platform credentials required, pay-per-query with prepaid credit, data is not confidential, and LGPD compliance responsibilities. This enriches the agent's understanding of side effects and requirements.

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 contains multiple sentences covering purpose, payment, credentials, data nature, and legal responsibility. Each sentence provides information, but the inclusion of legal/commercial details makes it somewhat verbose for a simple query tool. It is structured reasonably, starting with the core purpose.

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 (one parameter, no output schema), the description covers payment, authentication, and data sensitivity. However, it does not mention what the response contains or any expected return format, which could leave an agent uncertain about interpreting results. This is a moderate gap.

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 parameter 'placa' with no description (0% schema coverage). The tool description does not explain the parameter's format, meaning, or examples. While the parameter name is self-explanatory, the description fails to compensate for the absent schema 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 performs a DETRAN RJ 'Nada Consta' query from an official source, using the specific verb 'consulta' and naming the resource. It is easily distinguished from sibling tools which are platform management tools (authenticate, connect, etc.).

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 gives no explicit guidance on when to use this tool versus alternatives, nor any exclusions. Usage context is only implicit via the service name and description. Sibling tools are unrelated, but still no direct usage direction 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?

The description goes well beyond the sparse annotations (readOnlyHint=false, openWorldHint=true) by disclosing many behaviors: invoke works even when the MCP is not installed, returns a connect link if credentials are needed, returns a checkout link if the wallet is empty, writes require workspace owner/admin, and search/describe flag installation status. 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 quite long but densely packed with necessary workflow information. It is front-loaded with the core purpose, then structured around core flow, key invoke behavior, install vs invoke distinction, and the prompt library. While it could be tightened, every sentence adds meaningful context for this complex multi-action 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?

Given the tool's complexity (23 parameters, no output schema, no parameter descriptions), the description provides a remarkably complete picture: the full search→describe→invoke flow, auth and payment edge cases, workspace permissions, the prompt library subsystem, and the distinction between permanent and one-off execution. It covers all major behavioral and contextual aspects an agent would need.

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 carries a heavy burden. It explains the meaning of key parameters like action (with all enum values), mcp_id, tool_id, arguments, prompt_slug, prompt_vars, and request_mcp parameters. However, not all parameters are explicitly defined (e.g., immediate, tier_slug, conversation, prompt_targets, cancel_reason), though context often implies their purpose.

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: 'the in-platform catalog of every MCP/tool, AND the way to run them.' It lists distinct actions (search, describe, invoke, install, etc.) and distinguishes itself from sibling tools by explaining it is the hub for discovering and running MCPs, while siblings like detran_rj_nada_consta_consultar are specific tools.

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 provides an explicit core flow ('action=search discovers MCPs by intent → describe returns one MCP's full profile ... invoke RUNS that tool'), and gives clear when-to-use guidance: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', and lists alternatives like list_tools for currently callable tools and search_prompts for prompt text.

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 include idempotentHint=true, readOnlyHint=false, destructiveHint=false, which provide baseline safety info. The description adds no behavioral details beyond the purpose and a note on conversation reproduction. It doesn't contradict annotations but also doesn't enrich them with side effects, error handling, or persistence behavior.

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 front-load the purpose and provide a key usage tip. No wasted words, but the parameter explanation is minimal, and the lack of mention for context could be seen as a structural gap.

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 3 parameters and no output schema, the description is incomplete. It clarifies the main purpose and one parameter (conversation) but fails to elaborate on 'message' or 'context', leaving the agent to infer their roles. The absence of examples or edge-case notes further reduces completeness.

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 explain parameters. It mentions 'conversation array' explicitly but leaves 'message' and 'context' undefined. The purpose statement implies 'message' holds the report, but 'context' remains opaque, and there's no guidance on required formats or defaults.

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 clearly states the tool's purpose: 'Report a bug, missing feature, or send feedback.' This is a specific verb (report) plus resource (bug, feature, feedback) and distinguishes it from sibling tools like authenticate or marketplace, which serve 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?

Provides context on when to use the tool (reporting bugs, features, feedback) but lacks explicit alternatives or exclusions. The instruction to include the conversation array for reproduction is a usage hint, yet there's no mention of when NOT to use it or comparison 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?

The annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds that it reports both MCP platform and adapter versions, providing additional context about the output scope, but it does not disclose any further behavioral traits such as output format or side effects. With annotations covering safety, the description adds modest value.

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 8 words that immediately states the tool's action and target. There is no redundancy or filler; every word contributes to the meaning.

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 no parameters, no output schema, and safety annotations already present, the description fully captures what the tool does. It states the exact information conveyed (MCP platform and adapter versions) and needs no further explanation for an agent to understand its 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 input schema has zero parameters, so there is nothing for the description to clarify about parameter meaning. According to the rubric, a baseline score of 4 is appropriate for zero parameters, and the description does not introduce any parameter-related information because none exists.

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 'Show the current MCP platform and adapter versions' uses a specific verb ('Show') and identifies a clear resource (MCP platform and adapter versions). This makes its purpose unambiguous and distinguishes it from siblings like authenticate, connect, and marketplace, none of which claim to provide version information.

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 version information is needed) but does not explicitly state usage conditions or alternatives. Given the tool's simplicity and lack of similarly functioning siblings, this implicit guidance is satisfactory though 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 readOnlyHint, idempotentHint, and destructiveHint, establishing a safe read-only profile. The description adds useful context by specifying exactly what state is returned, which goes beyond the annotations. It does not contradict any 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, well-structured sentence that front-loads the primary purpose and lists key content areas without unnecessary detail.

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 serves as the only documentation of return values. It covers the main output expectations by listing installed MCPs, connection status, accounts, and catalog tool counts, though it could mention formatting or edge cases.

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 there are no parameter semantics to clarify. The description appropriately focuses on the return value rather than parameters, matching the baseline for 0-param tools.

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 clearly defines the resource as 'current toolkit state', enumerating specific components (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from sibling tools like show_version or connect, which serve 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 description provides clear context for when to use this tool by indicating it gives an overview of the toolkit's state. However, it does not explicitly mention when not to use it or name alternatives, such as show_version for version-specific information.

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