DETRAN RJ IPVA: DARJ

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

Annotations already indicate idempotent, non-read-only, and non-destructive behavior. The description adds useful context about permanent versus session-only authentication, the browser login flow, and the Authorization header approach. 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 compact and mostly front-loaded, conveying the core flow in two sentences. It is slightly run-on and starts with an audience qualifier rather than the action, but every sentence contributes essential usage details.

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?

No output schema exists, so the description carries the burden of explaining expected results. It does say 'with no args to get the link,' but it does not describe the response after submitting a token or error/edge-case behavior. Overall, it is sufficiently complete for a simple authentication 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?

With 0% schema description coverage, the description compensates by explaining the optional 'token' parameter as a JWT to paste and clarifying the no-args behavior returns a login link. This adds meaning beyond the schema's bare string property, though it could be more explicit about validation or failure cases.

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: authenticating an IDE agent to MCP.AI by logging in and providing an access token. It distinguishes itself from siblings like 'connect' and 'marketplace' by focusing specifically on the authentication flow 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?

The description gives explicit usage guidance: prefer adding the token as a persistent header, or use a session-only login by pasting a token or calling with no args to get the login link. It does not explicitly name alternative tools or state when not to use this tool, but the two-mode workflow is well explained.

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 behavioral detail beyond the annotations (readOnly, idempotent) by explaining the two possible return states: 'authenticated:true with empty pending[]' and 'connect_url for toolkit and per-install URLs' when credentials are missing. It does not contradict 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), clearly structured, and free of redundant information. It efficiently conveys the tool's purpose and behavior without extraneous details.

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 simple nature (no parameters, no output schema), the description sufficiently explains the expected return values and scenarios. It covers both the success and failure states, making it complete for typical usage, though it might not detail the exact JSON structure or error codes.

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 coverage is 100%. The description adds no parameter-specific meaning, but none is needed. Per the rubric, a baseline of 3 is appropriate when coverage is high and no additional explanation is required.

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 function: 'Returns connection status and URLs.' This is a specific verb+resource (returns connection status) and distinguishes it from siblings like 'authenticate' and 'show_version' by focusing on connectivity state.

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 when to use this tool (to check connection status and obtain URLs) without explicitly mentioning alternatives. It implies usage for diagnosing connectivity, but does not explicitly exclude other tools, so it lacks a direct 'use this instead' statement.

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 discloses behavioral traits beyond annotations: 'invoke works even when the MCP is NOT installed', returns connect/checkout links for credentials/payment, and notes that writes require workspace owner/admin. This adds significant transparency not present in the structured annotations (readOnlyHint=false, openWorldHint=true). No contradiction found.

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 one long paragraph but well-structured: starts with purpose, then core flow, then key behavioral notes, then additional features. It is dense and informative, though perhaps verbose; every sentence adds value, so it earns a 4 despite 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?

Given the tool's complexity (23 params, no output schema, multiple actions), the description is exceptionally complete. It covers the main flow, edge cases like authentication and payment, permission requirements, and the prompt library, providing ample context for an agent to use the tool correctly without needing additional info.

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 schema coverage at 0%, the description must compensate. It explains key parameters like action (with enumerated values spelled out in the flow), mcp_id, tool_id, arguments, and prompt-related fields. However, not all 23 parameters are described (e.g., limit, immediate, conversation, request_name), though the most important ones are covered. This is strong but incomplete.

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: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It lists specific actions (search, describe, invoke, install, etc.) and differentiates from siblings by its broad marketplace scope.

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 explains when to use each action: 'Core flow: action=search → describe → invoke', and provides a key distinction: 'prefer invoke for a single/occasional use' vs 'install only to make an MCP PERMANENT'. It also covers when to use subscribe/cancel, report_bug, and request_mcp, giving clear contextual 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 provide idempotentHint=true, destructiveHint=false, and readOnlyHint=false, covering the safety profile. The description adds value by noting the conversation array is used 'for reproduction.' However, it doesn't disclose that the submitted content (including conversation messages) is transmitted externally to developers/support, which would be valuable context for a send-type feedback tool. 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?

Two tightly-written sentences, front-loaded with the purpose. The first sentence states what the tool does, and the second delivers an actionable operational instruction (include the conversation array). Every word earns its place with zero waste.

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-param tool with no nested objects, no output schema, and good annotation coverage, the description covers the essential purpose and a key usage detail. Minor gaps remain: the 'context' parameter is unexplained, and with no output schema the post-submission behavior (e.g., return value) is unstated, but overall it's adequate for the tool's simplicity.

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 carries the burden and partially compensates by explaining that the conversation array holds recent messages for reproduction. However, the required 'message' parameter and the 'context' field receive no semantic explanation beyond what their property names imply, leaving the agent to infer their roles.

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+resource construction ('Report a bug, missing feature, or send feedback'), clearly stating what the tool does. It is immediately distinguishable from the unrelated sibling tools (authenticate, connect, marketplace, sefaz_rj_ipva_darj_consultar, show_version, toolkit_info), none of which involve reporting or feedback.

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 names the concrete use cases ('bug, missing feature, or send feedback'), giving clear context for when an agent should invoke this tool. It doesn't explicitly state when not to use it or name alternatives, but since all sibling tools serve entirely different domains, there is no competing tool to disambiguate against.

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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context: prepaid credit payment, no platform credentials, official data source, and LGPD compliance. This goes beyond the annotations, though it doesn't describe edge cases or response behavior, preventing a 5.

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 few sentences long and front-loaded with the main purpose. However, it includes some redundancy (repeating 'fonte oficial' and 'fontes e órgãos oficiais') and legal boilerplate that could be trimmed. It is not overly verbose but contains non-functional filler.

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?

Without an output schema and with only 2 parameters, the description should explain what the tool returns and how the parameters are used. It provides payment and legal context but omits functional details like the meaning of 'ano' or response format. The tool is only partially described for an agent to invoke it confidently.

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 mention the 'renavam' or 'ano' parameters at all. It provides no information about their formats, requiredness, or semantics. The description completely fails to compensate for the lack of 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 identifies this as a 'consulta' (query) for DARJ from DETRAN RJ, using a specific verb and resource. It distinguishes itself from the generic sibling tools by stating the exact domain (IPVA) and source (fonte oficial). While 'DARJ' is a technical acronym, the overall purpose is clear.

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 given on when to use this tool versus alternatives. The text mentions payment and LGPD but does not state scenarios, prerequisites, or exclusions. It is implied this is the tool for DARJ queries, but there is no 'use this when' or 'use that instead' 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 and idempotentHint=true, which fully covers the safety profile (no side effects). The description adds the specific information returned (platform and adapter versions) but does not dive into output format or how to interpret versions. Since annotations are rich, this is adequate.

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 function with no extraneous information. It is perfectly front-loaded and 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, parameterless, read-only version-check tool with complete schema coverage and good annotations, the description is sufficient. The output is not described, but since there is no output schema, the agent will rely on the description to infer the return type, which is adequately hinted by 'versions'. This is not a complex tool, so completeness is high.

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 is no hidden parameter semantics to describe. Baseline 4 is appropriate as the description focuses on the operation itself, which is sufficient for a parameterless version-check 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 states the specific purpose: showing current MCP platform and adapter versions. It is clear, uses a specific verb ('Show') and resource, and is distinct from sibling tools like 'authenticate' and 'toolkit_info' (which likely shows toolkit metadata).

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 clearly implies the tool is for checking version information, which is a common diagnostic task. It does not explicitly state when not to use it, but given the simple nature of the tool and that siblings like 'toolkit_info' indicate a potential alternative, 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.

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 meaningful behavioral context by specifying exactly what the state inspection covers, which goes beyond the annotation-provided safety traits and helps the agent set expectations about the returned information.

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 is concise, well-structured, and front-loaded with the primary action. Every listed detail directly contributes to explaining what is returned, with no unnecessary 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?

This is a simple zero-parameter informational tool with strong annotations. The description fully covers the return contents, and no output schema exists to explain. The tool's scope is small enough that this single sentence provides complete context for an agent to select and 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?

The tool has zero parameters, so there is no parameter semantics to document. The baseline of 4 applies, and the description justifiably omits parameter details since the input schema is empty.

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 identifies the resource ('current toolkit state') while enumerating the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from action-oriented siblings like authenticate and 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 the tool is used for inspecting environment status, but it does not explicitly state when to use this tool versus alternatives such as show_version. No exclusion criteria or alternative references are provided, so usage guidance remains implicit rather than explicit.

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