DNIT: Identificação de Condutor Infrator

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

Explains behavior beyond annotations: session vs permanent token, browser interaction, and the option to receive a link. No contradiction with the idempotentHint=true annotation; adds context about what happens with different argument combinations, though it doesn't detail response behavior or side effects.

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 dense paragraph that front-loads the tool's purpose before explaining options. It's a bit long but every sentence adds value, though bullets or line breaks could improve scannability for an agent.

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 self-contained authentication tool with no output schema, the description covers the core use cases and edge cases (no args, token arg, config). It could mention what a successful or failed login returns, but the current level is adequate for an agent to use 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?

With 0% schema coverage, the description heavily compensates by explaining that 'token' is a JWT pasted by the user and how omitting it yields a login link. This directly addresses the parameter's purpose and input format, going well beyond the bare schema definition.

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 authenticates to MCP.AI for IDE agents and provides a specific action (log in, copy token). It distinguishes itself from siblings by naming its target service and the browser-login flow, which is unique among the listed 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?

Provides explicit when and how to use: best practice (config header) vs session-only (paste token) vs no-args for link. This gives clear decision guidance, though it doesn't explicitly mention when not to use it or name alternative tools like 'connect' as a fallback.

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 the description adds valuable behavioral context: conditional return fields (authenticated, pending[], connect_url) and per-install URLs. This goes beyond the safe-read annotation without contradicting it.

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 each sentence adds distinct value. There is no redundancy or fluff, achieving maximum efficiency.

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 status tool with comprehensive annotations and no output schema, the description fully explains the primary return behavior and edge cases (missing credentials). It provides enough information for an agent to use the tool correctly without additional detail.

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 zero parameters, schema coverage is trivially 100%, so the baseline is 4. The description adds no parameter-specific detail (none needed), but knowing the tool takes no inputs is inherently conveyed by the empty schema, and the description clarifies what the output represents.

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, with specific outcomes for both connected and missing-credential scenarios. This distinguishes it from siblings like 'authenticate' and 'marketplace' by focusing on status reporting 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 implies use for checking connection status, but provides no explicit when-to-use or alternative guidance. It does not mention exclusions or direct comparison to sibling tools, leaving room for ambiguity in tool selection.

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 indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the agent already knows it's a safe read operation. The description adds valuable behavior: it discloses that the data is not confidential, it's the same available to citizens, and that the client is the data controller under LGPD. It also mentions payment via prepaid credits, which is crucial for understanding side effects (costs). No contradictions.

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 block of text, fairly concise, but it packs many pieces of information without clear structure. It is front-loaded with the purpose, but the legal and payment disclaimers, while important, are not separated. It could be more organized with bullet points or short paragraphs.

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 (15 params, no output schema, no enums), the description is not complete enough. It fails to explain what the tool returns (the information sought), the expected format for parameters like dates or URLs, or how to handle auth. The legal context is useful but does not compensate for the lack of parameter documentation.

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 the meaning or format of any of the 15 parameters. The parameter names like 'usuario', 'senha', 'ait', 'url_formulario' are self-explanatory to some extent, but the description adds no value. For a tool with 15 parameters, this is a significant gap.

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 this tool is for consulting driver identification (Identificação de Condutor Infrator) using an official source. It specifies the domain (DNIT) and the action (consult). It distinguishes from siblings, which are not related to this query, though it doesn't explicitly name a specific alternative.

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 this is a lookup service for Brazilian official data, but does not explicitly say when to use it vs. alternatives. It provides context about being hosted and payment model. No explicit exclusions or alternative tool references.

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 sparse annotations, the description discloses meaningful side effects: install makes an MCP permanent, invoke performs a one-off install, writes require workspace owner/admin, auth and wallet-empty cases return connect/checkout links, and installed status flags are surfaced. This substantially exceeds what readOnlyHint/openWorldHint/idempotentHint/destructiveHint 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 long but front-loaded: it opens with the core value proposition, then the search→describe→invoke flow, then the key one-off vs permanent distinction, followed by peripheral actions and the prompt library. It is dense and mostly earns its length, though the final prompt-library section is crammed into a single long sentence.

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 23-parameter multi-action tool with no output schema, the description is remarkably complete about workflows, auth/billing outcomes, and return signals (connect link, checkout link, shareable slug). It still leaves some return-value details and several parameters undocumented, but an agent can correctly select and invoke the main paths.

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 coverage, the description compensates by explaining the action enum and core workflow parameters like tool_id, prompt_vars, and prompt_slug. However, many of the 23 parameters (immediate, tier_slug, conversation, request_details, report_context, cancel_reason, etc.) receive no semantic explanation, leaving the agent to infer from names and 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?

The description opens with a specific, multi-part purpose: it is the mcp.ai marketplace catalog and execution layer, covering capability-request phrasing. It also distinguishes its internal actions (search, describe, invoke, install, prompt library) and, by naming them, separates itself from the sibling authenticate/connect/dnit 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 explicitly says when to use invoke (single/occasional use) versus install (permanent toolkit addition), and points to request_mcp when nothing fits. It also defines list_tools as what is callable right now and separates prompt-library actions from MCP actions, giving clear within-tool selection 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 cover idempotency, read-only, and destructive hints. The description adds the useful detail that the 'conversation' array is included for reproduction, giving some insight into expected input behavior. However, it does not elaborate on side effects (e.g., where the report goes, if confirmation is returned) beyond what annotations 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 exceptionally concise, consisting of two short sentences. The first sentence front-loads the primary purpose, and the second sentence immediately provides critical usage guidance. No superfluous words or redundant information.

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 relatively simple tool with flat parameters and no output schema, the description is mostly complete. It covers the core purpose and a key parameter. The main gap is the lack of documentation for 'message' and 'context', but given the tool's straightforward nature, the description is nearly sufficient.

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 must compensate but only clarifies the 'conversation' parameter ('Include the conversation array with recent messages for reproduction'). The required 'message' parameter and optional 'context' remain undocumented, leaving ambiguity about their format and 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 states the tool's purpose with a specific verb 'Report' and resources ('a bug, missing feature, or send feedback'), effectively distinguishing it from sibling tools like 'authenticate' or 'marketplace'. The purpose is unambiguous and immediately actionable.

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 the tool ('Report a bug... or send feedback') without explicitly listing alternatives or exclusions. It implies usage for any feedback-related task, which is sufficient for most cases, though it could be more explicit about when not to use it.

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, so the description needn't repeat these. The description adds no additional behavioral context beyond what annotations provide. It doesn't mention any side effects, prerequisites, or return format, but for a version query tool, the behavior is predictable. No contradiction.

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 relevant sentence, concise and front-loaded. Every word earns its place, and it provides all necessary information without 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?

Given the tool's simplicity (no parameters, no output schema), the description is complete. It tells the user exactly what information it will provide. Some might expect a version tool to clarify what 'adapter versions' means, but it's clear enough.

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 0 parameters, and schema coverage is 100%. The description doesn't need to explain parameters, and it correctly avoids doing so. Baseline for 0 params is 4, and the description is 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: 'Show the current MCP platform and adapter versions.' This is a specific verb-resource combination, and while siblings like toolkit_info and marketplace might be similar, the description clearly specifies what versions are shown, distinguishing it from other informational 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?

The description provides a clear context for use (when needing to know current versions), but it doesn't explicitly state when not to use it or compare to alternatives. Given the tool's simplicity and no parameters, this is adequate, but the description could have mentioned that it's a read-only informative tool, which is implied by annotations.

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 readOnly=true, idempotent=true, and destructive=false. The description's wording ('returns') aligns with these traits without contradiction. While the description does not explicitly state side effects, the annotations provide the necessary transparency, and the description is consistent with them.

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 lists the key output components without redundancy. It is well-structured and free of unnecessary details, achieving maximum informativeness with minimal 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 simple, read-only nature of the tool, the description is complete. It specifies exactly what the return value contains, making the output contract clear. No additional context about dependencies or side effects is needed, and the sibling tools do not require cross-referencing for this tool's 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 tool has no parameters, and the schema correctly reflects this. Since there are no parameters to describe, the description fully covers whatever input semantics exist (none). This is a trivial case but handled perfectly.

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: it returns the current toolkit state, enumerating specific components (installed MCPs, connection status, accounts, and catalog tool counts). This is unambiguous and specific, leaving no doubt about the tool's purpose.

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 it is implicitly a read-only informational call, there is no direct guidance on use cases (e.g., 'use to verify connectivity before making a request'). Given a collection of sibling tools like authenticate and connect, explicit usage direction would enhance clarity, but the simplicity of the tool mitigates the lack.

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