DETRAN MG: IPVA

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

Annotations declare idempotentHint=true and readOnlyHint=false, but the description adds valuable context: it explains what the tool does (returns a link, saves a token) and its two modes (permanent vs session). It doesn't contradict annotations. Some details like potential browser opening or token storage are implied but not explicit, so a 4 is appropriate.

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 but somewhat dense, packing multiple instructions into two sentences. It front-loads the purpose and then explains options. Some punctuation could be improved, but it's efficient and well-organized. Points deducted for the slightly run-on second 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 tool with only one optional parameter and no output schema, the description covers the essential workflows: permanent config, session token, and no-arg link retrieval. It does not describe the return value in detail, but that's not critical. It is sufficiently complete for 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?

The input schema has a single optional token parameter with no description. The tool description compensates by explaining that token is a JWT for session-only login)Skip not mandatory (no args gets link), and contrasts with the config approach. This adds meaning beyond the schema, though it could be more explicit about token format or validation. Given low schema coverage, this description does a good job.

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 purpose: authenticating with MCP.AI for IDE agents. It uses a specific verb ('log in') and resource ('MCP.AI'), and distinguishes itself from likely siblings like 'connect' by focusing on token-based authentication. The purpose is unambiguous and contextually rich.

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 when-to-use guidance: it explains the permanent configuration method versus session-only login, and instructs on calling with no args to get the link. It clearly differentiates usage scenarios and gives actionable instructions, fulfilling the dimension fully.

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 the tool is read-only, idempotent, and non-destructive. The description adds conditional behavioral details, such as returning authenticated:true with empty pending[] or returning connect_url and per-install URLs when credentials are missing. This goes well beyond the annotations and gives the model a clearer picture of the tool's conditional output 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?

The description is only two sentences and is highly information-dense. Every sentence adds value: the first states the general purpose, and the second illustrates the different return states. There is no filler 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?

With zero parameters and no output schema, the description does a good job of explaining what the tool returns and the main conditional outcomes. It could be a bit more complete by explaining what pending[] contains or how partial connection states are reported, but for a status-checking tool with such a simple interface, the description is 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?

There are no parameters in the schema, and schema coverage is 100%, which is the baseline for full coverage. The description therefore does not need to explain parameter meanings. The only enhancement would have been to describe the response object shape, which it partly does via authenticated and pending examples.

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 as returning connection status and URLs, which is specific and informative. It also explains the different response states (authenticated vs. missing credentials), making its purpose unambiguous and distinct from a tool like 'authenticate' which likely performs authentication rather than status reporting.

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: if you need connection status or authentication URLs. It explicitly distinguishes behavior under different credential states (all connected vs. missing credentials), but it does not explicitly say 'use this to check status, use authenticate to connect', leaving the usage guidance mostly implicit rather than stating a clear alternative.

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, so the tool is known to be a safe read operation. The description adds useful context about payment per query, no credentials required, and LGPD responsibility, which enhances transparency beyond annotations. However, it does not detail what happens on invalid input or data privacy specifics beyond the generic LGPD note.

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 conveys key information efficiently. It is not overly verbose, and the most important facts are front-loaded. It could be improved with bullet points but is acceptable.

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 moderate complexity (2 params, simple query), the description covers the key points: purpose, data source, payment model, and legal compliance. However, lack of output schema and minimal parameter documentation leaves some ambiguity about how to use the tool effectively, such as the format of 'ano' or what response is expected. It is adequate but not comprehensive.

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 two parameters: renavam (required) and ano (optional). Schema description coverage is 0%, so the description must compensate. The description does not explain the purpose of these parameters or their expected formats. It only mentions the data source and legal aspects, leaving parameter semantics unexplained, which is a 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 specifies that the tool queries IPVA data from DETRAN MG official sources, but it does not explicitly name the operation as 'consult' or 'query'. It distinguishes from siblings by mentioning DETRAN MG and IPVA, though it doesn't contrast with other potential data lookup 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 implies usage for legitimate purposes (LGPD compliance), but it does not provide explicit guidance on when to use this tool versus alternatives. It mentions it's for official data, but no when-not-to-use or alternative tools are referenced.

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 (readOnlyHint=false, openWorldHint=true), the description discloses critical behavioral traits: invoke runs one-off even if the MCP is not installed without bloating the toolkit, auth failures return a connect link, payment issues return a checkout/top-up link with a retry instruction, and writes (install/uninstall/subscribe/cancel) require workspace owner/admin. These specifics add real operational context that annotations alone do not 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 long but every sentence contributes unique operational detail. It is front-loaded with the core purpose, uses a clear arrow flow for the core sequence, and marks key nuances with 'KEY:'. The length is justified for a 14-action tool, though a slight tightening of the prompt-library section could make it more concise.

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 high complexity (23 params, 14 actions, no output schema), the description covers the main workflows well: search→describe→invoke, install vs invoke, credential/payment edge cases, permissions, and prompt library. But it omits some actions (resume) and several params (immediate, tier_slug, conversation, etc.), leaving gaps for an agent to infer those meanings. Still, it is far more complete than most tool descriptions.

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 full burden. It explains the action enum values, mcp_id and tool_id in the flow, and prompt library params like prompt_slug and prompt_vars. However, several parameters remain unexplained (immediate, tier_slug, conversation, cancel_reason, prompt_targets, request_details, etc.), so it does not fully compensate for the schema 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 opens with a precise declaration: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It then enumerates the specific capability areas (search, describe, invoke, install, prompt library) and distinguishes the tool from siblings by covering both catalog discovery and execution.

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: 'Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile ... so you pick the right tool_id → invoke RUNS that tool.' It also contrasts invoke vs install ('Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use') and names alternative tools like list_tools and search_prompts, covering when to use each.

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 the operation as idempotent, non-destructive, and not read-only. The description adds useful behavioral context by stating that the conversation array is used for reproduction. This goes beyond the structured data 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 short sentences, front-loaded with the primary purpose and followed by one key usage note. Every word earns its place; no redundant or filler language.

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 three parameters and no output schema. The description covers purpose and the conversation parameter but omits semantics for message and context, leaving an incomplete picture for an agent. It is adequate for a minimal viable understanding but not comprehensive.

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 only the 'conversation array' and its purpose, but fails to explain the meanings of 'message' (required) and 'context.' With three parameters and no schema descriptions, 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 uses a specific verb and resource: 'Report a bug, missing feature, or send feedback.' This clearly defines what the tool does and distinguishes it from sibling tools (e.g., authenticate, connect, detran_mg_ipva_consultar), which are unrelated.

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 indicates the appropriate use cases (bug, missing feature, feedback) and provides a practical instruction: include the conversation array for reproduction. It does not explicitly name alternatives or exclusions, but the context is clear and no sibling tool overlaps.

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, covering the safety profile. The description adds specificity by mentioning both platform and adapter versions, but it does not enrich behavioral context beyond what annotations imply. 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 a single, dense, front-loaded sentence with zero superfluous words. Every word carries meaning, making it ideal for quick agent parsing.

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 clear annotations, this description is entirely complete. It accurately tells the agent what the tool does, and there is no missing information that would hinder invocation.

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 need not add parameter meaning. Per the rule, a baseline of 4 applies, and since schema coverage is 100% (vacuous) and there's nothing to explain, this is fully adequate.

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: showing current MCP platform and adapter versions. It uses a specific verb ('Show') and a specific resource, and it easily distinguishes from sibling tools like authenticate, connect, or marketplace, which have unrelated 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 tool is so straightforward that usage context is implied: it's for checking version information. No explicit alternatives exist among siblings, and the description provides clear context without needing exclusions. A score of 4 is appropriate for a self-explanatory informational tool.

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 establish readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the agent knows this is safe to call. The description adds useful context about what the returned state contains, but it does not describe any additional behavioral traits such as staleness, latency, or side effects. This is adequate but not exceptional given the strong annotation coverage.

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 sentence, front-loads the core action, and every phrase adds value by specifying exactly what toolkit state is exposed. There is no filler, vague jargon, or duplication of the schema or annotations.

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 no-input, read-only introspection tool with full annotation coverage, the description is complete: it enumerates the return categories and leaves no obvious gaps. Since there is no output schema, the description appropriately carries the burden of explaining what information the caller will receive.

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 input schema is empty, so no parameter documentation is needed. The description fully clarifies what the tool reports, and the schema needs no additional semantic help.

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 identifies a concrete resource ('the current toolkit state') while enumerating the exact content included: installed MCPs, connection status, accounts, and catalog-tool counts. This clearly distinguishes it from sibling tools like authenticate, connect, and show_version, as it is an informational/overview tool rather than an action or version tool.

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 makes the intended use obvious: call this tool to inspect installed MCPs, connection status, and account associations. It does not explicitly name alternatives or state when not to use it, but the role of an introspection/status tool is clearly implied, and the sibling tools are distinct action-oriented tools.

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