DETRAN MG: TRLAV

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

The description discloses key behaviors beyond annotations: calling with no args returns a link, calling with a token establishes a session-only login, and config-based auth provides permanent access. It does not mention any side effects like overwriting existing sessions, but annotations already indicate idempotent and non-destructive behavior, and the description adds useful context about session duration.

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 slightly long but well-structured, front-loading the core purpose and then explaining the two usage patterns. Each sentence adds operational detail, so there is minimal waste, though it could be tightened for clarity.

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 covers the essential authentication flow, including both permanent and session-based approaches, and mentions what happens with no arguments (getting a link). It does not explicitly state the return format or potential errors, but for an auth tool with no output schema, it provides sufficient context to invoke and interpret results.

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 only a single string parameter, the description fully compensates by explaining exactly what the 'token' parameter is (a JWT from browser login) and how its presence vs. absence changes behavior (session login vs. retrieving a link). This is clear semantic guidance.

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 an authentication mechanism for IDE agents, explaining the browser login flow and token handling. It does not explicitly name sibling tools like 'connect' to differentiate, but the verb 'log in' and the resource 'access token' make the purpose evident.

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 when-to-use scenarios: adding the token to the server config for a permanent non-expiring connection, or pasting it in as a session-only login. It distinguishes between these two modes with a 'Best' recommendation, though it does not explicitly contrast with alternative 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 declare read-only and idempotent behavior, but the description adds specific response details such as authenticated:true, empty pending[], and connect_url, which go beyond the annotation hints and clarify the tool's output in different scenarios.

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-loading the core purpose ('Returns connection status and URLs') and then explaining conditional behavior. No wasted 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?

For a tool with no parameters and no output schema, the description provides a fairly complete picture by covering both possible return states. It could possibly include the exact JSON structure, but the key fields are mentioned, and annotations cover safety.

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 is empty (0 parameters), so there is nothing for the description to add. According to the rubric, 0 params has a baseline of 4, and the description does not need to elaborate on 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, using a specific verb and resource. This distinguishes it from siblings like 'authenticate', which likely performs authentication, and 'toolkit_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 provides clear contextual states: when all providers are connected versus when credentials are missing. This implies when the tool is useful for checking connection status, though it does not explicitly name alternatives or exclusions.

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 safety profile is covered. The description adds meaningful behavioral context: pay-per-query billing, no platform credentials, official-source data, and LGPD data-controller responsibility. It does not describe response format or failure modes, but those are not required by 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 only three sentences and front-loads the core purpose before addressing payment and legal terms. It is reasonably tight, though the LGPD sentence is somewhat boilerplate and the mixed clauses could be structured more cleanly.

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 2-parameter read-only tool with good annotations, the description covers source, billing, and compliance. It does not state what fields or data the consultation returns, nor does it decode the TRLAV acronym, so an agent cannot fully predict the output.

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 gives no explanation of 'renavam' or 'ano'. A domain-savvy agent may infer RENAVAM is a Brazilian vehicle identifier and that 'ano' is a year, but the tool does nothing to clarify formats, constraints, or which year (model, manufacturing, licensing).

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 'DETRAN MG: TRLAV, consulta em fonte oficial' and identifies the tool as a consultation against an official Brazilian source, which gives a clear verb+resource pairing. It does not expand the TRLAV acronym or state exactly what record types are returned, so it is clear but slightly underspecified.

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 useful context: the tool is hosted by the platform, requires no platform credentials, uses prepaid credits, and queries official public data. However, it never explicitly says when to choose this tool over siblings like connect or marketplace, or 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?

The description goes well beyond the sparse annotations, disclosing side effects and special behaviors: invoke works even without installation, may return connect/checkout links requiring retry, install makes tools permanently appear, and writes require workspace owner/admin. It also notes installed_in_toolkit vs installed_in_workspace flags, adding valuable behavioral context.

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?

Every sentence packs useful information and there is no fluff, but the description is a single dense paragraph covering 14 actions and prompt-library features. It is front-loaded with the purpose and core flow, yet the lack of paragraphing or bullet-like structure makes it harder to scan than it could be.

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 complex multi-action hub with no output schema, the description is remarkably complete: it covers core flows, credential/payment edge cases, permission requirements, install vs invoke semantics, and the prompt library. It does not explain every action (e.g., resume, immediate) or return shapes, but it provides enough context for correct tool selection and invocation in most scenarios.

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 is the only source for parameter meaning, and it compensates substantially by explaining the role of action, mcp_id, tool_id, arguments, prompt_* fields, cancel_reason, request_* fields, and report_bug context. However, it leaves several parameters (immediate, resume, tier_slug, conversation) unaddressed, so it is not fully comprehensive for a 23-parameter 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 clearly states the tool is the official mcp.ai marketplace and the way to run MCPs/tools, covering search, describe, invoke, install, and prompt-library actions. It is specific about the resource and core flow, but it does not explicitly differentiate from sibling tools like authenticate, connect, or toolkit_info, so it stops short of a 5.

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 when-to-use guidance with clear alternatives: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use,' and 'request_mcp asks us to build a NEW MCP when nothing fits.' It also explains the search→describe→invoke progression and covers prompt-library usage, giving the agent actionable decision rules.

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 does not disclose side effects or outcomes (e.g., what happens after submission). The annotations indicate it's non-read-only and idempotent, but the description itself adds little transparency beyond what the annotations already state.

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 and efficiently uses two sentences to convey the purpose and a key usage detail. No unnecessary verbiage 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?

The description covers the core functionality and provides an important instruction (include conversation for reproduction). It does not mention output, but given the absence of an output schema, this is acceptable. Overall, it is complete for a simple bug-reporting 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?

The description explains the 'conversation' parameter (as an array for reproduction) and implies 'message' is the content of the report, but it does not clarify 'context'. Additionally, it refers to 'conversation array' while the schema defines it as a string, potentially causing confusion. Coverage of parameters is partial.

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: reporting bugs, missing features, or sending feedback. This is distinct from the sibling tools (authenticate, connect, etc.), making the purpose unambiguous.

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 actionable guidance by instructing to include the conversation array for reproduction. While it doesn't explicitly contrast with alternatives, the tool's niche is apparent and the usage instruction is practical.

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, and the description's 'Show' aligns with them. The description adds minor scope details (platform and adapter versions) but no further behavioral context such as network usage, return format, or lack of authentication requirements, so it provides limited added transparency 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 a single concise sentence, front-loaded with the verb 'Show', and contains no unnecessary words or redundant phrasing. It is optimally compact.

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 trivial 0-parameter version query, the description is fully sufficient: it names exactly what will be shown (MCP platform and adapter versions). No output schema exists, but the return value (version strings) is the obvious implication, and no further detail is needed for an agent to invoke this tool 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?

The tool has zero parameters and the schema is an empty object, so there is no parameter ambiguity to resolve. A baseline of 4 is appropriate because 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?

Clearly states a specific verb ('Show') and resource ('current MCP platform and adapter versions'). It is semantically distinct from sibling tools like authenticate, marketplace, or report_bug, all of which perform different 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 the usage context (checking current versions) but does not explicitly state when to use it, such as for diagnosing version mismatches or verifying environment setup, nor does it mention alternatives. For a trivial 0-parameter tool, the implied usage is acceptable but not fully 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?

The annotations already communicate read-only, idempotent, and non-destructive behavior. The description adds useful context about what information the state includes, such as accounts and connection status, without contradicting the annotation.

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 entire description is one well-structured sentence that front-loads the main point and packs useful detail into a compact list. Every clause carries information; there is no fluff 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?

For a simple read-only, parameterless tool, this description is complete: it explains what is returned, includes enough specificity for selecting the tool, and is accompanied by strong annotations and no output-schema requirements.

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 and an empty input schema, so the schema cannot be expected to add meaning. The description also does not need to document parameters, and it provides no misleading parameter information.

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 a specific verb ('Returns') and a clearly scoped resource ('current toolkit state'), and it enumerates exactly what is included: installed MCPs, connection status, connected accounts, and exposed tool counts. This clearly distinguishes it from sibling tools like show_version or 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 makes it evident that the tool is meant for inspecting/discovering the toolkit's current configuration and connectivity. It does not explicitly say when to use an alternative, but no sibling tool claims the same introspection role.

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