DETRAN AM: Multas

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

The description adds context by mentioning 'permanent, non-expiring connection' and 'session-only login', which implies state changes. It does not explicitly state that authentication modifies server state, but it is reasonably transparent given the annotations (idempotent, non-destructive). Some side effects remain implicit.

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 well-structured: it opens with the purpose, then gives the primary login flow, followed by the two usage options. It is moderately long but each sentence adds value; no redundant fluff. The front-loaded purpose aids quick understanding.

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 how to authenticate, but it does not explicitly state what the tool returns when a token is provided (e.g., success message or error). It only mentions 'get the link' for the no-args case. With no output schema, this leaves some ambiguity about return values and error handling.

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 defines only 'token' as a string (optional). The description clarifies that 'token' is a JWT used for session-only login, and that calling with no args returns a link. This adds meaningful semantics beyond the raw schema, though it does not detail token format beyond '<jwt>'.

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 MCP.AI for IDE agents. It explains the login process and provides two authentication methods (permanent via config header, session-only via token). It is easily distinguishable from sibling tools like 'connect' or 'marketplace'.

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 step-by-step instructions: log in, copy token, then either add to config or call with token. It also explains the 'no args' case for retrieving the link. However, it does not explicitly mention when to prefer one method over the other or compare with alternatives, though the distinction is implicit.

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, so the description does not need to repeat safety traits. It adds value by explaining conditional output (authenticated:true vs. connect_url), which is behavioral detail beyond annotations. 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 exactly two sentences, front-loaded with the core purpose ('Returns connection status and URLs'), and each sentence adds essential information about conditional outputs. No wasted words or redundancy.

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 simplicity (no parameters, no output schema) and the presence of clear annotations, the description is complete for an agent. It covers what the tool does, the two possible outcomes, and what the response includes, leaving no critical gaps for safe usage.

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 schema, so there is nothing to document. Per the baseline for 0-parameter tools, the description does not need to add parameter-specific meaning; it correctly focuses on output behavior.

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 and resource: 'Returns connection status and URLs.' It also distinguishes behavior for two states (all connected vs. missing credentials), making it unambiguous and distinct from sibling tools like 'authenticate' which performs authentication.

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 as a status-checking tool (checking connection and URLs), but gives no explicit guidance on when to use it versus alternatives like 'authenticate' or 'toolkit_info'. It lacks any 'use when' or 'do not use' instructions, so the agent must infer from context.

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 goes beyond by explaining it's hosted on the platform, requires prepaid credits for payment, and that it accesses official public data. This adds value, but it doesn't fully cover all behavioral implications, such as potential response delays or legal complexities beyond the 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 concise and front-loaded, with the essential information in the first sentence. It covers payment, data source, and legal considerations in a single paragraph without unnecessary verbosity. Every sentence adds context, making it appropriately sized.

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 (querying official Brazilian data) and the lack of output schema, the description provides sufficient context on the data source and legal aspects. However, it misses critical operational details like response format, possible errors, or rate limits, which are important for an agent to handle results correctly. The description is adequate but not fully comprehensive for all 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?

The schema has 0% coverage and only defines 'placa' and 'renavam' as strings with no descriptions. The description mentions the tool requires these fields but does not explain the meaning, format, or validation rules. For example, it doesn't specify that 'placa' is a vehicle license plate or that 'renavam' is a vehicle registration number, nor does it outline format requirements, which is a significant gap given low schema coverage.

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 queries multas (fines) from an official DETRAN-AM source, using a specific verb 'consulta' and a resource. It distinguishes itself from sibling tools by focusing on a specific domain (DETRAN-AM multas) and mentions it provides the same info available to citizens, differentiating it from other tools that may offer different data.

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 context about the tool's purpose but lacks explicit guidance on when to use it versus alternatives. It doesn't mention any prerequisites or situations where it shouldn't be used. Sibling tools are generic (authenticate, connect, etc.) and don't overlap, so some implicit distinction exists, but no explicit when-to-use guidance is given.

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 important behavioral traits: invoke runs tools even when not installed without bloating the toolkit, may return connect or checkout links requiring user action before retrying, and writes require workspace owner/admin. It also explains the distinction between permanent install and one-off invoke, and that prompt links open without login.

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 densely structured and front-loaded: it opens with a definition, moves through the core search/describe/invoke flow, highlights the most important 'invoke works even when not installed' behavior, then covers install vs invoke, permissions, and the prompt library. Every sentence adds functional information, and the organization supports quick scanning despite the broad scope.

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 a wide range of contextual needs: auth/credential handling, paid-MCP wallet edge cases, workspace owner/admin requirements, installed vs non-installed behavior, and the distinct purposes of all 14 actions plus prompt-library functions. It does not specify the exact output/response structures for search/describe/list_tools or the formatting of complex parameters like arguments and prompt_vars, but the action-level completeness is strong for such a multifaceted 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 adds meaning to the central action parameter by contextualizing all enum values (search, describe, install, invoke, prompt actions, etc.) and explains the role of tool_id in the 'pick the right tool_id → invoke' flow. However, with 23 parameters and 0% schema description coverage, many parameters are left undefined (query, limit, arguments format, immediate, tier_slug, conversation, cancel_reason/comment, prompt_vars, request_details), so the agent must infer their semantics from names alone.

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 defines the tool as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them' and lays out a concrete core flow (search → describe → invoke). It distinguishes its scope from sibling tools by enumerating actions like report_bug, request_mcp, and the prompt-library functions, making it unmistakable what this tool does.

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, actionable guidance: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT in the active toolkit.' It also tells the agent when to use prompt-specific actions (search_prompts/get_prompt) versus MCP search, and explains the retry behavior for connect/checkout links, giving clear decision criteria versus alternatives.

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 implies a side effect (submitting a report) but does not detail outcomes, permissions, or rate limits. With sparse annotations, it carries partial burden but lacks explicit behavioral disclosure.

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—with no redundant wording, and the instruction is placed directly after the 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?

For a simple reporting tool with no output schema, it covers the essential input guidance (conversation for reproduction) and is otherwise complete, though it could mention the expected response or outcome.

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?

Only 'conversation' is hinted at in the description; 'message' and 'context' are not explained. Since schema coverage is 0%, the description fails to clarify the meaning of all 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's action ('Report') and the resource ('bug, missing feature, or send feedback'), making its purpose unmistakable even without sibling context.

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 explains when to use (to report issues/feedback) and gives a specific instruction (include conversation array for reproduction), though it doesn't explicitly discuss alternatives since none exist.

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, idempotent, and non-destructive behavior; the description adds 'current' but doesn't elaborate on side effects or output characteristics beyond that.

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, focused sentence with no unnecessary words, making it highly 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?

For a simple information tool, the description is adequate, but it could specify what the returned version information includes (e.g., format or fields) to be more complete.

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 fully covers parameter usage; no additional explanation needed.

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 shows current MCP platform and adapter versions, making its purpose unambiguous and distinct from sibling tools like 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 no guidance on when to use this tool versus alternatives (e.g., toolkit_info), leaving the selection context unclear.

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 readOnlyHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds concrete behavioral context: what data is returned (installed MCPs, connection status, accounts, tool counts). This enriches beyond annotations without contradicting them. Minor gap: no mention of possible errors or pagination, but for a zero-parameter info call this is acceptable.

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, front-loaded sentence that states the primary purpose and then lists the key elements. Every word adds value, with no redundancy or filler. It efficiently communicates the tool's role.

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 simplicity (no parameters, no output schema, read-only informational tool), the description fully covers what the tool returns. It explicitly lists the components of the toolkit state, which is sufficient for an agent to understand the outcome without needing an output schema. The low complexity does not demand more.

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 schema coverage is 100% (there are no parameters to describe). Baseline for 0 params is 4, and the description doesn't need to explain parameters since none exist. It effectively conveys that no input 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 verb 'Returns' and the resource 'current toolkit state', then enumerates specific contents: installed MCPs, connection status, accounts, and catalog tool counts. This distinguishes it from siblings like show_version (which focuses on version only) and marketplace (which likely lists available 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 obtaining an overview of the toolkit state. While it doesn't explicitly say when not to use it or mention alternatives, the resource is clearly a general info-read, and siblings like authenticate/connect are obviously for actions. It lacks explicit exclusion guidance, so not a 5.

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