DETRAN MA: Multas

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

The description discloses that the config approach creates a 'permanent, non-expiring connection' while pasting a token gives a 'session-only login', adding behavioral context beyond the annotations. It does not explicitly cover error handling or token management, but it covers the main outcomes.

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 reasonably concise but packs a lot into a single run-on sentence with colons and commas. It is front-loaded with the tool's purpose and avoids unnecessary words, though it could be broken into clearer sentences.

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 auth tool with one optional parameter and no output schema, the description covers the main scenarios (permanent config, session token, and obtaining a link). It implies the response contains a link but does not detail error cases or return structure, which is acceptable given 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?

Despite 0% schema description coverage, the description fully explains the 'token' parameter as a JWT to paste, and the no-argument call to retrieve the link. This goes beyond the bare schema and clearly instructs how to invoke both modes.

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 for authenticating IDE agents (Cursor, etc.) by logging in via browser and copying an access token. It specifies the action (authenticate), the resource (this server's config), and distinguishes itself from siblings like 'connect' by describing the auth flow.

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 describes when to use the config header approach for a permanent connection vs. pasting a token for session-only login, and mentions calling with no args for a link. This provides clear alternatives and when to use each, meeting the 'when/when-not' criterion.

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, reducing the burden. The description adds valuable context about the return values (authenticated, pending, connect_url) and explains conditional behavior based on credential presence, which goes beyond the annotation metadata and helps the agent predict outcomes.

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 succinct sentences that front-load the main purpose ('Returns connection status and URLs') and then briefly explain the two possible outcomes. There is no verbosity or redundancy, and every sentence adds meaningful 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?

Given the tool is simple with no parameters and no output schema, the description adequately explains the two main states (all connected vs. missing credentials) and what fields are returned. It does not cover partial connection states, but this may be outside the tool's scope. Overall, it provides enough detail for an agent to understand the tool's behavior.

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?

Since there are zero parameters, the schema trivially covers all (100% coverage). The baseline for 0 parameters is 4, and the description correctly omits any parameter details because none exist, so no additional semantic info is 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 returns connection status and URLs, with specific details about output when all providers are connected vs. when credentials are missing. This distinguishes it from siblings like 'authenticate' which handles authentication rather than status.

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 the status is expected (all connected vs. missing credentials) but does not explicitly mention alternatives or when not to use this tool. It implies usage for checking connection status but lacks explicit 'use this instead of X' guidance for sibling tools like authenticate.

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 cover readOnlyHint, idempotentHint, and destructiveHint, so the description adds complementary context: the tool is hosted by the platform, no platform credentials, payment per query, and relevant data privacy legal statements (LGPD). It does not add any misleading or contradictory behavior details.

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 starts with the concise purpose, then adds necessary operational, financial, and legal details. It is not bloated, but repeated references to 'official sources' and LGPD have slight redundancy. Overall, each sentence conveys important context for a paid Brazilian data-consultation tool.

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 is very simple (two parameters, no output schema), the description covers the main intent, payment model, and legal conditions. However, it lacks details about output format, any notification of missing results, or possible failure states such as invalid placa or renavam. The completeness is a moderate baseline with clear gaps.

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 coverage is 0%: descriptions are absent for placa and renavam. The description does not mention or explain these parameters, discuss formats, or provide examples. It expects the agent to infer that placa is the license plate and renavam is the Brazilian vehicle registration number; this ad hoc knowledge is implicit and not supported by the tool description.

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 explicitly states the action: consultar multas (query fines) from a specific resource: DETRAN MA, an official source. It uses a specific verb and resource, and clearly differentiates from the sibling tools like authenticate, marketplace, and report_bug by describing a niche municipal/government data-lookup service.

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 gives useful context for when to use this tool: for consulting official Brazilian traffic fines, paying via prepaid credit, and with no platform credentials required. It does not definitively contrast with alternatives, because none of the sibling tools offer a comparable consultancy, so it is more clear context than optional 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?

The description discloses important behaviors not covered by annotations: writes require owner/admin, invoke works even if MCP isn't installed, returns connect or checkout links when credentials or payment are needed, and distinguishes installed_in_toolkit vs installed_in_workspace. It doesn't mention rate limits or error details, but annotations already signal non-read-only and non-idempotent behavior, so the description adds meaningful context beyond 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 long but every sentence adds value, covering the core flow, key actions, and permission requirements. It is front-loaded with a clear definition and the flow, though it is a dense paragraph that could benefit from structured bullets. Given the tool's complexity, the length is justified and not wasteful.

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 all major workflows: searching, describing, invoking, installing, billing management, bug reporting, and prompt library actions. It gives enough behavioral context for the agent to act, though it doesn't document all parameters or exact output shapes (no output schema exists). For such a complex tool, it is reasonably 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 schema has 0% parameter descriptions, so the description bears the full burden. It explains the main parameters indirectly through action descriptions (query, mcp_id, tool_id, arguments, prompt_* ), but leaves many parameters like limit, immediate, tier_slug, conversation, report_context, and request_details undocumented. This is a partial compensation, not full.

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 is the official mcp.ai marketplace for discovering and running MCPs, and also hosts a prompt library. It uses specific verbs like 'search', 'describe', 'invoke' and 'install', and distinguishes it from siblings by being the central in-platform catalog and execution layer.

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 for each action: prefer invoke for one-off use, install for permanent addition, list_tools for currently callable tools, subscribe/cancel for billing, report_bug for feedback, request_mcp for new MCPs, etc. It also explains the search→describe→invoke core flow, making it clear when to use this tool over 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?

Annotations declare idempotentHint=true and destructiveHint=false, which the description does not contradict. The description adds context by requiring the conversation array with recent messages for reproduction, which is useful behavioral information 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 two sentences, front-loaded with the purpose and then a specific usage directive. Every word earns its place with no 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?

For a simple bug-reporting tool with one required parameter, the description covers the purpose and a key usage requirement. There is no output schema, so return values need not be explained, though a note on what happens after submission would add completeness.

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 coverage is 0%, so the description must compensate. It explains the 'conversation' parameter as 'recent messages for reproduction' and implicitly describes 'message' as the bug/feedback text. However, the 'context' parameter is not mentioned, leaving 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 uses the specific verb 'Report' and names the resources: bug, missing feature, or feedback. It is clearly distinct from sibling tools like authenticate, connect, and 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 purpose implies when to use it, but there is no explicit guidance about when not to use it or alternatives. The description states what the tool does but does not provide exclusions or comparisons.

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 this as read-only (readOnlyHint=true) and idempotent (idempotentHint=true). The description adds that it returns version information, which is consistent but does not disclose additional behavioral traits (e.g., exact return format, potential delays). It adds modest value beyond 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, clear sentence that front-loads the action and object. There is no wasted verbosity; every word contributes to 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?

For a simple zero-parameter, read-only tool with annotations covering safety and idempotence, the description is sufficient. It clearly states what is shown, though it does not mention output format or any side effects (which are none). It could note that it returns a version string, but it is not necessary for basic use.

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, the baseline is 4. The description does not need to describe parameters, and no parameters exist to add meaning for. The description accurately conveys the sole 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 states a specific verb ('Show') and resource ('current MCP platform and adapter versions'), which clearly identifies the tool's purpose. It distinguishes itself from a potential sibling like 'toolkit_info' by focusing specifically on versions, though it does not explicitly mention that distinction.

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 via its clear purpose but provides no explicit guidance on when to use it versus alternatives, such as 'toolkit_info'. It lacks context about typical use cases or exclusions, making it adequate but not proactive.

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, destructiveHint=false, so safety is clear. The description adds specificity about what 'state' includes (connection status, account lists, catalog tool counts), going beyond the annotations. There is 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?

One sentence, front-loaded with 'Returns the current toolkit state' and then enumerates the components. No fluff, every phrase adds value.

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 no parameters and no output schema. The description covers what is returned (installed MCPs, connection status, connected accounts, catalog tool count). Annotations confirm read-only nature. This is sufficient for a basic info tool, though it could mention whether any of these values could be empty or have special states.

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?

No parameters exist (0 required, 0 optional). Baseline for 0 params is 4. The description sufficiently explains the output, so no gaps.

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 the current toolkit state' and enumerates specific components (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from siblings like authenticate/connect (which perform actions) and show_version (which shows version 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 implies use cases: when you need an overview of the toolkit's installed/connected components. It doesn't explicitly state exclusions or alternatives, but it's unambiguous that this is for retrieving state, not for changing it. Sibling names (authenticate, connect) suggest different purposes, so no confusion.

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