DETRAN MS: Multas

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

The description explains the effects of both usage modes: permanent config change or session-based login. It implies state modification through config addition but does not explicitly state side effects or error handling, though annotations indicate idempotency.

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 verbose and wordy, repeating instructions and including unnecessary details like 'MCP.AI for IDE agents'. It could be condensed to a few 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?

It provides sufficient context for typical use, covering the two authentication paths and the token acquisition process. However, it lacks information about return values or error scenarios, which might be needed given no output schema.

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 single parameter 'token' is clearly described as an optional JWT, with instructions to pass it after the user pastes it, and the alternative of omitting it to get the link.

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 for IDE agents via browser login and token. It distinguishes from sibling tools by focusing solely on 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?

It provides explicit usage instructions: either pass the JWT token as an argument for session-only login, or add it to the server config for a permanent connection. It also explains that calling with no arguments returns the login link, covering both usage modes.

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 safe. The description adds value by explaining the behavior in different scenarios (all connected vs. missing credentials), which goes beyond the annotations. However, it doesn't detail the exact structure of the return payload or how to interpret the URLs, but this is acceptable for a read-only status tool.

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 extremely concise: two sentences that state the tool's purpose and the key scenarios. It is front-loaded with the core function, and every clause adds value without 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?

Given the tool's simplicity (0 params, no output schema), the description is complete. It gives the agent enough to know what to expect in terms of response (auth status and URLs) and the conditions for different outcomes. The annotations provide safety context, so no further details are needed.

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)Skip? Ha! But the schema has no properties w/ 0 params, so the baseline is 4. Since the description explains the output (not params) because there are none, it fully covers what the agent needs to know to invoke the tool. No parameter information 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 states the tool returns connection status and URLs, distinguishing it from siblings like authenticate (which likely initiates connection) and toolkit_info (which provides general info). It is specific about the resource (connection status) and the outcome.

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 it (to check connection status) and provides context about the return values (authenticated, pending[], connect_url), but does not explicitly state when not to use it or mention alternatives. However, given the tool's simplicity and the clear distinction from siblings, the guidance is adequate.

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 indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the tool is read-only and safe. The description adds context about hosting, payment, and data control (LGPD), which is useful but does not disclose behavioral traits like response format or error handling. 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 concise, two sentences, and front-loaded with the main action. It includes essential contextual information (official source, payment model, LGPD) without verbosity. Could be slightly more structured but is efficient.

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 (two parameters, no output schema), the description covers commercial and legal aspects but lacks details on expected results (e.g., whether it returns fines list, status codes). However, with no output schema and basic parameters, it provides adequate context for an agent to select the 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 schema has two required parameters with no descriptions, and the description does not explain the parameters either. Since schema description coverage is 0%, the description should compensate but only mentions 'placa' and 'renavam' implicitly through the context of vehicle fines. This adds minimal semantic value beyond the schema.

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 queries DETRAN MS fines from an official source, specifying the resource (multas) and the context (official Brazilian sources). However, it does not explicitly differentiate from sibling tools, as the siblings appear unrelated (authenticate, connect, etc.), so it lacks a direct comparison but still provides a clear 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 explains the commercial context (pay-per-query with prepaid credits) and legal compliance (LGPD), but it does not provide explicit when-to-use guidance or mention alternatives. The 'consulta em fonte oficial' implies usage for official fine queries, but it lacks clear exclusions or comparison to other 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?

Beyond annotations (readOnlyHint=false, openWorldHint=true), the description reveals critical behaviors: invoke runs uninstalled MCPs one-off without bloating the tool list, returns connect/checkout links when auth/payment is needed, and writes require workspace owner/admin. It also discloses the distinction between installed_in_toolkit vs installed_in_workspace.

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 earns its place—no filler. It is structured around the core flow, then the invoke/install distinction, then the prompt library. The use of semicolons and run-on sentences makes it slightly harder to scan, but the density of information is appropriate for such a complex 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 23 optional parameters, a multi-action surface, and no output schema, the description is remarkably complete. It covers core workflows, auth/payment edge cases, permissions, return value patterns (connect link, checkout link, shareable prompt URL), and the separate prompt library feature. Only minor optional details (e.g., error handling) are omitted.

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 does heavy lifting by explaining the roles of action, mcp_id, tool_id, arguments, prompt_vars, and prompt_slug through workflow walkthroughs. However, it does not systematically define every parameter (e.g., limit, immediate, tier_slug, cancel_comment), leaving some parameters to rely on schema defaults 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 identifies the tool as the official mcp.ai marketplace, combining catalog discovery and execution. It distinguishes itself from siblings (e.g., report_bug, toolkit_info) by explaining its unique core flow: search → describe → invoke, and separately covering the prompt library.

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 usage guidance with alternatives: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT', plus when to use list_tools, request_mcp, subscribe/cancel, and report_bug. It also explains the retry flow after auth/payment fallbacks.

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=false, destructiveHint=false, and idempotentHint=true, so the description carries less safety burden. It adds useful context by explaining the conversation array is for reproduction, but does not disclose outcome/return behavior or any side effects 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?

Two short sentences, front-loaded with the primary action, and every clause adds value, including the reproduction detail. No redundancy or filler.

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 three-parameter, non-destructive reporting tool with good annotations, the description is largely sufficient: it states the purpose and the critical reproduction use of conversation. It is not perfect because required 'message' and optional 'context' semantics are absent, but the tool complexity is low and no output schema is promised.

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 for all three parameters, but it only mentions 'conversation' and only as an 'array', which conflicts with the schema's string type and default '[]'. It does not clarify the required 'message' field or optional 'context', leaving the agent without full parameter semantics.

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?

Description uses specific verb 'Report' with explicit targets 'bug, missing feature, or send feedback', clearly identifying the tool's scope. Sibling tools are unrelated, so there is no ambiguity about 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 intended use is implied by the opening phrase, and the instruction to include the conversation array for reproduction gives practical 'how-to' guidance. However, there is no explicit when-to-use or when-not-to-use wording, and no alternative tools are mentioned; since siblings are dissimilar, this is acceptable but not strong.

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, covering the safety profile. The description adds minimal behavioral context beyond 'current' (implying live retrieval), but it doesn't describe any side effects, rate limits, or return format. With annotations covering the main traits, this is acceptable but not enriched beyond structured data.

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 with zero wasted words. It front-loads the key verb and resource, making it immediately actionable. Nothing is superfluous.

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, rich annotations, no output schema needed), the description is complete for operational purposes. It explains what the tool does without needing to detail return values or side effects. A slightly higher score would require explicit statement of what versions are covered (e.g., adapter names), but this is adequate for a straightforward version checker.

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 baseline is 4. The schema is trivially complete (no parameters to document), and the description doesn't need to add parameter semantics. It correctly focuses on what the tool does rather than empty parameter details.

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 'show' and identifies the exact resource ('current MCP platform and adapter versions'), making the tool's purpose unambiguous. It clearly distinguishes itself from sibling tools like authenticate or connect, as none of those are about version information.

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 checking version info but provides no explicit guidance on when to use this tool versus alternatives. There is no mention of exclusions or context where another tool might be preferred (e.g., toolkit_info could also provide system info). The intent is obvious but not explicitly differentiated from siblings.

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 as readOnly and idempotent. The description adds valuable context about exactly what state is returned (installed MCPs, connection status, accounts, catalog counts), which goes beyond the structured fields. No contradictions 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 a single, well-structured sentence that front-loads the purpose ('Returns the current toolkit state') and then lists the components. No filler words or repetition; every word adds meaning.

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 no output schema, the description must convey what is returned, and it does effectively by listing the categories of information. It is sufficient for a stateless query, though it omits details on error scenarios or response format, which are not critical for such a simple 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 tool has zero parameters, so schema coverage is 100% (trivially). The baseline for zero parameters is 4; the description adds no parameter information since none exist, which is appropriate. It doesn't need to explain parameters that don't exist.

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 specific resource 'current toolkit state', enumerating the exact data points (installed MCPs, connection status, accounts, catalog tool counts). It distinguishes from siblings by focusing on overall toolkit inspection rather than authentication or specific operations.

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 a diagnostic use (inspecting state) but does not explicitly state when to use it over alternatives or mention exclusions (e.g., 'use this before other tools to check readiness'). Sibling tools like 'connect' or 'marketplace' are distinct, but no guidance is offered for when this is the right choice.

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