DETRAN BA: Multas

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

The description adds meaningful behavioral context beyond annotations: it explains the permanent vs session-only modes, the no-args behavior to get the link, and the token-based login. It doesn't contradict the annotations and mostly clarifies the tool's side effects.

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 front-loaded with the core purpose and each sentence adds use-case value. It is slightly run-on and informal with phrases like 'Best:' but remains compact and structured well for its content.

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?

Despite no output schema, the description does not specify what is returned when a token is submitted, only implying a session login. It covers the main auth flow and token parameter, but the missing return/response detail makes it incomplete for an agent needing to handle the result.

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 only describes 'token' as an optional string with no explanation, and schema description coverage is 0%. The description fully compensates by explaining the token is a JWT, when to provide it, and that omitting it returns the login 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 authenticates to MCP.AI via browser login and token exchange, using specific actions like 'log in' and 'copy the access token'. It does not explicitly differentiate from sibling tool 'connect', so it falls short of a perfect 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 usage alternatives: 'Best' for permanent config header vs session-only paste, and no-args for getting the link. It provides clear when-to-use scenarios, though it doesn't mention alternative sibling 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 indicate readOnlyHint, idempotentHint, and non-destructive behavior, so the description adds value by explaining the conditional output states, including authenticated:true, pending[], and connect_url. It goes beyond the annotation metadata 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 sentences and front-loads the core action in the first sentence. Every clause contributes meaningful guidance about the tool's return behavior.

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 rich annotations, the description covers the main expected return states and missing-credential behavior. It does not spell out partial-connection output, but the tool's low complexity and strong annotation support keep the burden low.

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 100% schema description coverage, so the baseline is 4. The description adds no parameter-specific meaning, but none 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 opens with a specific verb and resource: 'Returns connection status and URLs.' It clearly distinguishes the tool as a status/read check, which differentiates it from the sibling 'authenticate' 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 provides clear contextual states ('when all providers are connected' vs 'when credentials are missing'), which effectively tells the agent when this tool is relevant. However, it does not explicitly name alternatives like 'authenticate' or state 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?

Beyond the readOnly and idempotent annotations, the description discloses additional behaviors such as payment per query, no platform credentials required, and non-confidential data handling (LGPD). No contradictions with 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 relatively concise, though it repeats the official-source idea. It is a single paragraph with clear segmentation, but minor redundancy prevents a perfect score.

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 provides essential context (purpose, cost, data source) but omits details about how to use the parameters or what output to expect. Given the lack of an output schema, this is a moderate gap.

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 does not explain any of the six parameters (chassi, renavam, login_cpf, etc.). Since the schema provides no parameter descriptions, the description fails to compensate, leaving parameter meanings unspecified.

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 that this tool queries traffic fines (Multas) from an official source (DETRAN BA). It is distinct from sibling tools like authenticate or connect, as it specifically addresses fine queries.

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 context by mentioning it is an official, paid service requiring prepaid credits, but it does not explicitly contrast with alternative tools or provide explicit when-to-use/when-not-to-use guidance.

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 reveals numerous non-obvious behaviors: 'invoke works even when the MCP is NOT installed — it runs the tool pontualmente... without adding the MCP to the toolkit,' and that invoke returns connect/checkout links under credential/billing gaps. It also states 'Writes ... require workspace owner/admin.' These go well beyond the annotations (readOnlyHint=false, etc.) without contradicting 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 a single dense paragraph with heavy punctuation, mixing core flow, permissions, billing, and prompt library in one stream. While nearly every sentence adds value, the lack of structure (bullets, sections) makes it harder to parse than necessary for 14 actions. It is comprehensive but not 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 zero required params and no output schema, the description covers the full decision tree: discover→describe→invoke/install, plus list_tools, subscribe/cancel, and prompt library operations. It covers auth requirements, billing exceptions, and installed-state reporting. Minor omissions like the default action='search' and the format of the `arguments` parameter don't undermine the overall 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?

With 23 params and 0% schema description coverage, the description compensates by explaining the central action parameter and the workflow around it (e.g., 'describe returns one MCP's full profile (every tool with its id + params, pricing, auth) so you pick the right tool_id → invoke RUNS that tool'). It also clarifies prompt-related actions. However, many parameters (limit, immediate, tier_slug, cancel_reason, etc.) are left to inference from names, so the compensation 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 identifies the tool as the official mcp.ai marketplace and runner: 'in-platform catalog of every MCP/tool, AND the way to run them.' It distinguishes itself from sibling tools like toolkit_info by enumerating its search/describe/invoke/install capabilities. The verb is specific (catalog + run) and the scope is defined.

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 flow guidance: 'action=search discovers MCPs by intent → describe returns one MCP's full profile... → invoke RUNS that tool.' It explicitly contrasts invoke vs install ('Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use'), and lists what each subscription/reporting/request action is for. This is textbook when-to-use guidance.

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 convey readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds reproduction-related context but does not disclose what happens after submission, whether reports are persisted, or any rate limits. No contradiction with annotations exists.

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-loads the core purpose, and provides a key usage hint without any redundant phrasing. Every sentence earns its place.

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 3-parameter reporting tool with no output schema, the description covers purpose and one usage hint, but it omits critical parameter semantics for 'message' and 'context', and the conversation format is ambiguous due to the array/string mismatch. It is minimally adequate but has 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 description coverage is 0%, so the description must compensate for the three parameters. It only explains the 'conversation' parameter, and even then calls it an 'array' while the schema types it as a string. The required 'message' parameter and the 'context' parameter are left unexplained, making correct invocation underspecified.

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 clearly identifies the targets: a bug, missing feature, or feedback. This distinguishes it from unrelated siblings like authenticate, connect, and show_version, and it expands beyond the title 'Report Bug' by covering additional request types.

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 clear context for when to use the tool—when the user wants to report a bug, missing feature, or provide feedback—and provides a practical instruction to include recent conversation messages for reproduction. It does not explicitly state when not to use it, but the sibling tools are not plausible alternatives, so no exclusion is strictly necessary.

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, providing the safety profile. The description adds the behavioral detail that it returns both MCP platform and adapter versions. No contradictions with annotations. The description complements the annotations rather than repeating 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 a single clear sentence, efficiently conveying the tool's purpose without extraneous detail. It is appropriately front-loaded and contains no 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?

Given the tool's simplicity (no parameters, no output schema), the description fully covers what the agent needs: what the tool does and what information it provides. The annotations cover the behavioral traits, so nothing is missing.

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 0 parameters, so there is no need for parameter documentation. The description already specifies what information is shown. Schema description coverage is 100% (vacuously), and the description adds meaningful context about what the tool outputs, so a baseline of 4 is appropriate.

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: showing the current MCP platform and adapter versions. It uses a specific verb ('Show') and resource ('platform and adapter versions'), effectively distinguishing its purpose. Even without siblings with similar names, it unambiguously communicates what the 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 implies usage: call it when you need to know current version information. It does not explicitly mention alternatives or when not to use it, but given it's a simple informational tool, the context is clear. There are no siblings with overlapping functionality, so no exclusions are necessary.

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 agent knows it is a safe read-only operation. The description adds meaningful behavioral detail by specifying exactly what state is returned, which goes beyond the generic annotation hints.

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 verb and resource ('Returns the current toolkit state') and then elaborates with four concrete data categories. 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?

Given that the tool has no parameters, no output schema, and the annotations cover safety, the description is fully complete. It tells the agent exactly what to expect in the response (installed MCPs, connection status, accounts, catalog tool counts), leaving no ambiguity.

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 there is no parameter burden on the description. The description fully explains the tool's return content without needing to compensate for undocumented parameters. A baseline score of 4 is appropriate for a zero-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 starts with a specific verb ('Returns') and clearly identifies the resource ('current toolkit state'), then enumerates the specific data points returned (installed MCPs, connection status, accounts, catalog tool counts). This fully distinguishes it from siblings like authenticate 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 clearly implies the tool is for checking current toolkit state, providing enough context for an agent to know when to invoke it. It does not explicitly mention alternatives or exclusion scenarios, but none are needed given the unique purpose.

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