DETRAN CE: Emissão de Taxa de Multas (Antiga)

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

The description is transparent about side effects: it may open a browser, it implies a state change (authentication). It clearly states the token is non-expiring when set in config vs. session-only when passed as an argument. However, it doesn't mention rate limits or side effects on subsequent calls, but given annotations already mark it as idempotent and non-destructive, the description adds good 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?

The description is compact and informative, packing a lot of information into two sentences. It uses abbreviations and parentheticals effectively. It could be slightly restructured for clarity, but it's quite 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?

The description covers the main use cases and alternatives well. It could mention what happens after a successful login (e.g., 'you are now authenticated for the session') or if there are any post-conditions, but it's not strictly necessary. The description is nearly complete for an authentication 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 parameter `token` is not described in the schema, but the description explains its semantics well: 'call with { token: "<jwt>" } after the user pastes'. This directly compensates for the 0% schema coverage. However, it's not entirely comprehensive about edge cases, but it's sufficient.

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: to authenticate by logging in via browser and copying an access token. It also explains the two modes (session-only vs. permanent via config). However, it could more explicitly say 'authenticates the user' as its primary function, though it's strongly implied.

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 tells when to use this tool (for IDE agents like Cursor) and precisely how to use it in each scenario (with no args, with token, or via config header). It even mentions an alternative (adding to config) for a permanent connection, which differentiates the usage.

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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which the description aligns with. The description adds behavioral context about the shape of the response (authenticated flag, pending[], connect_url) that goes beyond the annotations. This is a getter that says what it returns. A 3 is appropriate because the description is helpful for a read operation but doesn't go into edge behaviors (e.g., partial connection states, what providers means specifically), though the conditional logic with missing credentials is a plus. It's not 4-level rich but it's adequate and additive.

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 focused sentences. The first defines the tool's purpose, the second explains the branching behavior based on connection state. Every word earns its place. It's front-loaded with the most critical info (what it returns) and exactly as long as needed.

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 zero-parameter, read-only tool with rich annotations (safe, idempotent, read-only), the description is largely complete. It covers the main response fields and conditional logic. It would benefit from mentioning which providers are checked or an example output, but this description provides enough clarity without over-explaining. The annotations already encode the safety profile, so nothing more is needed there.

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 takes 0 parameters, so there's no parameter schema to clarify. Per rubric, 0 params = baseline 4. The description adds value by detailing what the response conveys (authenticated, pending[], connect_url), compensating for a lack of structured field documentation.

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 a specific verb (returns) and resource (connection status). It distinguishes itself from siblings by explaining the exact scenarios: when all providers are connected (authenticated:true, empty pending[]) and when credentials are missing (returns connect_url). This is not a tautology and provides concrete detail beyond the name.

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 in connection-status checking scenarios, and explicitly differentiates from siblings like 'authenticate' (which presumably handles the actual auth) by mentioning 'when credentials are missing, returns connect_url.' However, it doesn't explicitly say 'use this instead of authenticate when checking connection state' or provide exclusion criteria. Clear context, but no formal when/when-not structure.

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 read-only annotation, it adds that data is non-confidential and sourced officially, enhancing transparency about data handling and compliance.

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 well-structured, covering purpose, hosting, and legal aspects without unnecessary verbosity.

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 context about the query and legal disclaimers but omits return format and detailed parameter explanations, leaving some gaps for a complete understanding.

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 the meaning of 'ait', 'placa', or 'renavam', and the schema has no property descriptions, leaving parameters ambiguous.

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 fine fee information from an official source, distinguishing it from sibling tools like authentication 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?

It mentions payment and hosting details but does not specify when to use this tool versus alternatives, lacking explicit usage 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?

Goes far beyond annotations by disclosing invoke's one-off execution behavior, connect/checkout link returns, permission requirements for writes, installed status flags, and prompt library link sharing. No contradiction with annotations; adds critical operational 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?

The description is long but every sentence earns its place: it defines scope, explains the core flow, highlights key edge cases, then covers permissions and the prompt library. Logical structure with front-loaded core 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?

Complete for a 23-param, 14-action tool: covers discovery, invocation, installation, billing, permissions, prompts, and error handling (connect/checkout links). Since there is no output schema, the description compensates by explaining expected returns for main flows.

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 compensates by explaining core parameters like action, mcp_id, tool_id, and prompt fields. However, many schema fields (limit, immediate, tier_slug, cancel_reason, etc.) remain undocumented, leaving some gaps for advanced actions.

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 marketplace as the official mcp.ai catalog and execution platform, with an explicit core flow (search → describe → invoke). It distinguishes itself from sibling tools by covering both discovery and invocation, a unique scope among alternatives like authenticate and 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?

Provides explicit guidance on when to use invoke vs install, distinguishes list_tools, subscribe/cancel, report_bug, and request_mcp, and explains when to use search vs describe. It also clarifies the prompt library actions, making it easy to choose the right operation.

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 signal readOnly=false, idempotent=true, and destructive=false. The description adds the behavioral detail that conversation data is needed for reproduction, but it does not describe what happens after submission (e.g., where the report goes, whether a ticket is created). This still carries some value beyond the annotations, so a score of 3 is appropriate.

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 short sentences, front-loaded with the purpose, and each sentence delivers key information without unnecessary words or repetition. This is an ideal length for the tool's simplicity.

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 (3 params, 1 required, no output schema), and the description covers the purpose and an important usage hint. However, it omits the required 'message' parameter and the optional 'context' parameter. With zero schema description coverage, this leaves the description useful but not fully 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?

Schema description coverage is 0%, so the description must compensate. It says to 'include the conversation array', which maps to the 'conversation' parameter, but it does not explain the 'message' parameter (the only required one) or the 'context' parameter. It also omits that 'conversation' is a JSON string, despite calling it an array.

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 action: 'Report a bug, missing feature, or send feedback.' This clearly identifies the tool's purpose and distinguishes it from sibling tools like authenticate, marketplace, and detran_ce_multas_antiga_consultar, which serve entirely different functions.

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 instruction 'Include the conversation array with recent messages for reproduction' gives concrete usage guidance for one parameter. It does not explicitly say 'when to use this vs alternatives', but no sibling tool overlaps with bug reporting, so the context is clear enough.

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, which fully cover the safety profile. The description adds no extra behavioral context beyond the resource type, but for a simple read-only version query, this is acceptable and not misleading.

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 exactly what the tool does without any filler. Every word 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?

This is a trivial, zero-parameter, read-only tool. The description fully captures its purpose and no output schema is needed. Nothing important 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 tool has zero parameters, and the schema is empty (coverage 100%). With no parameters to document, the description is not expected to add anything beyond this, so the baseline of 4 applies.

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 'Show' with a clear resource: 'current MCP platform and adapter versions.' This is distinct from sibling tools like authenticate or marketplace, so there is little ambiguity about 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 context is clear: this is for retrieving version information. There are no explicit exclusions or alternatives, but the tool is so focused that none are necessary. It's obvious when to use it versus the other available 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, idempotent, non-destructive behavior. The description adds context about what the tool returns (MCPs, connection status, accounts, catalog counts) without contradicting the annotations. This adds value without overexplaining.

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 one concise sentence that front-loads the verb and resource, then lists concrete details. No filler, redundancy, or vague terms.

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 zero-parameter read-only introspection tool with no output schema, the description provides all the necessary context: what is returned and in what structural categories. There is nothing missing that an agent would need to invoke it 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 takes zero parameters, so there is no parameter documentation burden on the description. The input schema fully covers this (100% coverage, no properties), making a baseline of 4 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 uses a specific verb ('Returns') and clearly identifies the resource ('current toolkit state') and enumerates the key contents (installed MCPs, connection status, accounts, catalog tool count). It clearly distinguishes from sibling tools by focusing on introspection rather than authentication or marketplace 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 tool is for checking toolkit state and is distinct from action-oriented siblings like authenticate, connect, and marketplace. However, it does not explicitly state when to use it over alternatives or mention any exclusions.

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