DETRAN DF: Débitos

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

The description transparently explains side effects: initiating a browser login, accepting a token, or returning a link. It mentions the permanent non-expiring config option and acknowledges session-only behavior. Annotations (idempotent, non-destructive) align with the description, and no contradiction exists. The description adds valuable behavioral detail beyond the schema.

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 moderately concise and front-loaded with the core purpose. It's structured into two usage modes, which is helpful. However, it includes some redundant phrasing (e.g., 'log in in the browser' vs. 'user pastes') that could be trimmed without losing clarity. Still, every sentence adds practical 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 description covers the essential flows (browser auth, token-based login, permanent config) but does not mention return values or session expiration. Given there is no output schema, the agent would benefit from knowing what to expect (e.g., a URL or success message). Slightly incomplete but adequate for a single-parameter auth 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?

With 0% schema description coveragechers the schema only defines 'token' as a string. The description fully compensates: it explains the token is a JWT to be pasted for session-only login, and that omitting arguments yields a login link. This is a complete semantic explanation of the parameter and its optionality.

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: authenticate an IDE agent to MCP.AI. It specifies the resource (MCP.AI) and the action (log in, obtain token, configure). It distinguishes itself by detailing the browser login flow and two methods (permanent header config vs. session token), making its function unambiguous relative to generic sibling names like '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?

It provides explicit usage patterns: can be called with a token for session-only login or with no args to get a login link. It also recommends the permanent header approach. However, it does not explicitly contrast with the sibling 'connect' or state when NOT to use this tool, so slightly below full marks.

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 readOnly, idempotent, non-destructive behavior. The description adds valuable context about state-dependent responses (authenticated:true with empty pending[] vs connect_urls when credentials missing), which is not captured by annotations and aids the agent in understanding expected outputs.

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 primary purpose, and every phrase adds value. It efficiently covers both the happy path and the missing-credentials scenario without 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 no output schema, the description explains the return values for both connection states, making it sufficiently complete for an agent to understand what this tool will do. It covers the key scenarios and does not leave critical 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?

The tool has zero parameters, so the baseline is 4. The description does not need to elaborate on parameter semantics, and it adds meaningful context about return values instead, which 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 'Returns connection status and URLs', a specific verb+resource that distinguishes this tool from siblings like 'authenticate' by focusing on status rather than action. It also explains the two major outcomes (authenticated vs missing credentials), making the purpose unambiguous.

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: use this to check if all providers are connected and retrieve URLs when credentials are missing. It implies the use case but does not explicitly contrast with the 'authenticate' sibling tool 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?

Annotations already indicate read-only, idempotent, non-destructive. Description adds that it is paid via pre-paid credits Hierarchical, and clarifies data custody and LGPD responsibilities, which are extra behavioral/contextual cues. However, it doesn't detail authentication specifics (like needing certain credentials) or potential errors, but given existing annotations, a 3 is fair.

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?

Description is a single, dense paragraph but concise (~400 characters) and front-loads the primary purpose. It includes necessary compliance and hosting issues. Each sentence has purpose: purpose, hosting/platform context, data source explanation, LGPD warning. No fluff.

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?

Complexity is moderate (6 params, of which 4 optional auth-related). Output schema missing, so description should cover expected return. It does not explain return format or error handling. But given annotations (read-only, idempotent), and that it's a standard query tool, the description is fairly complete for a casual user; yet it lacks param details. Thus a 3.

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 description must compensate. The description lists only hints that 'placa' and 'renavam' are likely vehicle identifiers but doesn't explain optional parameters like login_cpf, senha, or certificates. It does state the tool uses official source and payment, but that's not about parameter semantics. With zero schema coverage service, the description falls short of giving meaningful parameter guidance, earning a 3.

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 debts/charges from DETRAN DF, an official Brazilian source (verb 'consultar' = consult, resource='débitos' = debts). It distinguishes itself from siblings by specifying the official DETRAN DF scopeasia, but does not explicitly compare to other sibling tools, yielding a slight deduction.

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 implicitly tells when to use: for consulting debts from official Brazilian sources, with a note that it is not confidential data. It does not explicitly state when NOT to use or name alternative tools, but the context (official source) illuminates appropriate use. Sibling tools are mostly support/misc, so it's clear this is a data lookup.

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 adds rich behavioral detail beyond the annotations: it discloses side effects (install makes an MCP permanent; invoke may return connect/checkout links), permission requirements (writes require owner/admin), and the prompt library's non-login share behavior. It does not contradict 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 long but dense and front-loaded with the core flow; each sentence carries information about a distinct action or behavior. It could be better structured with bullets, but it earns its length for a 14-action 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's complexity and absence of an output schema, the description covers the main flows and return behaviors, including invoke's auth/payment links and the prompt library. Some actions (search, subscribe/cancel) receive less detail, but overall it is sufficiently complete for an agent to invoke 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 schema has 0% description coverage for its 23 parameters, and the description compensates for the key ones by explaining the action-dependent workflow—e.g., 'describe returns one MCP's full profile ... you pick the right tool_id → invoke RUNS that tool'. It explains prompt_vars, prompt_slug, and tool_id semantics, though some params like immediate and tier_slug remain implicit.

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 execution engine, with specific verbs: 'search', 'describe', 'invoke', 'install', etc. It distinguishes from siblings by explaining its unique role as a catalog/runner, and even contrasts report_bug and request_mcp as alternative 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?

It provides explicit decision guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT', and explains when to use search/describe. It also lists alternative actions for other intents (request_mcp, report_bug, subscribe/cancel), making when-to-use clear.

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 indicate readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description does not contradict these, but it adds minimal behavioral context: it mentions the action of reporting, which aligns with non-destructive, idempotent behavior. It doesn't disclose any side effects, rate limits, or what happens after reporting, so it adds some value but not much 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 short: one sentence that efficiently communicates the tool's main purpose and a key usage tip (include conversation). It is front-loaded with the action verb 'Report' and the object. No fluff, but it could be more structured if it listed parameters, hence not a 5.

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 medium complexity (3 params, no output schema, minimal annotations), the description is incomplete. It lacks parameter semantics, expected input formats (e.g., how to structure the conversation array), and any details about the response. The user/agent is left with insufficient guidance for correct invocation, especially since schema coverage is 0%. It covers basic purpose but not operational details.

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%, meaning the description provides no parameter documentation. The description mentions 'conversation array' but does not explain the other parameters (context, message) beyond what their names imply. With three parameters and zero coverage, the description must compensate but fails, leaving the agent to guess the purpose and format of 'context' and how 'conversation' should be structured (JSON string?).

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 purpose: to report a bug, missing feature, or send feedback. It identifies the primary resource (the system being used) and the action (report/send). While it distinguishes this from sibling tools (which are mostly unrelated operational tools), it doesn't explicitly name alternatives, so it's not a 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 implies usage: when the user wants to report a bug or provide feedback. It gives a key hint about including the conversation for reproduction, which is important context. However, it doesn't explicitly say when NOT to use it or mention alternatives (e.g., for feature requests, use marketplace?), leaving some ambiguity. This is adequate but not explicit.

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 idempotentHint=true, so the safety profile is covered. The description adds that it shows platform and adapter versions, but doesn't disclose any additional behavioral traits like network calls or potential errors. It doesn't contradict annotations, but doesn't add much 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?

Single sentence, front-loaded, no filler. Exactly as concise 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 version info tool with no params and clear annotations, the description is sufficient. It states what it does. It doesn't specify output format, but that's minor.

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 0 parametershola, so baseline is 4. The description doesn't need to add parameter semantics because there are none.

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 action (show) and the resource (current MCP platform and adapter versions). It is specific and distinguishes this tool from siblings like connect or authenticate, which serve entirely different purposes.

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. It doesn't mention when it's appropriate to call, nor does it exclude any situations. There is no mention of prerequisites or exclusions, leaving the agent without usage context beyond the name.

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 readOnly, idempotent, and non-destructive behavior. The description adds transparency about what data is returned (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the annotation metadata.

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 leads with the action and quickly enumerates the key return items within the same sentence. Every word contributes value with no repetition 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 zero-parameter introspection tool with strong annotations, this description is fully adequate for an agent to understand what the tool returns and why it might be invoked. The absence of an output schema is offset by the plain-language enumeration of returned data categories.

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 description coverage is 100% by default, so parameter semantics are not a burden on the description. The baseline for 0-parameter tools is 4, and the description does nothing to detract from that.

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 it 'Returns the current toolkit state' and enumerates the specific contents: installed MCPs, connection status, connected accounts, and count of exposed catalog tools. This specific verb+resource combination clearly distinguishes it from the sibling tools like show_version 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 makes it evident that this tool is for obtaining an overview of the toolkit's current status, which implies use for checking connections or state before taking actions. But it does not explicitly state when-not-to-use or mention alternatives among the siblings.

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