DETRAN AL: Licenciamento

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

Annotations already indicate idempotent and non-destructive behavior. The description adds useful context: config-header login is permanent/non-expiring, pasted-token login is session-only, and no-args returns the auth link. No contradiction 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?

Three sentences, front-loaded with the tool's purpose, followed by clear mode alternatives. Every sentence contributes useful information with 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?

For a simple one-optional-parameter auth tool with no output schema, the description covers the login flow, token usage, and no-args behavior. It omits response/error details, but the core invocation guidance is 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%, but the description fully explains the only parameter: token is a JWT used for session-only login, and omitting it returns the auth link. This fully compensates for the schema 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 clearly states the tool authenticates to MCP.AI via browser login and token handling. It identifies the tool's function well, though it does not explicitly differentiate it from the sibling 'connect' 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 gives explicit usage modes: add the token to server config for a permanent connection, or paste it for a session-only login. It also explains when to call with no args to get the link, but does not mention when to prefer this over sibling 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 already declare readOnlyHint, idempotentHint, and destructiveHint as safe, so the description adds value by explaining the two output conditions: authenticated:true with empty pending[] when connected, versus connect_url and per-install URLs when credentials are missing. This goes beyond the annotations 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 two sentences, front-loaded with the primary purpose ('Returns connection status and URLs'), and every clause adds meaningful detail about expected states and return values. No wasted words.

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 status tool with rich annotations, the description covers the main output scenarios well. It could be slightly more complete by defining the middle/partial state or explicitly contrasting with authenticate, but it is adequate for invocation.

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 there is no parameter semantics burden. A baseline of 4 is appropriate because the description correctly focuses on behavior rather than inventing 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 clearly states the tool's function: 'Returns connection status and URLs.' It also distinguishes behavioral outcomes by provider connectivity state, making the tool's scope specific and useful relative to siblings like authenticate.

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 this tool is relevant—checking connection status and obtaining URLs when credentials are missing. It does not explicitly name alternatives or exclusions, but the conditional states imply its role as a status/readiness check.

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 and idempotent behavior. The description adds transparency about payment (prepaid credit), hosting, lack of platform credentials, and LGPD data controller responsibilities, which are useful beyond the annotations and do not contradict 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 concise, front-loads the core purpose, and keeps sentences short. It includes some extra legal context that is not essential for tool selection but does not bloat the description excessively.

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?

There is no output schema and the description omits details about expected result format, parameter semantics, or error conditions. It provides general context about official sources and payment but is insufficient for an agent to confidently invoke the tool without prior domain knowledge.

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% and the description does not explain the parameters 'placa' or 'renavam' — no formats, examples, or meaning. The description fails to compensate for the missing schema 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 clearly states it consults licensing information from DETRAN AL, using specific verbs ('consulta') and resource ('Licenciamento'), and distinguishes from sibling tools which are about authentication, marketplaces, or bug reporting.

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 DETRAN AL licensing queries but does not explicitly state when to use it versus alternatives, nor any exclusions. It mentions payment and official source, which are contextual but not direct usage 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 discloses non-obvious behaviors: writes require workspace owner/admin, invoke returns connect/checkout links when credentials or payment are missing, and invoke performs a one-off install without bloating the toolkit. These details go well beyond the sparse annotations (readOnlyHint=false, openWorldHint=true) and materially shape agent expectations.

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 that is information-rich but not easily scannable. Every clause adds distinct value (permissions, pricing, prompt library), so it earns its length, but better structural separation would improve readability and agent parsing.

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 full scope: core search/describe/invoke flow, install vs invoke semantics, billing and auth handling, workspace permission requirements, and the secondary prompt library. It also specifies outputs for key actions (describe, invoke, publish_prompt), making it complete for an agent to decide and call 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?

With 0% schema description coverage, the description compensates by explaining many key parameters: action values (search, describe, install, invoke, etc.) and their roles, plus mcp_id, tool_id, arguments, prompt vars. However, several parameters like limit, immediate, tier_slug, conversation, and cancel_reason are left unexplained, so the 23-parameter surface is not fully covered.

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 'the in-platform catalog of every MCP/tool, AND the way to run them', which is a specific verb+resource. It differentiates itself from sibling tools by positioning itself as the central discovery/execution hub, covering capability requests and the full search→describe→invoke 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?

Explicit guidance is given: 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use' and the core flow is spelled out. It also distinguishes when to use subscribe/cancel, report_bug, request_mcp, and the prompt library actions, giving a clear decision tree.

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=false and destructiveHint=false, so the tool's non-read-only, non-destructive nature is known. The description adds that conversation data is used for reproduction, but does not disclose what happens after submission (e.g., whether a report is actually created, confirmation behavior). No contradiction 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 two sentences with the primary purpose front-loaded. The second sentence adds a useful reproduction hint, and there is no filler or 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?

The tool is relatively simple (3 flat params, no output schema), and the description covers purpose and one key usage detail. However, it omits any indication of the result/response of reporting and does not explain the `context` parameter, leaving minor gaps for a tool of this complexity.

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 parameter clarity. It explains `conversation` (array with recent messages for reproduction) and implies `message` via the reporting purpose, but leaves `context` entirely undocumented.

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 action: 'Report a bug, missing feature, or send feedback.' It uses a specific verb and resource, and it is distinct from the sibling tools, which handle authentication, marketplace, or 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 establishes clear usage context by naming the scenarios (bug, missing feature, feedback) and instructs the user to include the conversation array for reproduction. It does not explicitly exclude alternatives, but since no sibling tool handles feedback, this is clearly sufficient.

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 read-only, idempotent, and non-destructive, so the description does not need to repeat those. It adds the useful detail that versions are 'current' and derived from the MCP platform and adapter, but it does not describe output format or possible error behavior.

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, direct sentence with no filler or redundant detail. It captures the tool's full purpose without forcing the agent to parse 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?

For a zero-parameter diagnostic version tool, the description is sufficiently complete: it identifies what is shown, the current MCP platform and adapter versions. There is no output schema, but the expected output is straightforward enough that the description is not misleading.

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 zero parameters and 100% schema coverage, so there are no parameter semantics to document. The no-parameter baseline of 4 applies because the description accurately aligns with an empty invocation.

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 clear verb ('Show') and identifies a specific resource: 'current MCP platform and adapter versions.' This is enough to distinguish it from sibling tools like toolkit_info, which is broader in scope.

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 retrieving version information during diagnostics or compatibility checks, but it does not explicitly state when to use it over alternatives or provide any exclusions. Usage context is reasonable 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, idempotentHint, and destructiveHint, so safety is covered. The description adds behavioral context by detailing what information is returned (installed MCPs, connection status, accounts, tool counts), which goes beyond annotations but doesn't address auth or rate limits. Given the simple read-only nature, this is sufficient.

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 with no unnecessary words. It efficiently lists the exact components of the returned state, earning 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?

For a no-parameter, read-only introspection tool, the description fully explains what the tool returns and its purpose. Annotations cover safety, and no output schema is needed. The description is complete and self-sufficient.

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 zero parameters, and the baseline for 0 params is 4. The description correctly omits parameter details, and no additional meaning is needed beyond the empty 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 returns toolkit state with specific components (installed MCPs, connection status, accounts, catalog tool counts). It uses a specific verb 'Returns' and a resource, distinguishing it from siblings like 'authenticate' or 'show_version'.

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 inspecting toolkit state but does not explicitly state when to use it versus alternatives or provide exclusionary guidance. It gives a clear context but lacks explicit when/when-not instructions.

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