Veículo

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

The description adds behavioral context beyond annotations: it explains that calling with no args returns a link, while passing a token enables session login. It also mentions the option of permanent non-expiring connection via config, which is a side effect or external step. Annotations mark idempotent and non-destructive, which align with the description. It doesn't contradict annotations and provides meaningful user-flow details.

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 sentence with a colon, but it packs substantial information: primary purpose, two usage modes, and token type. It is front-loaded with the main verb and context. It's slightly dense but efficient, covering necessary details without fluff. Could be broken into clearer sections, but it's not overly verbose.

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 tool with one optional parameter and no output schema, the description covers the essential scenarios: getting a link with no args, session login with token, and recommendation for permanent config. It doesn't describe the exact output format (e.g., is the link a URL?), but given simplicity and lack of output schema, the description is sufficiently complete. It also aligns with annotations for safety.

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 only defines an optional 'token' string with no description coverage (0%). The description compensates by explaining 'token' is a JWT and shows how to pass it ({ token: '<jwt>' }) and when not to pass it (no args for link). This adds significant meaning beyond the schema, though it could explicitly state the token is a JWT in the schema description. Overall, it covers the parameter's purpose and usage.

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 MCP.AI for IDE agents. It specifies the workflow (log in via browser, copy access token) and distinguishes it from potential siblings by naming the specific use case (IDE agents like Cursor). The verb+resource is explicit: authenticate with token or get link.

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 usage guidelines for two modes: permanent configuration (adding token to server config) and session-only (passing token or no args to get link). It explains when to use each variant, though it does not explicitly mention alternatives like 'connect' or conditions for not using it. The guidance is actionable but lacks explicit when-not-to-use versus 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 readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds valuable behavioral detail by specifying the exact return states: authenticated:true with empty pending[] when connected, and connect_url plus per-install URLs when credentials are missing.

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 main purpose, and every sentence adds meaningful conditional behavior. 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?

With no parameters and no output schema, the description carries the full burden of explaining return values. It covers both primary states (all connected vs. missing credentials) and is complete for a simple status-checking 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 the baseline is 4. The description does not need to explain parameter semantics; it appropriately focuses on output behavior instead.

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 and resource. It differentiates from siblings like authenticate by focusing on status reporting rather than initiating 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?

The description provides clear context for when to use the tool: to check connection status and retrieve URLs when credentials are missing or all providers are connected. It does not explicitly name alternatives or state when not to use it, but the status-vs-authenticate distinction is implied.

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 many behavioral traits beyond annotations: invoke works without installation, returns connect/checkout links for auth/payment, writes require owner/admin, search/describe flag installation status, and publish_prompt returns a shareable link. These details are not in the annotations, adding significant 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 well-structured, front-loading the core purpose and flow. Each sentence provides relevant detail about workflows, edge cases, and permissions. While verbose, it's appropriately sized given the tool's complexity of 14 actions and 23 parameters.

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 highly complex tool with no output schema and 0% parameter descriptions, the description covers main workflows, auth/payment handling, permissions, and prompt library specifics. It doesn't detail all parameters or return formats, but the core usage is clearly communicated. Some gaps remain (e.g., exact output structures, certain parameter meanings).

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%, so the description must compensate. It explains key parameters like action, mcp_id, tool_id via the workflow, and mentions prompt_vars for variable filling. However, many parameters (limit, immediate, tier_slug, cancel_reason, report_context, etc.) remain unexplained, leaving gaps for a 23-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 clearly states the tool's purpose: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It enumerates specific actions (search, describe, invoke, install, etc.) and distinguishes itself from siblings by being the marketplace for MCPs/tools and 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 gives explicit usage guidance: 'Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile... → invoke RUNS that tool.' It provides when-to-use vs alternatives: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use.' Also differentiates actions like list_tools, subscribe/cancel, report_bug, and prompt library functions.

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 cover the side-effect profile (readOnlyHint=false, destructiveHint=false, idempotentHint=true). The description adds the behavioral context that conversation data is used for reproduction, which is useful but limited. It doesn't disclose what happens after submission (e.g., ticket creation, email) or any failure modes. This is adequate but not rich, given 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 concise sentences. The first sentence front-loads the purpose, the second gives a key usage instruction. No filler or redundant 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?

For a simple tool with 3 parameters and no output schema, the description covers the main purpose and a critical usage tip. It could clarify that 'conversation' is optional (since it has a default) and perhaps describe expected behavior after submission, but overall it provides a viable understanding of how to use 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?

Schema description coverage is 0%, and the description only explicitly explains the 'conversation' parameter as an array for reproduction. The 'message' parameter (required) is implied by the tool's purpose but not described. 'context' is not mentioned. The description partially compensates for the low schema coverage but leaves gaps for two of three parameters.

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 report a bug, missing feature, or send feedback. The verb 'report' combined with the resource 'bug/feature/feedback' is specific and unambiguous. Among sibling tools (authenticate, connect, marketplace, etc.), none handle reporting, so it is well-distinguished.

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 instructs to include the conversation array for reproduction, which is a concrete usage guideline. While it doesn't mention when not to use it, there are no competing alternatives among siblings, and the instruction ties to a key parameter. The guidance is actionable and context-rich.

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 safety profile is well covered. The description adds the useful scope detail that it covers both MCP platform and adapter versions. It is a simple read operation; no further behavioral disclosure is necessary.

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?

One short sentence, front-loaded with the verb 'show', and zero filler words. 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?

For a no-parameter, read-only, idempotent version info tool with strong annotations, the description fully conveys the tool's scope. No output schema is present, but the described output ('versions') is self-explanatory.

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 schema provides all needed information. The description naturally doesn't add parameter-level detail, but baseline 4 is appropriate given the 0-parameter design.

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 'show' and the resource 'current MCP platform and adapter versions'. It is instantly distinguishable from sibling tools like authenticate, connect, 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?

The description implies usage: use when you need to check version information. However, it provides no explicit when-to-use/when-not-to-use guidance or mention of alternative tools, so it's adequate but not richly contextual.

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 this is a safe introspection call. The description adds useful behavioral detail by naming what state is returned, including connection status, accounts per MCP, and catalog tool counts. No contradiction 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?

A single, well-structured sentence front-loads the core purpose and then expands with a colon-delimited list of return components. Every word earns its place; there is no waste.

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 informational tool, the description provides all essential context: what it returns and what categories of data are covered. Annotations confirm safety, and the lack of an explicit output schema is acceptable given the low complexity and clear textual enumeration.

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 schema fully covers parameter semantics. The description enriches the schema by explaining that the output is a toolkit state report rather than a simple boolean or list.

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 a clear resource ('current toolkit state'), then enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This makes its purpose fully distinguishable from sibling tools like authenticate, connect, and 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?

The description makes the usage context clear: call this when you need an overview of the toolkit's current state. It does not explicitly name alternatives or state when not to use it, but the scope is self-evident and no exclusion is needed.

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 safety. The description adds behavioral context: it works for any vehicle and requires no login, which is beyond annotations. It also lists the data categories returned, giving the agent a sense of the output. No contradictions.

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 sentence of about 20 words, front-loaded with the action and resource. It contains no filler or redundant information. Every clause adds value: identifying the method, listing the data fields, and noting accessibility.

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 (2 params, no output schema, strong safety annotations), the description is quite complete. It states purpose, inputs, output categories, and public access. It lacks explicit details on output structure or error handling, but those are not critical for a read-only lookup. Overall, it sufficiently covers the necessary context.

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 two string parameters (placa, renavam) with no descriptions, and schema coverage is 0%. The description mentions 'pela placa + RENAVAM', but this merely restates the parameter names without adding format, examples, or constraints. It does not meaningfully enhance understanding beyond what the schema names already imply.

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 (consulta), the resource (dados de um veículo), and the specific identifiers (placa + RENAVAM). It lists the fields returned (marca/modelo, ano, combustível, situação, restrições) and distinguishes it from sibling tools, which are unrelated (authenticate, marketplace, etc.). This is a specific, unambiguous 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 indicates applicability ('Funciona para qualquer veículo; não exige login'), implying it is a public, universal lookup. It does not explicitly mention alternatives because none exist among the siblings, but the context is clear. There are no exclusions or when-not-to-use scenarios, so a 4 is appropriate.

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