ECRVSP Veículos: Número de Motor na BIN

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

Annotations only state idempotentHint=true and destructiveHint=false. The description adds that calling with no args returns a link, and calling with a token performs a session login. It also clarifies the token is a JWT and distinguishes session-only vs permanent (via config). 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, but it packs a lot of information: platform context, two usage modes, and a recommended permanent solution. It is front-loaded with the login purpose. No wasted words, though the sentence structure is a bit run-on. Still efficiently informative.

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 (one optional param, no output schema), the description covers the essential behavior: how to trigger a link, how to pass a token, and that there's a permanent alternative. It doesn't explicitly state the return value or error cases, but for an authentication step this is adequate. No output schema means the burden is on description, and it delivers enough for usage.

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 a single optional 'token' parameter with no description (coverage 0%). The description fully explains the token: it should be a JWT pasted by the user, and calling with it enables session-only login. It also clarifies that omitting the token yields a login link. This compensates entirely 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's purpose: to authenticate the user by providing a login link or accepting an access token. It names the resource (MCP.AI for IDE agents) and specifies the verb (log in, authenticate). This distinguishes it from siblings like connect or marketplace, which likely serve 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?

It explains when to use the tool (to authenticate) and provides two concrete usage modes: with a token for session login, or without arguments to retrieve a login link. It also suggests a better long-term alternative (config header) but that is external to the tool, not an alternative tool. It doesn't explicitly mention when not to use it or compare to siblings, but the context is clear enough for a single-purpose auth tool.

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 a safe read-only, idempotent operation. The description adds value by describing the conditional output based on connection status (authenticated:true with empty pending[], or connect_url for toolkit and per-install). It does not contradict 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 concise, using two sentences that immediately convey the tool's purpose and the two key scenarios. No filler 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?

For a simple status tool with no output schema, the description covers the essential return behaviors: the all-connected case and the missing-credentials case. It accurately reflects the likely use case and provides sufficient context for an agent to interpret results.

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 for this dimension is 4. The description adds no parameter semantics but explains the return values meaningfully, which is sufficient given the absence of 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 returns connection status and URLs, with specific response behavior (authenticated:true vs connect_url). It distinguishes itself from the sibling 'authenticate' tool by focusing on status rather than performing 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 if all providers are connected or to obtain connection URLs when credentials are missing. However, it does not explicitly name alternatives or state when NOT to use it, though the interplay with 'authenticate' 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?

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds context about payment per query and LGPD compliance, which is useful. However, it does not detail side effects, rate limits, or other behavioral aspects beyond what annotations provide.

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 verbose and repetitive, repeating phrases like 'consulta em fonte oficial' and 'informação de fontes e órgãos oficiais brasileiros' and 'não é dado sigiloso'. It could be more concise and better structured, but it does provide some context.

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 complexity (multiple parameters, authentication, payment), the description lacks essential details such as how to provide credentials, what the output format will be, or how the query is executed. It is incomplete for a user to confidently invoke 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?

The schema provides no descriptions for parameters, and the description does not explain the meaning or usage of parameters like 'a3', 'a3_pin', 'login_cpf', 'login_senha', 'motor', 'placa', 'chassi'. The description only hints at credentials (login) and vehicle fields but leaves most parameter semantics unclear.

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 is a query ('consulta') for vehicle information (vehicles) related to engine number (motor), and mentions official sources. However, it is somewhat cryptic with 'BIN' and the exact purpose could be more explicit, but overall it conveys a read-only query action.

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 does not provide guidance on when to use this tool versus alternatives. It mentions payment and lack of platform credentials, but does not specify scenarios or compare with other tools. No explicit usage instructions or limitations are given.

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=false, openWorld=true, idempotent=false, and the description adds valuable behavioral context: invoke runs uninstalled MCPs one-off without bloating the toolkit, auth/payment gaps produce connect/checkout links, writes require workspace owner/admin, and search/describe flag installation status. No contradiction with 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 densely packed and front-loaded with the core discovery → describe → invoke flow, then systematically covers conditional behavior, permissions, billing, and the prompt library. Every sentence adds useful information, and the emphasis markers help an agent scan the key points quickly.

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 (14 actions, no output schema, 23 optional params), the description is remarkably complete: it covers main flows, auth/billing edge cases, permission requirements, and prompt-library behavior. Minor gaps remain, such as the `resume` action being absent from the description and some secondary parameters like `immediate` and `tier_slug` not being clarified.

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 gives real meaning to the central `action` parameter and explains key workflow parameters like tool_id, mcp_id, prompt_vars, and prompt_slug. However, with 23 optional parameters and 0% schema description coverage, several parameters such as query, limit, arguments, immediate, tier_slug, and conversation are left largely to the schema/defaults rather than being explained in prose.

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 hub, with concrete verbs and resources: search/describe/invoke MCPs, install/uninstall, billing actions, and prompt-library actions. It distinguishes itself from sibling utilities by defining the marketplace domain and the 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?

The description gives explicit guidance on when to use invoke vs install ('prefer invoke for a single/occasional use'; 'use install only to make an MCP PERMANENT'), when to use list_tools, when to use request_mcp, and how prompt-library actions differ from MCP actions. This level of alternative/comparison guidance is exemplary.

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 provide idempotentHint=true and destructiveHint=false. The description adds behavioral guidance by instructing the caller to include the conversation array for reproduction. However, it doesn't disclose what happens after reporting (e.g., report creation, notification side effects) or what the response looks like.

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 conveys the purpose and a critical usage detail. Every word earns its place with no 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?

For a simple reporting tool with no output schema and sufficient annotations, the description is mostly complete. It explains the purpose and gives one actionable instruction, but the lack of guidance on the required 'message' parameter is a minor 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?

Schema description coverage is 0%, so the description must compensate. It explains the purpose of the 'conversation' parameter but ignores 'message' (the required parameter) and 'context'. This leaves the most important parameter semantically 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 function with a specific verb ('report') and resource ('a bug, missing feature, or send feedback'). It distinguishes itself from sibling tools like authenticate or marketplace, which serve unrelated 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 clear context for when to use the tool (bug reporting, feature requests, feedback) and includes an important instruction about the conversation array. It doesn't explicitly mention alternatives or exclusions, but sibling tools are obviously unrelated, so this is not a significant gap.

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 the main behavioral safety profile. The description adds no extra behavioral details (e.g., network access, caching), but does not contradict annotations. With annotations present, a 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 a single sentence, front-loaded with the verb 'show' and the resource 'MCP platform and adapter versions'. No waste, perfectly 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?

For a simple version-info tool with no parameters and a clear purpose, the description is sufficient. The output is not detailed, but the absence of an output schema means the description should ideally specify what the output includes (e.g., format), but given the simplicity and existing annotations, it is mostly 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?

The tool has zero parameters, so there is nothing to document in the schema. The description's lack of parameter info is not a gap; no additional semantics are needed. A baseline of 4 is appropriate for no-parameter tools.

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 shows the current MCP platform and adapter versions, which is specific and distinct from siblings like authenticate or connect. It could be slightly more detailed but effectively communicates its 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 implies usage for checking versions, but does not explicitly state when to use it vs alternatives or provide context like 'use this to verify environment setup'. It is adequate but lacks explicit 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 provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful behavioral context by specifying exactly what information is returned (installed MCPs, connection status, accounts, tool counts), going beyond the annotation-only safety profile.

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 well-structured sentence with a colon-led list; every element adds information and no words are wasted. It is immediately readable and front-loaded.

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, so the description must convey return values, and it does so at a useful category level. It omits formatting/status-value details, but for a simple no-parameter introspection tool the description is sufficiently 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?

The tool has zero parameters, so schema coverage is trivially 100% and there are no parameter semantics to clarify. The baseline of 4 applies because no parameter documentation burden exists.

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 identifies the exact resource ('current toolkit state'), then enumerates what that includes: installed MCPs, connection status, accounts, and catalog tool counts. This clearly distinguishes it from siblings 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 the tool's context obvious: use it when you need current toolkit state or connection/account information. It does not explicitly mention when not to use it or name alternatives, but for a read-only status tool this is acceptable.

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