ECRVSP Veículos: Base de Outros Estados

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

Annotations declare idempotentHint=true and readOnlyHint=false. The description adds context about the browser login process and token validity (permanent vs session-only), which is useful. However, it doesn't mention that this is a state-changing operation (auth storage) or any side effects of calling it repeatedly. With annotations covering the idempotency and no contradictions, a 3 is warranted for some extra context but not rich behavioral disclosure.

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. It packs a lot of guidance efficiently, though the second sentence is a bit convoluted with nested conditions. It earns its place with essential usage details.

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 moderate complexity (1 optional param, no output schema), the description covers the use cases, permanent vs session login, and actionable steps. It leaves no major gaps for an agent to decide how to invoke it. Sibling tools are different enough that no confusion arises.

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 describes only 'token' with no description, and coverage is 0%. The description compensates by explaining that token is the JWT to paste for session-only login, and that omitting it yields the login link. This adds meaningful semantics beyond the schema, but the description could be clearer about the token format and expected behavior if invalid. Baseline 3 for partial compensation.

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 this tool handles authentication for MCP.AI in IDE agents, specifying the login flow and token handling. It distinguishes it from siblings like 'connect' by focusing on browser login and token access, though it doesn't explicitly name the alternative.

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 comprehensive usage guidance: when to use (for IDE agents like Cursor), when to use the config vs session login, and how to call with token or no args. It explicitly explains the two login methods and the outcome for each, leaving little ambiguity.

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 and idempotentHint, so no contradiction. The description adds context about response behavior (e.g., authenticated:true, pending[], connect_url), which is useful. However, it does not disclose any potential side effects or deeper behavior beyond what annotations cover.

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, front-loaded with the core purpose, and no fluff. Every sentence adds 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 tool is simple with no parameters and no output schema, but the description adequately explains the return scenarios. It could mention that no parameters are needed, but that is inferred. Given the complexity, it is complete enough.

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 is complete. The description focuses on output behavior rather than parameters, which is appropriate. Since there are no parameters, the description doesn't need to add parameter semantics, but it could have explained return structure more; baseline 3 is fair.

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, identifying the specific resource (connection status). It distinguishes from siblings like authenticate and marketplace by focusing on status retrieval, but does not explicitly name alternatives.

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 when to use it: to check connection status and get URLs when credentials are missing. It does not explicitly state when not to use it or mention alternatives, but the context is clear that this is for status checking, not authentication.

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 the description is consistent with. Beyond that, the description adds critical behavioral traits: it requires payment per query (pre-paid credits), uses its own credentials (a3, a3_pin, login_cpf, login_senha) instead of platform credentials, and notes LGPD compliance responsibilities. This goes beyond annotations and is valuable for the agent.

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, containing several sentences that cover the source, payment, credentials, and legal context. It is front-loaded with the tool name and purpose, but includes some operational details that are useful. Not overly verbose, but could be tightened by removing redundant phrasing like 'consulta informação de fontes e órgãos oficiais brasileiros (a mesma disponível ao cidadão)'.

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 six required parameters, zero parameter descriptions, and no output schema, the description must provide substantial guidance. It explains the general purpose and operational constraints (payment, credentials, LGPD) but does not describe what each parameter is for, what the expected output looks like, or any usage patterns. This is insufficient for an agent to correctly 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?

Schema description coverage is 0%—no parameter descriptions are provided. The tool description does not explain the meaning of any of the six required parameters (a3, a3_pin, login_cpf, login_senha, chassi, uf). Even though 'chassi' and 'uf' appear in the text, they are not elaborated. The agent receives no assistance in understanding how to fill these fields, which is a major 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 it's a consultation tool for vehicle data from other states (Base de Outros Estados) using official sources. It distinguishes itself from sibling tools (authenticate, connect, marketplace, etc.) which are platform-level operations, so the core purpose is evident. However, it doesn't specify exactly what vehicle information is returned (e.g., owner, restrictions), leaving some ambiguity.

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 use for querying vehicle information from other states, and mentions payment via pre-paid credits and credential requirements, which gives some usage context. However, it does not explicitly state when to use it over alternatives or provide any exclusions. Since sibling tools are unrelated, the guidance is implicit rather than 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?

The description goes far beyond the spare annotations by disclosing important behaviors: invoke works even when the MCP is not installed, one-off runs do not bloat the tool list, credential needs return a connect link, empty-wallet paid tools return a checkout link then require retry, and writes require workspace owner/admin. No contradiction with annotations was found.

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 dense but logically organized: overview, core flow, the key invoke behavior, install-vs-invoke guidance, auxiliary actions, permissions, and the prompt library. It is on the longer side, but for a multi-action tool of this breadth every sentence adds meaningful guidance and there is 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?

Given the tool's complexity, the lack of an output schema, and minimal annotations, the description covers the major workflows, permission constraints, credential/payment edge cases, and prompt-library behavior well. It does not describe return shapes or error conditions, but the described flow is actionable enough for an agent to select the right action and parameters.

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% across 23 parameters, so the description must compensate. It does explain many action enum values and the roles of mcp_id/tool_id/arguments in the search→describe→invoke flow, but several parameters remain opaque (e.g., immediate, tier_slug, prompt_targets, prompt_title, limit/query). The description adds meaning for the main workflow but does not fully clarify the parameter space.

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 an overarching verb+resource ('official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them') and differentiates its main functional areas: search/describe/invoke, install/list/subscribe, and the prompt library. It goes beyond a vague label by specifying the core flow and distinguishes itself from the sibling tools.

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 provided throughout: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT in the active toolkit', and 'request_mcp asks us to build a NEW MCP when nothing fits.' It also distinguishes list_tools from search/describe and notes admin/owner requirements for writes, giving clear when-to-use versus 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 indicate idempotentHint=true and no destructive hints, which are not contradicted by the description. The description adds a behavioral note: including the conversation array for reproduction, which helps the agent understand the expected input. However, it does not disclose any other behavioral traits (e.g., response format, rate limits), though the lack of such may be acceptable given the simplicity.

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 front-loads the core purpose immediately. Every word is useful; no redundant or filler content.

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 (no output schema, 3 parameters) and the description covers the main action and one parameter usage. However, it does not explain the 'context' parameter at all, nor does it specify what constitutes a valid 'conversation' array or mention any prerequisites (e.g., authentication). Given the simplicity, it's adequate but leaves 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?

Schema description coverage is 0%, but the description clarifies the 'conversation' parameter (used for reproduction). It does not explain 'context' or elaborate on 'message' beyond implying it contains the report content. With only 3 parameters and defaults provided, the description partially compensates but leaves 'context' 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 the tool's purpose: reporting bugs, missing features, or providing feedback. It identifies the primary action (report/send) and the resource (bug/feature/feedback). Although it doesn't explicitly differentiate from siblings, its unique function as a feedback mechanism is evident.

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 context: 'Report a bug, missing feature, or send feedback' indicates when to use the tool. However, it does not mention when NOT to use it or suggest alternatives (e.g., for general inquiries), so it lacks explicit exclusion criteria.

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 and idempotentHint, covering the safety profile. The description adds the fact that versions are 'current,' implying dynamic retrieval, but it does not provide additional behavioral context (e.g., output format, no network dependency). 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 a single sentence, front-loaded with the key action and resource, with no unnecessary words or repetition. It is highly concise and clear.

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-argument, read-only version-checking tool, the description is complete. It specifies the exact categories of information returned (platform and adapter versions). No output schema exists, but the simplicity of the tool makes this 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?

The tool has zero parameters, so the description cannot add parameter semantics beyond what the schema shows. The baseline of 4 for zero-parameter tools applies; no additional information is needed.

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: showing current MCP platform and adapter versions. It uses a specific verb ('show') and a specific resource, which distinguishes it from sibling tools like authenticate or report_bug.

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 any guidance on when to use this tool versus alternatives. It lacks explicit context such as 'use this when checking compatibility' or 'for version issues in bug reports.'

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, establishing a safe read operation. The description adds value by enumerating the exact return content (installed MCPs, connection status, accounts, catalog tool counts), which is not covered by annotations. It doesn't mention side effects or constraints beyond what annotations imply, but with strong annotation coverage, this is adequate additional 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 a single, well-structured sentence that front-loads the verb 'Returns' and then lists the specific data items. There is no fluff, every clause contributes to understanding the output, and it is optimally concise for an informational 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?

With no output schema, the description must explain what the tool returns, and it does so thoroughly by listing the five components of the toolkit state. Given the tool's simplicity (no params, read-only, idempotent), this is complete. The description fully prepares an agent to invoke and interpret the result without ambiguity.

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 schema coverage is trivially 100%. Per rubric, a baseline of 4 applies for 0-param tools. The description adds no parameter-specific meaning because none exist, but it correctly implies no inputs are required, aligning with the tool's purpose.

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: returning toolkit state with specific components (installed MCPs, connection status, accounts, catalog tool counts). It uses a specific verb 'Returns' and identifies the resource ('current toolkit state'), effectively distinguishing it from siblings like show_version (version info) and connect (establishing connections).

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 clearly conveys when to use this tool—whenever an overview of the toolkit's status is needed. It doesn't explicitly exclude alternatives, but given the tool's self-contained nature and the sibling tools' distinct purposes (auth, connect, version, report), the context is sufficient. A minor gap is the lack of explicit guidance on precedence over show_version or connect, but this is not ambiguous.

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