SEFAZ PR: IPVA

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

Annotations already indicate idempotent and non-read-only behavior, but the description adds valuable context: it explains the tool returns a link when called with no args seria and that authentication can be persistent or session-based. It does not contradict annotations and goes beyond them by detailing the exact behavior in two scenarios.

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 and front-loaded with the tool's purposeais, then explains usage. It is somewhat long but every sentence adds value—no fluff. The structure is logical, though it could be tightened with clearer separation of steps.

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 slash single optional parameter and lack of output schema, the description covers essential usage and outcomes. It does not explicitly state the return value or error cases, but for a simple auth tool, the description is sufficiently complete to guide an agent.

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 only a bare 'token' string with no description, and coverage is 0%. The description fully compensates by explaining that the token is a JWT for session-only login Secret, and explicitly states that calling with no args retrieves the link. This gives complete clarity on parameter 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: to authenticate with MCP.AI for IDE agents by logging in and obtaining an access token. It distinguishes itself from siblings by focusing specifically on authentication rather than generic operations, and it explains the two primary modes of use (permanent config vs. session-only), making the tool's function 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 explicit guidance on when to use each mode: for a permanent connection, configure the header; for a session, call with a token after pasting; and call with no args to get the login link. It clearly separates the alternatives and gives concrete steps, which qualifies as strong 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?

Annotations already cover safety (readOnlyHint, idempotentHint, destructiveHint). The description adds meaningful behavioral context: what happens when credentials are missing (returns connect_url) and distinguishes between toolkit and per-install URLs. This goes beyond annotations and provides useful usage 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 two sentences, concise, and front-loaded with the primary action. Every sentence provides actionable information without redundancy 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 stateless status tool with no parameters and no output schema, the description adequately covers the essential return behavior (connection status and URLs) and scenarios (all connected vs. missing credentials). It does not detail the exact response shape, but that is acceptable given the simplicity and the readOnlyHint.

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 per the rubric baseline is 4. The description does not need to elaborate on parameters, and no parameter-specific information is missing.

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 examples of states (authenticated:true when all connected, empty pending[]). This is a specific verb+resource and distinguishes it from siblings like authenticate, which performs 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?

The description implies usage as a status check, but does not explicitly contrast with alternatives or provide when-not-to-use guidance. It is clear from context that this is a read-only connectivity check, but no explicit exclusions or alternative references (e.g., 'use authenticate to initiate connection') 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 indicate readOnlyHint=false and destructiveHint=false, which already signal mutability, but the description goes far beyond by explaining that invoke runs tools even when the MCP is not installed, returns connect/checkout links for auth/payment, and that writes require workspace owner/admin. It also notes installed_in_toolkit vs installed_in_workspace flags and the one-off install behind invoke. These behaviors are critical and not disclosed in 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 a single dense paragraph but well-structured: it opens with the core purpose, then details the invoke behavior, distinguishes install vs invoke, covers subscription and reporting actions, and finishes with the prompt library. Every sentence adds value, but the sheer length (due to the complexity of 14 action types) makes it less concise than ideal. The flow is logical 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?

Given the tool has 23 parameters, 14 action types, and no output schema, the description provides a comprehensive overview of the main workflows (search, describe, invoke, install, prompts) and key side behaviors (auth links, wallet top-up, permission requirements). It does not detail return formats for each action or cover all edge cases, but it is sufficient for an agent to select and invoke the appropriate action in most scenarios.

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 carries the full burden. It explains the meaning of key parameters like action (through its enum values), query, mcp_id, tool_id, and arguments, and describes prompt-related parameters (prompt_slug, prompt_vars, etc.) in the context of the prompt library. However, some parameters like immediate, tier_slug, and prompt_targets are not explicitly discussed, leaving minor gaps despite the strong overall contextual guidance.

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 is the official mcp.ai marketplace—a catalog of every MCP/tool and a way to run them. It explicitly covers capability requests like 'find an MCP that does X' and explains the core flow (search → describe → invoke). It distinguishes this tool from siblings like authenticate or report_bug by focusing on marketplace operations, even if not naming them directly.

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 when-to-use guidance: 'prefer invoke for a single/occasional use; use install only to make an MCP PERMANENT' and explains that search discovers MCPs, describe returns profiles, and invoke runs tools. It also differentiates list_tools for what is callable right now and request_mcp for when nothing fits. Ownership requirements for writes are also stated, offering clear direction on action selection.

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, destructiveHint=false, and idempotentHint=true, which covers safety and idempotency. The description adds a practical behavioral instruction (including conversation for reproduction) but does not disclose what happens after submission (e.g., acknowledgment, persistence). Since annotations carry safety context, a mid-range score 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 two sentences: the first states purpose, the second gives usage guidance. No word is wasted, and the most critical information (purpose) is front-loaded. It is appropriately sized for the tool's simplicity.

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 three parameters and no output schema, the description should cover all inputs. Only the conversation parameter is mentioned; the required 'message' and optional 'context' are ignored. The description also does not explain expected return values or side effects. This is incomplete for an agent to use effectively.

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 explain parameters. It only mentions the 'conversation array' for reproduction, leaving 'message' and 'context' undocumented. For a 3-parameter tool with zero schema descriptions, this is insufficient 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 the tool's function: 'Report a bug, missing feature, or send feedback.' This is a specific action with a clear resource (the bug/feedback report). It distinguishes itself from sibling tools like authenticate, marketplace, and show_version, 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 gives direct usage guidance: 'Include the conversation array with recent messages for reproduction.' This tells the agent how to construct a useful report. However, it does not explicitly mention when not to use it or compare to alternatives, but given the unique nature of the tool, that omission is acceptable.

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?

Beyond the readOnlyHint, idempotentHint, and destructiveHint annotations, the description discloses additional behavioral traits: no platform credentials required, pay-per-query with prepaid credit, querying non-confidential official data, and LGPD responsibility. These add meaningful context about operation cost and legal requirements.

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 four sentences, containing relevant information about purpose, hosting, credentials, cost, data confidentiality, and LGPD compliance. While slightly verbose, each sentence adds value and the structure is 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?

Given the simple one-parameter tool with no output schema, the description covers operational context (payment, credentials, data type) but lacks an explanation of the parameter or the response format. It does not mention what the IPVA query returns, which would help the agent understand expected outcomes.

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 single parameter 'renavam' has no description in the schema (0% coverage) and the description does not mention it at all. It does not explain what renavam is or how it should be formatted, so the agent receives no semantic guidance beyond the parameter name.

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 explicitly states 'SEFAZ PR: IPVA, consulta em fonte oficial' which clearly identifies the tool as a query for IPVA data from the official SEFAZ PR source. This is a specific verb+resource combination that distinguishes it from sibling tools 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 provides context such as 'Hospedado pela plataforma, sem credenciais da plataforma' and 'pague por consulta com crédito pré-pago', indicating the tool is a paid service without platform credentials. However, it does not explicitly state when to use this tool versus alternatives or exclusions, though the sibling tools are unrelated.

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 minimal behavioral context beyond that, such as the nature of the version information. No contradiction exists, but the description does not go beyond the annotations to disclose additional traits.

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 without any extraneous wording. It is front-loaded with the action and resource, making it highly concise and well-structured.

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 (no parameters, no output schema, and comprehensive annotations), the description is sufficiently complete. It states exactly what the tool does, and the annotations cover safety and idempotency, leaving no critical gaps for an agent to select or 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 tool has zero parameters, so the description does not need to elaborate on parameter meaning. The schema coverage is 100% (no properties). Baseline is 4 for zero-parameter tools, and the description adds clarity about the tool's output without needing 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: showing current MCP platform and adapter versions. It uses a specific verb (show) and a definite resource (versions), which distinguishes it 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 when to use the tool (to retrieve version information) but provides no explicit context about alternatives or exclusions. It does not compare with sibling tools like toolkit_info, so the usage guidance is only 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 readOnlyHint=true, so safety is established. The description adds value by detailing exactly what information is returned (installed MCPs, status, accounts, tool counts), which goes beyond annotation hints and clarifies output scope.

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 core action ('Returns the current toolkit state') and then lists what is included. No unnecessary words 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?

Given no output schema exists, the description adequately explains the return content. For a low-complexity, read-only tool, it 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?

With zero parameters, baseline is 4. The description adheres to this: no parameter information is needed, and the description does not introduce any parameter-related ambiguity.

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 what the tool does: returns the current toolkit state including installed MCPs, connection status, connected accounts, and tool counts. This is specific and distinguishes it from sibling tools like authenticate or connect, which are action-oriented.

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 toolkit status but does not explicitly state when to use it versus alternatives (e.g., show_version for version info). No exclusions or alternative recommendations are provided, so while the purpose is clear, guidance is minimal.

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