SEFAZ SPU: Emitir Certidões de Imóveis da União

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

Annotations indicate idempotentHint=true and destructiveHint=false, which align with the description's non-destructive nature. The description adds context about the authentication flow (browser login, token copy) and the two modes, which goes beyond the annotations. However, it doesn't mention potential side effects like token expiration or security considerations, but given the annotations cover the safety profile, this is adequate.

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-loaded with the tool's purpose, and every sentence adds value. It covers the main use case, the two modes, and the invocation pattern in a compact form. No fluff.

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 is complete enough. It explains the authentication flow, the two modes, and how to invoke. It could mention what the response looks like, but since there's no output schema, it's not strictly required. The description is sufficient for an agent to use the tool 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?

The schema has one optional parameter 'token' with no description. The tool description explains that the token is a JWT pasted by the user for session-only login, and that calling with no args returns the link. This adds meaning beyond the schema, which is otherwise bare. Since schema coverage is 0%, the description compensates well.

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: authenticate the MCP server for IDE agents by logging in via browser and obtaining an access token. It distinguishes itself from siblings by specifying the authentication flow and the two modes (permanent config vs session-only).

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 this tool: when the user needs to authenticate the server. It explains the two usage scenarios (adding token to config for permanent connection, or pasting token for session-only) and even instructs to call with no args to get the link. This is clear and actionable.

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 establish safe, idempotent, non-destructive behavior; the description adds valuable detail about the two possible response states (authenticated vs. missing credentials), enhancing transparency beyond 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 clearly explain the tool's output without redundancy. The structure is efficient and easy to parse.

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?

Despite lacking an output schema, the description fully explains the return values in both states (authenticated and missing credentials), providing complete context for expected behavior.

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 no parameters, so the parameter coverage is trivially complete. The baseline of 4 applies given the high schema coverage, and no further description 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 it returns connection status and URLs, with specific conditions for authenticated vs. missing credentials, distinguishing it from sibling tools like authenticate and 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?

While it doesn't explicitly contrast with alternatives, the behavior is clear enough to indicate when to use it (checking connection state). The description implies usage for status checks, which is adequate for a simple 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?

Beyond annotations (openWorldHint true, etc.), the description discloses that invoke runs MCPs even when not installed, returns connect/checkout links for auth/payment, and that writes require workspace owner/admin. It also notes the 'without bloating the tool list' behavior and flags installed_in_toolkit vs workspace status. 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 dense paragraph with no visual structure (bullets, sections). While every sentence adds value, the wall of text makes it harder to scan. It is front-loaded with the main purpose but quickly becomes a lengthy list of actions and edge cases. Could be improved with structured formatting.

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 is exceptionally thorough for a complex multi-action tool with no output schema and no annotation help. It covers the full workflow, authentication/payment handling, permission requirements, the prompt library, and even mentions edge cases like 'request_mcp asks us to build a NEW MCP'. It is practically complete for an agent to understand and use the tool 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 does a good job explaining key parameters like action, mcp_id, tool_id, arguments, prompt_vars through the flow narrative. However, many parameters (limit, immediate, tier_slug, cancel_reason, prompt_category, etc.) are not individually described, requiring inference from action names. It partially compensates but not fully for 23 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 role as 'the official mcp.ai marketplace' and explains its core functions: search, describe, invoke, install, and prompt library actions. It distinguishes from siblings by covering the marketplace hub, while separate tools like report_bug are also mentioned as actions within, though a sibling tool exists, the description clarifies its 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 provides explicit guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT'. It also explains when to use search vs describe, how invoke handles auth/payment links and retry logic, and distinguishes prompt library actions from MCP actions. It even notes permission requirements for writes.

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 idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds no additional behavioral details (e.g., ticket creation, side effects), but it doesn't contradict the annotations. With annotations present, the bar is lower, and the description meets the minimum without adding extra value.

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 purpose first and a critical usage tip second. No redundant wording, no repetition of schema info, and every word earns its place. It's appropriately brief.

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 (3 flat params, no output schema), and the description covers main purpose and one key usage detail. However, it overlooks the 'context' parameter entirely and doesn't mention any preconditions or limitations. For a simple tool it's mostly adequate but has a noticeable gap that could confuse 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?

Schema description coverage is 0%, so the description must compensate for parameter explanations. It only hints about the 'conversation' parameter, but doesn't clarify the meaning or format of 'context' or 'message' (though message is implied by purpose). It doesn't explain that conversation is a JSON string or what context is used for. This is insufficient given the lack of schema descriptions.

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: report a bug, missing feature, or send feedback. The verb 'Report' and resource are explicit, and it is distinct from sibling tools like authenticate or marketplace, which 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 provides a clear directive to include the conversation array with recent messages for reproduction. While it doesn't explicitly say when not to use it, there are no similar sibling tools, so the context is unambiguous. The instruction is actionable and relevant.

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 annotations declare readOnlyHint: true, idempotentHint: true, and destructiveHint: false, which already cover the safety profile (read-only, non-destructive). The description adds context about the service being hosted on the platform, requiring no platform credentials, and payment via prepaid credits, which is useful. It also clarifies the data is not confidential and the client is responsible for LGPD compliance, adding behavioral context. However, it does not describe the full response format or any rate limits, but given the annotations, the transparency is adequate but not extensive.

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-loaded with the primary action. It packs a lot of information: purpose, official source, hosting, payment model, data privacy. It could be slightly more structured, but it efficiently communicates the essential information without unnecessary fluff.

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 moderately complex with 4 parameters but only 1 required, and there is no output schema. The description explains the context (official source, payment, LGPD) but lacks details on parameter semantics and the return value (certificate data). Given that annotations cover safety and idempotency, the description is fairly complete for a read-only consultation, though it could mention the type of data returned.

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 4 parameters with 0% description coverage, so the description must compensate, but it does not provide any details about the parameters. It mentions 'consulta a informação' but does not explain what each parameter (cpf, rip, cnpj, tipo_certidao) represents or how they should be used. Since the description covers the purpose of the tool but not the parameters, the baseline of 3 is appropriate, but it could be improved by describing 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 emit certificates for Union properties (Certidões de Imóveis da União) using an official source. The verb 'Emitir' is specific, and the resource is named clearly. It also distinguishes itself from generic tools by specifying the domain (SEFAZ SPU) and the type of certificate (imóveis). However, it does not explicitly mention the required parameter in the description, and the schema lacks descriptions, so the purpose is clear but not fully detailed.

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 context: it is for consulting official Brazilian sources, and it is a paid service with prepaid credits, suggesting a cost consideration. It also mentions data privacy (LGPD) and that the client is the data controller, hinting at when this tool should be used responsibly. However, it does not provide explicit guidance on when to use this tool over alternatives, nor does it mention when not to use it. It also lacks details on prerequisites such as authentication or required credits.

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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, clearly indicating a safe read operation. The description's verb 'show' aligns with these hints, and while it doesn't detail the return format or any potential side effects, the annotations cover the safety profile adequately.

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 unnecessary words. It efficiently conveys the tool's action and subject.

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-check tool, the description is complete: it states what versions are shown (MCP platform and adapter). There is no output schema, but for a version query that is not necessarily required, and the absence of parameters means no additional context is needed.

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 the schema's description coverage is 100% trivially (as there are no properties). Thus, there is no need for parameter explanations; the schema and description are complete.

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', providing an unambiguous purpose. There is no ambiguity or vagueness about what the tool does.

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 when version information is needed, but does not explicitly mention alternatives or preconditions. However, given the tool's simplicity and zero parameters, its use case is self-evident, and there are no competing tools listed that would require differentiation.

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 safety is covered. The description adds detail about the return content but does not disclose additional behavioral traits such as network dependencies, rate limits, or side effects beyond what annotations state.

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 primary action ('Returns the current toolkit state') and then lists the details in a clear, efficient manner. There is no unnecessary repetition or fluff.

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-param, read-only tool with strong annotations, the description fully covers what the tool returns and is self-sufficient. No output schema exists, but the description serves that role by detailing the return value composition.

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 the schema coverage is trivially 100%. Baseline for 0 params is 4, and no parameter clarification 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 uses the specific verb 'Returns' and clearly identifies the resource as 'current toolkit state,' enumerating specific contents (installed MCPs, connection status, accounts, catalog tool counts). This makes it distinct from sibling tools like show_version or 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 implies usage for inspecting toolkit state, but it does not explicitly mention when to use this tool versus alternatives or provide exclusions. No direct guidance is given beyond the purpose statement.

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