SEFAZ SPU: Dados Cadastrais de Imóvel da União

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

Annotations already declare idempotentHint=true and readOnlyHint=false. The description adds context about returning a login link when called with no args and about session vs permanent connections, which goes beyond the structured fields.

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?

Three dense sentences, front-loaded with purpose, structured with 'Best'/'Or' to clearly separate alternatives. Every sentence adds value with no 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?

The tool has one optional parameter and no output schema, and the description covers both usage modes and parameter behavior. It lacks explicit success/error response details, but overall it is sufficiently complete for an agent to invoke 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?

Schema coverage is 0% and the token parameter has no description. The description compensates by explaining the token is a JWT for session-only login and that omitting it generates a link, providing essential semantics not available elsewhere.

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 handles authentication/login for MCP.AI with specific actions (log in, copy token, get link). It distinguishes from sibling tools like 'connect' and 'marketplace' by focusing on token-based 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 explicit usage guidance: 'Best' for permanent config header, 'Or' for session-only token, and 'with no args to get the link'. It tells the agent when to use this tool and how to invoke it, though it doesn't explicitly compare with sibling tools.

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 read-only and idempotent behavior. The description adds valuable detail about the response structure under different conditions (e.g., 'authenticated:true' vs 'connect_url'), enhancing transparency beyond the annotations. No contradictions exist.

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 to convey the core behavior and conditional outcomes. It avoids redundancy and is 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, straightforward output), the description adequately explains all relevant behavioral aspects, including edge cases like missing credentials. It is complete in 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 tool has zero parameters, so schema coverage is 100%. The description adds no parameter-specific information, which is appropriate. Baseline score of 3 is given as per guidelines.

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: 'Returns connection status and URLs.' It also explains specific conditions for different outputs, making the purpose unambiguous. It is distinct 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 does not explicitly indicate when to use this tool versus alternatives. It describes output behavior but not usage scenarios or prerequisites. There is no mention of when to prefer 'connect' over 'authenticate' or other tools.

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?

Discloses key behavioral nuances: invoke runs an MCP even when not installed (without adding it to the toolkit), returns authenticate/top-up links for credential/payment needs, and distinguishes one-off vs permanent execution. Also covers auth requirements for mutating actions. This goes well beyond the bare readOnlyHint=false annotation, which is the only structured signal.

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 block of text that flows without structural breaks. It is informative but wordy, mixing core flow, edge cases, and prompt library guidance in one paragraph. Front-loads the purpose well, but could benefit from bullet points or action-by-action breakdown to improve scannability.

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 23 parameters and no schema descriptions, the narrative maps each action to its intent-on parameter needs, covers auth constraints, credential/payment fallback flows, and distinguishes installed vs ephemeral execution. Complete enough for an agent to properly route most queries.

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 21 parameters with zero descriptions sequins full burden. The description explains the central 'action' parameter by walking through each action and its role in the flow, and clarifies key parameters like query, tool_id, arguments, and prompt_* fields. It doesn't thoroughly document every parameter (e.g., immediate, tier_slug), but it covers enough to guide correct invocation in the majority of cases.

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?

Description clearly identifies the tool as the marketplace hub with both discovery and execution modes, and maps each action (search, describe, invoke, install, list_tools, prompt library, etc.) to its purpose. Distinguishes from sibling tools like toolkit_info and sub-tools by naming capabilities and the core 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?

Explicitly explains when to use invoke vs. install ('Use install only to make an MCP permanent... prefer invoke for a single/occasional use'), when to search vs. request_mcp, and states permission requirements for writes (owner/admin). Names alternatives and exclusions, giving clear decision 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 disclose safety traits (readOnlyHint false, destructiveHint false, idempotentHint true). The description adds that a conversation array should be included for reproduction, which is useful context, but it does not disclose external effects (e.g., where the report is sent, whether data leaves, or persistence).

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 front-load the core action and provide the key reproduction instruction. No filler or redundant 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?

For a simple three-parameter reporting tool without an output schema, the description covers the main purpose and the most important parameter guidance. It is slightly incomplete because the 'context' parameter is left undocumented and no return/side-effect behavior is mentioned, but the complexity level is low.

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 partially compensates by indicating that the conversation array is used for reproduction and that message is the core text. However, it does not explain the 'context' parameter or provide format/type details for the conversation string.

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 reports a bug, missing feature, or feedback, with a specific verb and resource. It is distinct from all sibling tools, none of which handle feedback or issue reporting.

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?

Usage context is implied by being the only feedback/reporting tool among the siblings, but the description does not explicitly state when to prefer this tool over others or provide exclusions. The instruction to include the conversation array is usage guidance, but not alternative-selection 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?

Beyond the annotations (readOnly, idempotent, non-destructive), the description adds meaningful behavioral context: the operation is paid via prepaid credits, uses no platform credentials, retrieves only non-confidential citizen-accessible data, and places LGPD-related responsibility on the client. This is substantial useful disclosure beyond the structured hints.

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 and front-loads the core purpose in the first sentence. The subsequent sentences add relevant context around cost, credentials, data sensitivity, and legal responsibility. There is minor boilerplate in the LGPD clause, but overall the description is efficiently organized.

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 relatively simple and the annotations plus description cover safety, cost, and data sensitivity. However, there is no output schema and the parameter semantics are entirely unaddressed, leaving a noticeable gap for an agent trying to construct a valid request. It is adequate but not 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 schema has 0% description coverage and the description never mentions the three parameters (cpf, rip, cnpj). Although the parameter names are somewhat self-explanatory as Brazilian identifiers, there is no guidance on requiredness, mutual exclusivity, or formatting, so the description fails to compensate for the schema's lack of parameter documentation.

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 this tool consults 'Dados Cadastrais de Imóvel da União' from an official SEFAZ SPU source. The verb 'consultar' plus the specific resource and official-source context makes the purpose unambiguous and distinguishes it from the unrelated 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?

The description provides clear context for use: it queries official Brazilian government data, requires no platform credentials, and costs prepaid credits per query. It does not explicitly name alternatives or exclusion conditions, but the official-source and citizen-accessible framing gives sufficient situational 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds no behavioral context beyond stating that version information is shown, but for a simple no-argument read-only tool this is minimally 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 a single front-loaded sentence that states exactly what the tool does with no redundant words, filler, or repetition of schema information. 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 such a simple tool with zero parameters, no output schema, and strong annotations, the description is complete enough. It identifies the content ('current MCP platform and adapter versions') and the action ('Show'), which fully covers the user-facing 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?

The tool has zero parameters, so there is no parameter semantics for the description to clarify. The description is consistent with the empty input schema and does not need to compensate for schema gaps.

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 ('Show') and names the resource ('current MCP platform and adapter versions'), making the tool's purpose immediately clear. However, it does not explicitly distinguish this tool from sibling tools like toolkit_info, which could conceivably also expose informational data.

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?

There is no guidance about when to use this tool versus alternatives, nor any context about runtime, troubleshooting, or verification scenarios. The description implies it is for checking versions, but it does not say when this is appropriate or when another tool should be preferred.

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 read-only, idempotent, and non-destructive behavior, so the description doesn't need to repeat these. It adds value by specifying exactly what state fields are returned, which goes 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?

The description is a single, well-structured sentence that front-loads the key information (returns toolkit state) and then lists the specific aspects covered. It is concise, with no redundant or vague wording.

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, no-output-schema tool, this description is nearly complete. It covers the essential aspects of what the tool returns. It might have mentioned whether the data is a snapshot or real-time, but that's minor given the tool's simplicity.

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 no parameters, and schema coverage is 100% (empty properties), so the description has no parameters to explain. It avoids inventing unnecessary details, earning a baseline 4 for zero-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 identifies the tool as returning toolkit state with specific details (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from siblings like 'authenticate' or 'connect' which handle actions rather than state inspection.

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 it is a read-only informational tool for inspecting the toolkit's current state, which is clear from context. It doesn't explicitly name alternatives, but 'show_version' is the only sibling with a similar informational purpose, and this description's detail makes the differentiation obvious.

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