CND Imóvel Rural

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

The description adds behavioral context beyond annotations: it distinguishes 'permanent, non-expiring connection' from 'session-only login' and specifies that calling with no args returns a link. This is consistent with idempotentHint=true and provides useful operational detail.

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 three sentences, front-loaded with purpose and usage, and each sentence adds necessary info about the two auth modes. It is slightly dense but every part 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 a simple tool with one optional parameter and no output schema, the description covers the full workflow: getting the link, using a token for session login, and permanent header configuration. It is complete for an authentication 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's token property has zero description, but the description fully explains its semantics: 'call with { token: "<jwt>" } after the user pastes', and clarifies optionality with 'no args to get the link'. This completely compensates for the 0% schema coverage.

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 authenticates IDE agents for MCP.AI, describing the login flow with specific verb 'log in' and resource 'MCP.AI'. It does not explicitly differentiate from sibling 'connect', though the target audience ('IDE agents (Cursor, etc.)') provides some context.

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 gives explicit usage instructions: 'Best: add it to this server's config as a header' for permanent connection, or 'paste it here for a session-only login' with token, or 'no args to get the link'. This clearly explains when to use each mode, though it does not mention alternatives or when not to use the 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 the annotations (readOnly, idempotent, non-destructive), the description discloses important behavioral traits: no credentials required, pay-per-query model, public data source, and client data controller responsibility. These add significant context beyond the structured annotations, with no contradiction.

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 paragraph with no redundancy. It efficiently covers purpose, access model, and data privacy. It is slightly dense but every sentence adds necessary context, so it earns a 4.

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 two-parameter tool with no output schema, the description covers operational context (hosting, credentials, payment, data sensitivity, LGPD). It does not mention response format or error handling, but these are less critical given the tool's simplicity and good annotations.

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 CIB parameter ('a partir do CIB') but does not explain the 'completo' boolean parameter. With two parameters and zero schema coverage, the description should clarify both or at least hint at the optional one's meaning.

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 specific action ('Emite a Certidão Negativa de Débitos e Dívida Ativa da União') and the resource (rural property, identified by CIB). This is a specific verb+resource combination that clearly distinguishes it from the generic 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 about when the tool is appropriate: it queries public-access information, requires prepaid credit, and involves LGPD responsibilities. However, there are no explicit alternatives or when-not-to-use conditions, so it falls short of a 5.

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 readOnly and idempotent. The description adds meaningful response behavior: it returns authenticated:true with empty pending[] when all providers are connected, and connect_url when credentials are missing. This 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 two sentences, front-loaded with the core result, and contains no redundant or verbose 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 zero-parameter read-only tool, the description adequately covers both the success case and the missing-credentials case. No output schema exists, but the returned fields are described enough for an agent to understand the tool's 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 the schema trivially covers them. A baseline of 4 is appropriate because no parameter explanation 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 returns connection status and URLs. It differentiates from sibling 'authenticate' by focusing on checking status rather than establishing 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?

Usage context is implied: it is the tool to check connection status. However, there are no explicit when-to-use or alternative references, even though sibling tools like 'authenticate' could warrant a comparison.

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?

Goes far beyond minimal annotations, explaining nuanced behaviors: invoke runs tools even when not installed, returns connect/checkout links for missing credentials or empty wallets, and does not bloat the toolkit. It also discloses authorization requirements for writes and distinguishes permanent vs. one-off installations. 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 dense but well-structured, starting with the overall purpose, then the core flow, key behavioral notes, permissions, and the prompt library subsection. Each sentence adds value, though it is long—justified by the tool's complexity.

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 high complexity (23 params, 14 actions, additional prompt library), the description is remarkably complete. It covers all action categories, edge cases like uninstalled MCPs and payment/auth failures, permission requirements, and the distinct prompt library feature. It even notes output details like installed_in_toolkit flags, making it sufficient despite no output schema.

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 compensates by explaining the action parameter and its possible values, and referencing key parameters like mcp_id, tool_id, and arguments within the flow. However, many individual parameters (e.g., limit, cancel_reason, prompt_vars) are not explicitly described, so it doesn't fully cover all 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 identifies the tool as the official marketplace for MCPs/tools, functioning as both catalog and execution platform. It differentiates from sibling tools by explicitly stating its scope ('every MCP/tool, AND the way to run them') and detailing the core flow of search/describe/invoke/install.

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?

Provides explicit guidance on when to use each action: search to discover, describe to inspect, invoke for one-off runs, install for permanent additions, list_tools for current callable tools, request_mcp for unmet needs. It also states preferences (prefer invoke over install for occasional use) and alternatives, making tool selection unambiguous.

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 readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description adds the reproduction guidance but does not disclose what happens after reporting (e.g., whether data is sent, any confirmation behavior, or side effects). With annotations present, the bar is lower, yet the description still adds limited behavioral 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 concise sentences, front-loaded with the action ('Report a bug, missing feature, or send feedback'), and each sentence provides necessary information without 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 simple reporting tool, the description covers the core purpose and the key parameter guidance. It does not explain the optional 'context' parameter, and there is no output schema, but the missing details are 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?

Schema description coverage is 0%, so the description carries the burden. It clarifies that 'message' is the bug/feedback text and 'conversation' should convey recent messages for reproduction. However, the 'context' parameter remains unexplained, so the compensation is partial.

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. It uses a specific verb ('Report') and resource ('bug') and naturally distinguishes itself from unrelated sibling tools like authenticate 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?

Clear context is given: use this tool to report bugs, missing features, or feedback. It also provides a practical instruction ('Include the conversation array with recent messages for reproduction'), though it does not explicitly exclude alternatives. Siblings are different enough that no further disambiguation is needed.

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, idempotentHint, and non-destructive behavior, so the description does not need to restate safety. The description adds no extra behavioral context beyond the annotations, but it is consistent with 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 a single, front-loaded sentence that clearly states the action and target. No wasted words.

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-parameter tool with no output schema, the description fully conveys what the tool does and what the user will get (version info). It is complete enough to select and invoke 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 tool has zero parameters, so the input schema is trivially complete. Baseline for 0 params is 4; the description correctly implies no arguments are 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 a specific verb ('Show') and identifies the resource ('MCP platform and adapter versions'), making the tool's purpose immediately clear. It is distinct from sibling tools like toolkit_info, which likely covers broader information, whereas this focuses specifically on versions.

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, nor does it mention exclusions or prerequisites. It is a simple 'show me versions' tool, but there is no explicit when-to-use context provided.

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 mark it as read-only, idempotent, and non-destructive. The description adds value by detailing exactly what state is reported (installed MCPs, connection status, accounts, tool counts), which goes beyond the annotation hints 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?

A single, well-structured sentence that front-loads the core action (returns toolkit state) and immediately specifies the meaningful components. Every word contributes 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?

For a parameterless read-only info tool with no output schema, the description fully conveys the purpose and return content. It is complete in context, especially with sibling tools like authenticate and connect clarifying its observational role.

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, so the schema coverage is trivially 100%. The description has no parameter burden and correctly focuses on return content instead.

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, listing specific content (installed MCPs, connection status, connected accounts, catalog tool counts). This distinguishes it from sibling tools that perform actions like authentication or connection.

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 on what information is returned, implying usage when an overview of toolkit state is needed. It does not explicitly name alternatives or exclusions, but the sibling tool names make the differentiation obvious.

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