Prefeitura RS Santa Cruz do Sul: Certidão Negativa de Débitos

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

Annotations already convey non-read-only, idempotent, and non-destructive behavior; the description adds browser login flow, token copying, permanent vs session-only connections, and the no-args link behavior. It does not describe the exact response shape, but no output schema exists to require that.

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 somewhat run-on but every clause adds value: audience, login flow, permanent configuration option, session-only option, and no-args behavior. It is appropriately sized and front-loaded with the core purpose.

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 single optional parameter and lack of output schema, the description provides enough context for an agent to execute the authentication flow end-to-end. Minor gaps like the exact return format prevent a perfect score.

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 token string with 0% description coverage, so the description carries the burden. It compensates well by explaining that token is a JWT pasted by the user for session-only login and that omitting it returns the login link. This fully clarifies the only parameter.

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 with MCP.AI for IDE agents, involving browser login and token retrieval. This specific verb+resource combination distinguishes it from siblings like connect by naming the service and the authentication mechanics.

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 explicitly explains when to use the permanent config-header approach versus a session-only token paste, and notes that calling with no args returns the login link. It gives clear context, though it does not name sibling alternatives or state explicit exclusions.

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, so the description doesn't need to repeat that. It adds valuable behavioral context by describing the response structure (authenticated:true, pending[], connect_url) and the conditional behavior for missing credentials, 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?

Two concise sentences that front-load the core purpose and then add conditional detail. Every word earns its place; there is no fluff 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?

With no output schema, the description must carry the return documentation, and it does well by outlining the key response fields and their meaning. It could be slightly more exhaustive (e.g., listing all possible fields or error states), but it covers the main scenarios for a status-check 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?

With 0 parameters, the schema covers everything trivially (100% coverage). The description correctly avoids inventing parameter details, while the baseline of 4 is appropriate for a parameterless tool as specified in the rubric.

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 with a specific verb and resource: 'Returns connection status and URLs.' It further clarifies the output conditions (authenticated:true, pending[] empty, etc.), and the name 'connect' is distinctly different from siblings 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?

The description explains the tool's behavior under different credential states, giving implicit context on when to call it (e.g., when you need to check connection status). However, it does not explicitly mention alternative tools or state 'use this instead of...' or provide exclusions, so it leaves the comparison to the agent's inference.

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 discloses key behaviors beyond annotations: invoke runs tools even when not installed without bloating the tool list, returns a connect link for credentials, returns a checkout/top-up link for paid tools, and wraps a one-off install. It also clearly states permission requirements for writes, with no contradiction of 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 information-dense but delivered as one long, run-on paragraph with many chained clauses and em-dashes. It front-loads the core mission well, but the lack of bullet points or action-by-action structure makes it harder to parse than necessary for a tool with 14 actions and 23 parameters.

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 covers the full core flow, auth and permission requirements, credental/payment edge cases, install vs. invoke tradeoffs, and the separate prompt library. Without an output schema, it only partially describes return shapes, but for a complex hub-style tool it is remarkably complete. Minor gaps remain only in less-common params and exact response formats.

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 across 23 parameters, the description carries a heavy burden. It explains the action-driven params (search, describe, invoke, install, prompt-library actions) and their purpose, but leaves many parameters undocumented, such as cancel_reason, tier_slug, immediate, prompt_targets, report_context, and request_details. It gives strategic context but not complete per-parameter semantics.

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 is 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' with a specific core flow of search → describe → invoke. It distinguishes itself from sibling tools like report_bug and connect by enumerating its own actions and 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 gives explicit usage guidance: 'prefer invoke for a single/occasional use,' 'Use install only to make an MCP PERMANENT in the active toolkit,' and explains when to use report_bug, request_mcp, and the prompt library actions. It also states prerequisites for writes: 'require workspace owner/admin.'

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 read-only annotations, the description discloses additional behaviors: it requires prepaid credit, it accesses non-confidential public data from official Brazilian sources, and it states the client's data controller responsibility under LGPD, which provides meaningful transparency.

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 repetitive, repeating similar phrases such as 'consulta em fonte oficial' and 'consulta informação de fontes e órgãos oficiais', and it is presented as a single block without clear structure, making it less concise than necessary.

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?

While it provides some context (official source, non-confidential data, payment), it does not explain the input parameters (e.g., whether cpf or cnpj is required) nor the expected output format, leaving significant gaps for a user to understand how to use the tool 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?

The schema defines two parameters (cpf and cnpj) with zero description coverage, and the tool description does not mention them at all, leaving their meaning and usage completely unexplained. The description fails to compensate for the lack of schema detail.

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 that the tool performs a consultation of 'Certidão Negativa de Débitos' (negative debt certificate) from the official source of the Santa Cruz do Sul prefecture, making its purpose specific and 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 mentions the payment model ('pague por consulta com crédito pré-pago') and that it uses official sources, but it does not provide explicit guidance on when to use this tool versus alternatives or when to avoid it, lacking clear usage context.

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, but idempotentHint=true. The description aligns: reporting is a non-destructive, idempotent operation (sending feedback). It also adds that the conversation array should be included for reproduction, which is a behavioral requirement not in annotations. No contradiction 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 two sentences, front-loaded with purpose, and provides key usage detail. No wasted words. It is appropriately concise.

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 3 parameters, no output schema, and simple annotations. The description covers the purpose and the key parameter (conversation) but does not explain the context parameter or the expected format. However, the tool is simple (reporting feedback) and the description is sufficient for an agent to invoke it. Slight gap on context parameter prevents a 5.

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. The description mentions the conversation array and that message is required, but does not explain the context parameter or the exact format of the conversation string. It adds some value but leaves gaps. Since required parameter is message and the description says 'Include the conversation array', it partially covers semantics. Baseline 3 is appropriate.

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 bugs, missing features, or feedback. It specifies the resource (conversation array) and the action (report). It distinguishes from siblings like show_version or toolkit_info which are informational.

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: when there is a bug, missing feature, or feedback. It provides a specific guideline: include the conversation array for reproduction. However, it does not explicitly mention when not to use it or alternatives, but given the sibling tools are unrelated, the guidance is adequate.

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, indicating a safe, non-mutating operation. The description adds context by specifying what versions are shown (platform and adapter), but does not detail return format or potential errors. Given the strong annotation coveragechers, the description adds value beyond the annotations, so a 4 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 a single, concise sentence that conveys all necessary information without any redundancy. It is front-loaded with the key action and resource, and there is no wasted wording. Perfectly minimal and effective.

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 no parameters, no output schema, and strong annotations, the description is completely adequate. It covers the purpose and what it returns (versions). It could briefly mention that the output is informational and non-mutating, but the annotations already cover that. Thus, it is complete enough for its complexity.

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 has no parameter semantics to add. Per the rubric, a baseline of 4 is given for 0 parameters. The description is clear that the tool takes no input, which is consistent with the schema. Thus, it fully compensates for any missing parameter information.

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 the current MCP platform and adapter versions. It uses a specific verb ('show') and specifies the resource (platform and adapter versions), distinguishing it from siblings like toolkit_info which likely provides broader system information. This is a precise and unambiguous purpose.

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 version information, which is clear in context. It doesn't explicitly mention alternatives or when not to use it, but given the simplicity (no parameters) and distinct name, the intended use is obvious. It could improve by stating that this is a diagnostic tool for verifying environment versions, but it's sufficient.

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 established. The description adds valuable behavioral context by specifying exactly what state information is returned, including connection status and per-MCP account details, 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 sentence that front-loads the main purpose and then lists the key data points. Every word contributes meaning; there is no 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?

With no parameters, no output schema, and rich annotations, the description fully covers the tool's purpose and returned state items. It provides enough information for an agent to know exactly what this tool offers without additional explanation.

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 explain parameter semantics. The baseline of 4 applies because there is nothing for the description to compensate for.

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 ('Returns') with a clear resource ('current toolkit state') and enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from siblings like show_version and connect, which target different concerns.

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 the tool: whenever an agent needs an overview of installed MCPs, connection status, or connected accounts. It does not explicitly contrast with alternatives or state exclusions, but the context is clear enough for tool selection.

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