Prefeitura PR Maringá: Certidão Negativa de Débitos (Contribuinte)

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

Annotations indicate idempotentHint=true, meaning repeated calls are safe. The description adds behavioral context: it explains that calling with no args returns a login link, calling with a token establishes a session, and it warns about token expiry (session-only vs permanent). It doesn't contradict annotations; it complements them by detailing the flow and outcomes.

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 but packs multiple instructions (login link, token paste, permanent vs session). It's slightly dense but front-loads the primary purpose and uses parentheses for secondary details, keeping it structured. Could be split for readability but remains efficient.

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 (1 optional param, no output schema), the description covers the essential flow: how to authenticate, two methods (config vs session), and the call variants. It doesn't describe return values, but since there's no output schema (output likely a URL or success message), the absence is acceptable. Idempotency is implied by annotations and description's clarity.

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 (0% coverage). The description compensates by explaining the token's purpose: to be pasted after the user copies it from the browser. It clarifies that the token is a JWT and that omitting it triggers a link generation, adding meaning beyond the bare schema.

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 the tool's purpose: authenticating IDE agents like Cursor via browser login and token exchange. It clearly distinguishes from siblings like 'connect' and 'marketplace' by focusing specifically on token-based authentication for the MCP server.

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 when-to-use guidance: use for logging in to the MCP server, either via a permanent config header or a session-based token. It also explains the two invocation modes (with or without token) and contrasts with alternatives like 'connect' for general connectivity, making usage clear.

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. The description adds valuable context about conditional output (e.g., authenticated:true vs connect_url) that goes beyond the annotations, providing insight into response behavior.

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 main purpose and followed by conditional details. Every sentence adds value with no fluff or redundancy.

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 tool with no parameters and no output schema, the description explains the key return scenarios (all connected vs missing credentials). However, it does not cover partial connection states or the exact structure of URLs, leaving some ambiguity.

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 fully covers parameter semantics. The description does not need to explain parameters; the baseline of 4 is appropriate for this no-parameter scenario.

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 that the tool returns connection status and URLs, with specific details about behavior when all providers are connected versus when credentials are missing. This clearly distinguishes it from the sibling 'authenticate' tool, which likely performs authentication rather than reporting status.

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 connection status but does not explicitly state when to use this tool versus alternatives such as 'authenticate'. It lacks clear when-to-use/when-not-to-use guidance, though the context is self-evident.

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 goes well beyond the sparse annotations by disclosing that writes require workspace owner/admin, invoke works even when the MCP is not installed, invoke avoids bloating the toolkit, and auth/payment failures return actionable connect/checkout links. No contradiction with readOnlyHint=false, openWorldHint=true, or destructiveHint=false.

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 and front-loaded with its core purpose, but it is one long run-on paragraph with semicolon-heavy clauses. Most sentences contain useful information, but the lack of bullet points or per-action structure makes it harder to scan and 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?

For such a complex multi-action tool, the description covers the core search→describe→invoke flow, install-vs-invoke semantics, auth and billing behavior, the prompt library, and auxiliary actions like request_mcp and report_bug. However, a few action enum values such as resume and the immediate flag are not explained, so completeness is strong but not total.

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 23 parameters and 0% schema description coverage, the description must compensate, and it does only indirectly. It explains the meaning of action values, the need to pick tool_id after describe, and prompt_vars/{{variables}} in the prompt library, but many parameters such as immediate, tier_slug, cancel_reason, request_details, conversation, and prompt_targets are left without meaningful explanation.

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 mcp.ai marketplace" — both a catalog of MCPs/tools and the way to run them. It distinguishes itself from siblings by centering on search/describe/invoke/install flows, rather than authenticate, connect, or toolkit_info.

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 guidance: "prefer invoke for a single/occasional use" and "use install only to make an MCP PERMANENT." It also explains when to use search, describe, invoke, subscribe/cancel, report_bug, and request_mcp, plus the retry-after-connect/checkout-link workflow.

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, idempotentHint, and destructiveHint=false. The description adds that it is a paid query, hosted by the platform without credentials, and clarifies LGPD compliance. It also states the data is not confidential, which is useful. No contradictions with annotations; description adds behavioral context beyond 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 block of text with three sentences. It is relatively concise but includes some redundancy (e.g., 'consulta em fonte oficial' and later 'fontes e órgãos oficiais brasileiros'). It is front-loaded with the main purpose, but the sentence about LGPD could be seen as extraneous for tool description.

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 is a read-only query with some legal and payment context, the description covers essential information such as payment, data source, and LGPD compliance. However, with no output schema and zero parameter descriptions, it lacks completeness regarding input expectations and return format. The absence of any output schema makes it harder to know what the result contains.

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% and there are 6 parameters with no descriptions in the schema. The description does not explain any parameter semantics; it only hints at CPF/CNPJ usage by mentioning taxpayer. It does not clarify parameters like finalidade, nome_requerente, or the requester fields. This is a significant gap.

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 states the tool performs a CND consultation (Certidão Negativa de Débitos) for taxpayers in Maringá-PR, with a clear verb ('consultar') and resource (debt clearance certificate). It also clarifies the data source (official Brazilian sources) and type of data (non-confidential). However, it does not explicitly differentiate from sibling tools, but siblings are generic system tools, so no real overlap.

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 that payment is required via prepaid credits and that the client is the data controller under LGPD, implying use cases. However, it does not state when to use this tool versus alternatives, nor provide explicit conditions or exclusions. The context is somewhat clear but lacks alternative 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 provide basic behavioral hints (readOnlyHint=false, idempotentHint=true, destructiveHint=false). The description adds context about including the conversation array for reproduction, which is useful, but it does not disclose the actual effects of the report (e.g., whether a ticket is created, if data is sent externally). No contradiction with annotations exists.

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 purpose and followed by a key instruction. Every word earns its place; there is no fluff or irrelevant detail.

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 (3 params, no output schema), but the description leaves gaps: it doesn't clarify the 'context' parameter, nor does it explain what happens after reporting (e.g., return value or acknowledgement). Annotations mitigate some concerns, but the description is not fully 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?

Schema descriptions are completely absent (0% coverage), so the description carries the burden for parameter meaning. It gives meaningful context for the 'conversation' parameter ('recent messages for reproduction') but says nothing about 'message' or 'context.' This partial clarification is helpful but does not fully compensate for 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' combined with the resource types (bug, missing feature, feedback) is specific and differentiates this tool from sibling tools like authenticate or show_version, which serve entirely 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?

The description does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or conditions. The intended usage is implied by the purpose (reporting feedback), but there is no guidance on conflict with other tools. Since none of the siblings handle reporting, the usage is fairly obvious, but the description lacks explicit instructions.

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 well covered. The description adds meaningful context by specifying exactly what is shown (platform and adapter versions), which goes beyond the annotations 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?

The description is a single, focused sentence that states exactly what the tool does. There is no wasted wording, redundancy, or unnecessary detail.

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 low complexity, zero parameters, and rich annotations, the description fully covers what the agent needs to know. No output schema exists, but for a simple version-reporting tool, the description is sufficiently 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 tool has zero parameters, and the schema is empty, so the description has no parameter semantics to explain. Per the baseline for zero-parameter tools, a score of 4 is appropriate since the description is clear and no additional parameter detail 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 a specific verb ('show') and a clear resource ('current MCP platform and adapter versions'), making the tool's function immediately understandable. It also distinguishes itself from siblings like authenticate and connect, which have clearly 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 implies the tool should be used when version information about the MCP platform or adapters is needed, but it provides no explicit guidance about when not to use it or alternatives. For a simple version-check tool, the implied usage is acceptable but not fully explicit.

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. The description adds value by specifying the exact contents of the returned state (MCPs, connection status, accounts, catalog counts). It clearly indicates a read-only inspection tool, and the description aligns with the annotations without contradictions.

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, information-dense sentence. It lists four specific components of the state without any filler. This is appropriately concise and front-loaded, stating the purpose immediately and then elaborating.

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 zero parameters correspondently handled, no output schema (but the description enumerates the return fields), and rich annotations, the description fully covers the tool's function. There is no missing context that an agent would need to safely and effectively call this 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?

There are no parameters (schema has zero properties). The description does not need to explain any parameters in the description because there are none. According to the rubric, 0 params = baseline 4; here the description is complete and speaks to the return value instead, adding meaning beyond the schema (which is empty). So a 5 is justified.

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 unambiguously states the tool's action ('Returns the current toolkit state') and enumerates exactly what that state includes: installed MCPs, connection status, accounts, and catalog tool counts. There is no ambiguity about what this 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?

While the description doesn't explicitly mention when to use this tool relative to siblings, the nature of a read-only status tool is self-evident. The sibling list contains other info tools like show_version, but the description sufficiently conveys its purpose without needing explicit guidance. Minor gap: no mention of related tools or prerequisites, but with zero parameters, the tool is simple to call.

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