SEFAZ PR: Dívida Ativa

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

The description adds substantial behavioral context beyond the annotations: token handling, permanent non-expiring config header vs temporary session login, and no-args link retrieval. It makes the tool's side effects and state implications clear, and it does not contradict 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 compact and information-dense: every sentence supports the tool invocation or setup, and it is front-loaded with the target audience and login flow. The phrasing is not overly verbose and avoids repeating the tool name or title.

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 has one optional parameter and no output schema, the description covers the main invocation paths and config-recommendation behavior well. It could be slightly more complete by stating what a successful token-based call returns or how to handle an invalid token, but it remains effective for 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?

With 0% schema description coverage and only one optional parameter, the description fully compensates by showing the expected syntax `{ token: "<jwt>" }`, explaining the token is a JWT, and clarifying that calling with no arguments is valid and returns the login link. It adds real semantic meaning beyond the bare type declaration.

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 conveys an authentication flow: log in in the browser, copy the access token, and either call with a token or with no arguments to get a link. It is much more specific than the tool name alone, but it does not explicitly distinguish this from the sibling tool `connect`, so it misses the strongest level of differentiation.

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: use no arguments to get the login link, paste the token for a session-only login, and preferably add the token to the server config as a permanent header. It also clearly explains the trade-off between the permanent connection and session-only login, which is exactly the kind of practical guidance an agent needs.

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. The description adds useful conditional details: when all providers are connected returns authenticated:true and empty pending[], and when credentials are missing returns connect_url plus per-install URLs. This goes beyond 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 concise and well-structured: one sentence states the overall purpose, then two sentences describe the main conditional outputs. Every sentence carries useful information with 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?

The description covers the two primary states (all connected vs. missing credentials) and explains the return payloads meaningfully. Given the simple zero-parameter interface and no output schema, this is mostly complete. It does not explicitly describe a partial-connection state, but the provided conditions are sufficient for the intended status-check use case.

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 zero parameters, so there is no meaningful schema information to supplement. The description appropriately focuses on output behavior instead of inventing parameter details.

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' and clearly identifies the resource as connection status and URLs. It differentiates from sibling tools like 'authenticate' by describing this as a status retrieval operation rather than an authentication action.

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 clear context by explaining what results appear under different connection states, implying this tool is used for checking whether authentication is complete. It doesn't explicitly name alternatives or say when not to use it, but the behavioral conditions convey its diagnostic role well.

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 note readOnlyHint=false and openWorldHint=true, but the description adds important behavioral context: invoke can run MCPs without installation, returns connect/checkout links for auth/payment, and requires workspace owner/admin for writes. It also explains side effects like not bloating the tool list. Minor gaps: no explicit mention of idempotency or failure modes, but the description is quite transparent.

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 comprehensive, covering many actions and scenarios, but it is a single long paragraph without clear breaks or front-loaded summary. It earns its place for the most part, but could be more scannable with lists or sectioning. It is not overly verbose relative to the tool's breadth.

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 23 parameters prescription, no output schema, and no per-parameter documentation, the description is remarkably complete: it explains the core flow, edge cases (auth, payment, writes requiring admin), and the prompt library. Minor omissions: no detail on parameters like 'limit', 'immediate', or 'tier_slug' beyond their existence, but the description covers the main usage comprehensively.

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 key parameters like action (lists all enum values with semantics), mcp_id, tool_id, arguments, and prompt-related params. It does not detail every parameter (e.g., limit, immediate, tier_slug), but covers the most critical ones, enabling correct 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 is 'the official mcp.ai marketplace' for discovering and running MCPs, enumerates its primary actions (search, describe, invoke), and distinguishes it from sibling tools like authenticate and connect. It covers the full scope of the marketplace and the prompt library, providing a specific verb+resource for each action.

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: use 'invoke' for one-off runs even if not installed, use 'install' for permanent toolkit inclusion, and states 'prefer invoke for a single/occasional use'. It also details the core flow (search → describe → invoke) and covers edge cases like auth and payment links, which clarifies when to use each action.

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 non-destructive, idempotent, and non-read-only. The description adds the requirement to include a conversation array for reproduction, which is extra context beyond annotations. However, it does not disclose what happens after reporting (e.g., confirmation, ID returned), so it adds limited 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?

Two concise sentences, front-loaded with the core purpose and a practical hint about the conversation. No redundant information or fluff; every word serves a 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?

For a simple reporting tool with no output schema, the description covers the purpose and a key input but omits details about outcomes or return values. Given the low complexity and available annotations, it is adequate but not fully complete—more could be said about expected behavior after submission.

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 has zero description coverage, so the description must compensate. It explains the conversation parameter's purpose (for reproduction) but leaves 'message' and 'context' without explicit explanation. It adds some value but does not fully clarify all parameters, earning a middle score.

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 reports bugs, missing features, or feedback, with a clear verb and resource. It distinguishes from siblings like authenticate or connect by focusing on issue reporting, and even hints at a key input (conversation) for reproduction.

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 purpose clearly implies when to use (when a user wants to report an issue or send feedback). There are no explicit alternatives or exclusions, but the context is clear and the tool is specialized for this task, making usage 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 state readOnlyHint=true and idempotentHint=true, but the description adds valuable context: payment model ('pague por consulta com crédito pré-pago'), no platform credentials needed, and LGPD data control responsibilities. This goes beyond what annotations provide.

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 of four sentences, each serving a distinct purpose: primary function, hosting/payment, data source/confidentiality, and LGPD responsibility. It is front-loaded with the core purpose and contains no unnecessary 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?

The tool has only two parameters and no output schema; annotations cover safety. The description covers payment, auth context, and legal aspects. However, it omits any hint about the response format or edge cases, and lacks parameter definitions, leaving some gaps for a simple query 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?

Schema coverage is 0%, so the description must compensate for parameter explanations, but it does not explain 'renavam' or 'ano'. While the names suggest vehicle registration and year, the description provides no explicit definitions, leaving the agent to infer 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 identifies the tool as a query ('consulta') for SEFAZ PR Dívida Ativa information from official Brazilian sources. The specific resource and action are stated, and it stands apart from sibling tools which are platform-level utilities (authenticate, connect, etc.).

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 when SEFAZ PR active debt information is needed and explains important conditions: it's hosted by the platform, requires no platform credentials, and costs prepaid credits per query. While it doesn't explicitly compare to alternative tools, the siblings are unrelated, so the context is clear enough.

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, idempotent, and non-destructive. The description adds context beyond annotations by specifying exactly what versions are shown (platform and adapter). This adds value without contradicting anything. It does not discuss return format, but for a no-parameter info tool, this is sufficient.

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 with no filler. It efficiently communicates the tool's function without any waste.

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 the lack of an output schema, the tool is trivial: no parameters, no side effects, and the description fully covers what it does. Annotations cover safety, and the description covers the return contents. For a simple version checker, this is 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, so the baseline is 4 per the rubric. The description adds nothing about parameters (none exist), and the schema is empty, which is consistent. No additional parameter documentation 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 verb 'show' and a specific resource ('current MCP platform and adapter versions'). It is unambiguous and distinct from siblings like authenticate or connect, though it doesn't explicitly contrast with toolkit_info, which might also show info. Still, the purpose is specific and self-contained.

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 tool's purpose inherently defines its usage—when you need to check versions. It does not explicitly state when not to use it or mention alternatives, but in a small sibling set (authenticate, connect, marketplace), the context is clear. A mention of toolkit_info as an alternative would be a slight improvement, but not critical.

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, signaling a safe read operation. The description adds value by specifying exactly what the state contains—installed MCPs, connection status, linked accounts, and catalog counts—which goes beyond the raw annotations. This contextual detail helps set expectations for the return value without needing to describe side effects or errors, making 4 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, well-structured sentence that front-loads the primary action ('Returns the current toolkit state') before listing specifications with colons and commas. Every phrase earns its place with no fluff. It is concise yet comprehensive, perfectly sized for its 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?

For a simple read-only info tool with no output schema, the description is remarkably complete. It enumerates the return context (installed MCPs, statuses, accounts, catalog counts) and pairs with annotations that confirm safety. There are no hidden behaviors or parameter interactions to disclose, and the lack of an output schema is fully compensated by the explicit content listing. The description leaves no unanswered questions for the intended use case.

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 zero parameters, there is no schema to document and nothing to elaborate on. The rubric prescribes a baseline score of 4 for zero-parameter tools, as the description cannot add parameter-level detail. This rationale applies here, yielding a 4.

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 ('Returns') and a well-defined resource ('current toolkit state'). It details the exact data points included (installed MCPs, connection status, accounts, count of catalog tools), leaving no ambiguity about the tool's purpose. This differentiates it from its siblings, which cover authentication, connectivity, and other separate 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 provides clear context on when to use the tool: whenever an agent needs to understand the toolkit's current state, including connections and exposed catalog counts. No explicit alternatives or exclusions are stated, but the purpose is specific enough that usage guidance is implicitly obvious. Since no sibling comparison is given, it falls short of a 5 but earns a 4 for clear contextual cues.

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