SEFAZ PB: Emissão Dar

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

Annotations indicate idempotentHint=true and destructiveHint=false, and the description aligns with these. It explains two authentication flows (browser link and token submission) and notes the difference between permanent (config) and session-only (token) connections. It does not mention success/failure details, but the idempotent property is respected. Adds context beyond annotations about how the login link is obtained.

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 paragraph. It front-loads the purpose and then clearly delineates the two usage modes. Every sentence adds value without redundancy. It is concise yet informative, balancing detail and brevity.

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 moderate complexity, no output schema, and limited annotations, the description covers the essential behaviors: how to authenticate, the two methods (permanent and session), and the context for IDE agents. It could detail what the returned link looks like or error cases, but the core usage is fully specified. Overall, sufficient for an agent to invoke it 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 schema has one optional parameter 'token' with no description (0% coverage). The description compensates by explaining its purpose: 'call with { token: "<jwt>" } after the user pastes, or with no args to get the link.' This clarifies the token is a JWT for session-only login and that omitting it triggers link generation. Provides meaning beyond the 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 clearly states the tool's purpose: to authenticate the user via browser login or token. It specifies the resource (MCP.AI server) and the action (authenticate/log in), and distinguishes from siblings like 'connect' or 'marketplace' by focusing on credential establishment.

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 instructions on when to use each mode: 'Best: add it to this server's config as a header...' for permanent connection vs. 'Or paste it here for a session-only login...' It also clarifies that calling with no args returns a link, and with token it authenticates. This gives clear usage context and alternatives.

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 the tool as read-only, idempotent, and non-destructive. The description adds behavioral context by specifying conditional return values (authenticated:true or connect_url depending on credential state), 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 two sentences long, front-loaded with the primary purpose, and contains no redundant information. Every clause adds 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?

With no parameters and no output schema, the description covers the main return scenarios (all connected vs. missing credentials). It does not handle partial connectivity explicitly, but for a simple status-check tool, this is nearly 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?

There are zero parameters, so the schema provides full coverage. The description does not need to explain parameter semantics, and it appropriately focuses on output behavior 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 states that the tool returns connection status and URLs, using a specific verb and resource. It distinguishes itself from siblings like 'authenticate' by focusing on reading status rather than performing authentication actions.

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 implicitly establishes when to use the tool: to check connection status and obtain URLs depending on credential state. It does not explicitly exclude alternatives or name sibling tools, but the context is clear enough for an agent.

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 far exceeds the sparse annotations (readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false). It discloses the critical one-off invoke behavior (runs without installing, no toolkit bloat), the auth (connect link) and payment (checkout/top-up link followed by retry) fallbacks, workspace owner/admin permission requirements for writes, and the installed_in_toolkit vs installed_in_workspace flag distinction. 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?

Every sentence earns its place — there is genuinely no filler — but the entire description is one unbroken wall of text covering 14 actions plus the prompt library. For such a large action surface, it should be structured with section breaks or bullets. It front-loads the core flow early (search → describe → invoke), which helps, but the dense single-paragraph format hurts 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?

For a tool with 23 params, 14 actions, no output schema, and minimal annotations, the description is remarkably complete. It covers the multi-step workflow, the security model (owner/admin gates), the install-vs-invoke semantics, auth/payment retry behavior, and the separate prompt library subsystem — all essential for correct agent use. The only gap is return-value shape, but given no output schema exists and the behavioral surface is so thoroughly covered, this is a strong 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 coverage is 0%, so the description must compensate, and it does: all 14 action enum values are explained within the flow narrative, and the prompt_* params are contextualized via the prompt library section. However, several params receive no individual treatment (immediate, conversation, limit, prompt_targets, request_details), relying on the agent to infer their meaning from the action descriptions. Strong compensation, but not exhaustive for a 23-param surface.

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 states the tool is "the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them," a specific verb+resource with clear scope. It enumerates capability requests it handles ("find an MCP that does X", "consulta um CPF") and outlines the core search→describe→invoke flow, distinguishing itself from sibling tools by being the central hub that both catalogs and executes MCPs.

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 when-to-use guidance: "prefer invoke for a single/occasional use" vs "Use install only to make an MCP PERMANENT in the active toolkit." It names alternatives directly (request_mcp when nothing fits, list_tools for currently-callable tools, search_prompts for prompt text) and states the retry protocol after connect/checkout links. This is textbook usage differentiation.

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 include readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description doesn't contradict these. It adds context that the tool is for reporting and that conversation data is needed for reproduction, which is useful. However, it doesn't disclose what happens after reporting (e.g., whether it creates a ticket, sends an email, etc.), and with no annotations for openWorldHint, the description could add more behavioral context. The bar is lower because annotations exist, but the description adds minimal extra behavioral detail beyond the purpose.

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 includes a specific instruction about the conversation array. Every sentence earns its place; no fluff. It's concise and 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?

The tool has 3 parameters, no output schema, and annotations that are minimal. The description covers the purpose and hints at the conversation parameter's role, but it doesn't explain the 'context' parameter or what happens after submission. Given the simplicity of the tool (reporting), it's adequate but could be more complete by explaining the expected format of 'message' or 'context' and the outcome.

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 'conversation array' and 'recent messages', which adds meaning to the 'conversation' parameter. However, it doesn't explain 'message' or 'context' parameters beyond what the schema provides (type and default). The description adds some value for the conversation parameter but not for the others, so it partially compensates for the low 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's purpose: 'Report a bug, missing feature, or send feedback.' It uses a specific verb ('report') and resource ('bug'), and distinguishes from siblings by covering feedback and missing features, which are not covered by other tools like authenticate or show_version. However, it doesn't explicitly differentiate from a generic 'feedback' tool, but given the sibling list, it's clear enough.

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 it: when reporting bugs, missing features, or feedback. It doesn't explicitly state when not to use it or mention alternatives, but the context is clear. The instruction to 'Include the conversation array with recent messages for reproduction' provides usage guidance for the conversation parameter, but no explicit exclusions or alternatives are given.

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, non-destructive, idempotent behavior. The description adds meaningful context: the query is paid with prepaid credit, requires no platform credentials, returns only non-confidential information available to citizens, and places LGPD responsibility on the client. 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 compact and front-loaded with the tool's purpose, followed by payment, data source, and legal context. It is slightly repetitive around the 'official source' idea, but overall each sentence contributes useful operational context.

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 important context such as payment model, credential requirements, data sensitivity, and LGPD responsibility. However, it does not explain what the consultation returns or how the four parameters should be used, and there is no output schema to compensate.

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 the description does not explain the roles of placa, renavam, cpf, or cnpj. The parameter names are self-explanatory to a Brazilian audience, but the description adds no guidance about required combinations, formats, or selection logic.

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 identifies the tool as a consultation on the official SEFAZ PB DAR source, using the verb 'consulta' and naming the resource. It does not explicitly differentiate from sibling tools, but the sibling tools are generic platform utilities, so the domain-specific purpose is reasonably clear.

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 no explicit guidance on when to use this tool versus alternatives. It mentions that it queries official Brazilian sources and that no platform credentials are needed, but it does not state use cases, exclusions, or prerequisites beyond payment.

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 the tool as read-only, idempotent, and non-destructive. The description adds the relevant scope beyond that by specifying that the tool reports both MCP platform and adapter versions, which provides additional behavioral detail about what the user will get. The description does not contradict 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 uses no unnecessary words. Every word contributes to meaning, and the key information is clearly front-loaded.

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 tool with no parameters, no output schema, and minimal annotations, the description fully covers the needed context: the tool reports the current platform and adapter versions. The annotations establish safety and idempotency, so nothing more is required.

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 empty schema trivially achieves 100% coverage. Per the rubric, 0 parameters warrants a baseline score of 4. There is nothing for the description to add in terms of 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 uses a specific verb ('Show') and clearly identifies the resource ('the current MCP platform and adapter versions'). This is unambiguous and easily distinguished from sibling tools like authenticate, connect, 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 implies a straightforward usage scenario: when you need to know the current platform and adapter versions. There are no exclusions or alternatives mentioned, but for a simple version-check tool with no siblings serving a similar purpose, a clear and self-evident context is 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?

The annotations ('readOnlyHint: true', 'destructiveHint: false', 'idempotentHint: true') already declare this is a safe, read-only operation. The description adds context beyond the annotations by specifying the exact scope of what is returned, but does not reveal further behavioral details (e.g., latency, whether it makes network calls).

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 sentence that perfectly balances detail and brevity. It front-loads the core function and then enumerates a clear list of return values 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?

For a zero-parameter, read-only tool with comprehensive annotations and a clear description, this is complete. The description fully compensates for the lack of an output schema by explicitly describing what the state check covers, and no additional context is needed for an agent to successfully invoke 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?

With zero parameters in the schema, there are no parameters to document. The baseline of 4 is appropriate here since the description and schema are both minimal and complete.

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 opens with a specific verb ('Returns') and a specific resource ('the current toolkit state'), then enumerates exactly what that state includes ('installed MCPs, their connection status, the accounts connected to each one, and how many catalog tools each exposes'). This level of specificity clearly distinguishes it from siblings like 'show_version' and '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 implies a clear use case (checking status of the toolkit) without explicitly naming alternatives. However, by listing exactly what is returned, it becomes clear this is the diagnostic/status tool among the siblings, leaving 'authenticate', 'connect', and 'marketplace' for their respective mutation/action roles.

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