SEFAZ SP DEC: Caixa Postal

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

The description adds valuable behavioral context beyond annotations: it explains the browser-based login flow, tells the agent that a config header is non-expiring, and clarifies that session-only login requires pasting a token. It also notes the no-args invocation returns the link. No contradiction with idempotentHint=true.

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. Each sentence adds necessary information: what the tool is for, how to set up permanent auth, and how to perform session-only login. No unnecessary repetition 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?

For a simple one-parameter tool with no output schema, the description covers invocation modes and the intended workflow well. The main gap is that it does not describe what the tool returns when a token is provided, only that no-args returns the login link.

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 input schema only defines an optional string 'token' with no description. The description compensates by explaining that the token is a JWT to paste for session-only login and that omitting the token fetches the login link. It does not explain the token's format or where to obtain it in detail, but provides sufficient meaning for the single 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's action: authenticating by logging in through the browser, obtaining an access token, and either configuring it for permanent use or passing it as a JWT for session-only login. It differentiates itself from siblings by focusing on authentication and token exchange.

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?

Explicitly distinguishes between permanent setup via server config header and session-only usage by pasting a token. It also provides clear call patterns: with no args to get the login link, or with { token: "<jwt>" } after the user pastes the token.

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 adds valuable context about what the tool returns in different states (authenticated:true with empty pending[] vs. connect_url with per-install URLs), which goes beyond the annotations' readOnlyHint and idempotentHint. A slightly lower score is given because it could be more explicit about being read-only or safe to call, as implied by the annotations, but the state descriptions are a strong positive.

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?

At 51 words, the description is concise and gets straight to the point. But since there are no params or complex conditions to explain, it's a bit easier to be concise. The structure could be improved by front-loading the most important information, but the precision compensates for the slight lack of structural flair.

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 stateless, no-parameter tool, the description is remarkably complete. It could go slightly deeper on edge cases (e.g., behavior when a provider is in an error state) or the meaning of the URLs, but these are absent without any clear gaps. The description provides all necessary information for a developer 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?

With no parameters, there is no schema to cover, and the tool's behavior is independent of user input. The description completely covers the tool's lack of params, so a high score is warranted. A 4 is given because, although there are no params, the description effectively communicates the fixed behavior and return structure, fulfilling the spirit of the dimension.

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 is excellent—it clearly explains what the tool does (returns connection status and URLs), specifies the exact behavior when the system is in different states (all providers connected vs. credentials missing), and includes the exact parameter names and possible values. This level of detail makes the tool's purpose and usage extremely clear, far exceeding a minimum viable description.

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 there's some redundancy with the tool's name and the mention of 'connection status' in the description, the description itself is so precise that it negates the need for explicit when-to-use guidance. It mentions alternative tools or conditional usage ('When all providers are connected', 'When credentials are missing'), which effectively guides the user. However, it doesn't explicitly compare itself to siblings, hence the 4 instead of 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?

The description goes far beyond the basic annotations by explaining that invoke runs uninstalled MCPs one-off, returns connect or checkout links when credentials/payment are needed, does not bloat the tool list, and that writes require workspace owner/admin. These are meaningful behavioral disclosures the agent would not otherwise know.

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 long single paragraph, but every segment adds real information about a different action or behavioral rule. It is front-loaded and uses repetition like 'KEY' to emphasize the most important invoke behavior. Bullets would improve scannability, but the density is justified by the tool's polymorphic nature.

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 main user journeys, auth constraints, payment edge cases, installed-status flags, and the prompt library. Given the number of actions and parameters, it is quite complete. It is missing some minor action detail such as resume and it does not describe all return shapes, but the core flows are actionable.

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 carries a heavy burden. It explains the meaning of action well and even mentions tool_id and the flow behind arguments, but it does not map out many other parameters such as limit, tier_slug, immediate, cancel_reason, prompt_title, prompt_vars, request_details, and related fields. The compensation is good for the dispatcher core but incomplete for such a large parameter 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 is explicit about what the marketplace does: it is the official mcp.ai catalog and execution layer, covering discovery, profiling, invocation, installation, subscription management, and prompt-library lookups. It names concrete actions such as search, describe, invoke, install, and search_prompts, which gives the agent a precise mental model.

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 strong when/when-not guidance: use invoke for occasional one-off runs, use install only to make an MCP permanent, prefer search_prompts when the user wants prompt text rather than MCPs, and use request_mcp when nothing fits. It also explains the auth/payment retry flow and workspace-owner requirements for writes.

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 adds the requirement to include the conversation array for reproduction, which is useful behavioral context. However, it does not disclose what happens after reporting (e.g., ticket creation, notification, persistence). The annotations already provide idempotentHint=true and destructiveHint=false, so the safety profile is clear, but the description doesn't add much beyond the reproduction hint.

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 extremely concise—two short sentences that directly state the purpose and a key requirement. Every word earns its place, with no filler or repetition. It is well-structured, front-loading the primary purpose before the instruction.

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 3 parameters and no output schema, the description covers the main purpose and one parameter's role. However, it omits guidance on what to put in 'message' (the required field) and 'context'. Since the schema has no descriptions, this gap leaves the agent uncertain about how to populate all parameters, making the description less complete than ideal.

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 clarify parameter usage. It explicitly mentions the 'conversation' parameter and its purpose (recent messages for reproduction). However, it does not explain the required 'message' parameter or optional 'context' parameter. This partial compensation is helpful but incomplete, given that only one of three parameters is addressed.

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 identifies the resources (bug, missing feature, feedback). This distinguishes it from sibling tools like authenticate, connect, or marketplace, 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 provides clear context for when to use the tool: when reporting a bug, missing feature, or giving feedback. It also gives a specific instruction: 'Include the conversation array with recent messages for reproduction.' However, it does not explicitly mention when not to use it or suggest alternatives, leaving room for a higher score if exclusions were stated.

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 destructiveHint. The description adds context about LGPD compliance and that data is not confidential, which is helpful, but it doesn't disclose other behaviors like response format, error handling, or rate limits. Overall, it adds some value beyond annotations but remains thin.

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 few sentences and not excessively long, but it is a bit convoluted with legal and payment details that could be streamlined. It is reasonably front-loaded with the core action but lacks clear structure.

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 absence of parameter descriptions, no output schema, and a vague purpose, the description is incomplete for an agent to understand the tool's inputs, outputs, or prerequisites. It fails to compensate for the sparse 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?

Schema description coverage is 0% and the description does not explain any of the 4 parameters (cnpj, pkcs12_cert, pkcs12_pass, ignora_nao_lidas). With no param information in either the schema or description, an agent cannot correctly fill required fields.

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 it performs a consultation ('consulta') on an official source for 'Caixa Postal' (mailbox), but the term is ambiguous and the exact resource/action is unclear. It doesn't distinguish from sibling tools beyond being a query, and lacks specificity about what data is retrieved.

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 payment per query and no platform credentials, which are useful operational hints, but it gives no guidance on when to use this tool vs alternatives. There are no exclusions or explicit 'when not to use' criteria.

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, fully covering the safety profile. The description aligns with these annotations and adds the 'current' qualifier, reinforcing that it is a non-mutating read of current state.

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 with no wasted words. It is front-loaded with the action 'Show' and immediately states the object of interest.

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 (no parameters, no side effects, clear purpose), the description is sufficient. No output schema exists, but the description's clarity covers what the agent needs to know to invoke it.

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 covers everything. Per the rules, a baseline of 4 is appropriate when there are no parameters, and the description does not need to add 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 verb and resource: 'Show' the 'MCP platform and adapter versions'. It is specific and unambiguous, and it is distinct from siblings like authenticate and marketplace, which have 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?

While no explicit alternatives are mentioned, the tool's simplicity and self-evident use case (checking versions) make its usage context clear. The description implies when to use it (when version information is needed) without needing 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=true and destructiveHint=false, so the safety profile is fully covered. The description adds behavioral detail by specifying the type of information returned (connection status, accounts, tool counts), but does not cover potential performance implications or any caveats about state freshness. Given the excellent annotation coverage, the additional detail earns a high score.

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 conveys all necessary information without filler. It follows a clear structure: action, object, and constituent details. There is zero waste and perfect clarity.

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 read-only info tool with no parameters and no output schema, the description provides a complete picture of what the agent will get. Annotations cover the safety aspects, and the description enumerates all returned components. Nothing is left ambiguous or missing.

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 parameter documentation is trivially complete. The schema declares an empty object, and the description explains what is returned without needing parameter explanations. There is nothing missing here.

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 action (returns) and the specific object (current toolkit state) detailing exactly what fields are included: installed MCPs, connection status, accounts, and catalog tool counts. This is unambiguous and provides a comprehensive scoping of the tool's 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 provides implicit guidance that this is for inspecting toolkit state, but it does not explicitly state when to use it versus sibling tools like authenticate or connect. No prerequisites or conditions are mentioned, leaving some inference required, though the context and read-only nature make it reasonably clear.

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