Receita Federal Sistema de Acréscimos Legais (SAL): Dados Cadastrais

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

Annotations already mark idempotent and non-destructive; the description adds that config-header auth is permanent/non-expiring while pasted-token auth is session-only, and that no-args returns a login link. 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?

Two sentences pack purpose, two auth strategies, and invocation patterns without fluff. The description is front-loaded with the tool's purpose and remains highly scannable.

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 one-optional-param auth tool with no output schema, the description covers the flow, permanence trade-off, and no-args behavior. A minor gap is not describing the success response when a token is provided or how this relates to the sibling 'connect' 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?

The schema only defines an optional string token with no description, so the description carries the full burden. It compensates by explaining the token is a JWT to paste and that omitting it returns the login link.

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 the MCP.AI server for IDE agents, with a browser-login/token-copy flow. It distinguishes two auth modes but doesn't explicitly contrast with the sibling tool 'connect'.

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 recommends a permanent config-header approach versus a session-only pasted token, and specifies exact call patterns: call with { token: "<jwt>" } after the user pastes, or with no args to get the link. This is strong when-to-use 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?

Beyond the readOnly and idempotent annotations, the description reveals specific behaviors: returns authenticated:true and empty pending[] when all providers are connected, and returns connect_url when credentials are missing.

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?

Description is concise, two sentences, and directly covers the tool's purpose and key behaviors without 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?

Even without an output schema, the description fully explains the return values (authenticated, pending, connect_url) and the conditional scenarios, making it complete for the user.

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?

No parameters exist, so schema coverage is complete; baseline score of 3 applies, and no additional parameter explanation 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?

Clearly states the tool returns connection status and URLs, which is specific and distinguishes it from sibling tools 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?

Implies usage for checking connection status, but does not explicitly state when to use this tool versus alternatives like authenticate or show_version.

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 behavioral traits beyond annotations, such as invoke running one-off without installation, returning connect/checkout links when credentials or funds are missing, and requiring owner/admin for writes. It matches the readOnlyHint=false and openWorldHint=true annotations, adding valuable context about auth, payment, and installation side effects.

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 lengthy but information-dense; every sentence adds value by covering the core flow, key distinctions, auth/payment, and the prompt library. It is not overly redundant, though it could benefit from more structured bullet points for the various actions.

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 parameters and no output schema, the description covers essential behaviors, use cases, constraints, and the two-tier installation model, including auth, payment, admin roles, and the prompt library. It is sufficiently complete for an agent to select and invoke tools 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 0% schema coverage, the description compensates by explaining the purpose of core parameters (action, mcp_id, tool_id, arguments, prompt variables) within the narrative, mapping them to the flow. It does not enumerate all 23 parameters, but it gives enough contextual meaning for the main ones, though not exhaustive.

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, enumerating its core actions (search, describe, invoke, install, etc.) and distinguishing it from sibling tools by covering the entire MCP lifecycle and prompt library. It specifies the exact verb+resource scope and separates it from alternatives like authenticate/connect.

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 guidance on when to use each action: search→describe→invoke flow, prefer invoke over install for one-off use, install for permanent toolkit addition, and when to use subscribe/cancel, report_bug, request_mcp, and prompt functions. It also notes admin requirements for writes and how to handle connect/checkout links.

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 annotations (readOnlyHint, idempotentHint, destructiveHint false), the description adds critical context: 'sem credenciais da plataforma' (no platform credentials), 'pague por consulta com crédito pré-pago' (pay per query with prepaid credit), and LGPD data controller responsibilities. This enriches the agent's understanding of cost, authentication, and legal handling.

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 front-loaded with the purpose statement, followed by operational and legal context. It is not overly long, but some sentences (e.g., 'Hospedado pela plataforma') could be trimmed. Overall, it is organized and each sentence adds some 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 output schema, the description should explain what data is returned, but it only vaguely says 'Dados Cadastrais'. It omits return structure, error conditions, and example usage. Given the tool's simplicity, it is still incomplete for an agent to fully anticipate outcomes.

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 mention the 'pis' parameter or its meaning. This is a single-parameter tool, and the description fails to explain what PIS is or how to provide it, leaving the agent without necessary semantic 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 it is a 'consulta' (query) for 'Dados Cadastrais' (registration data) from the Receita Federal SAL system. It distinguishes itself from sibling tools, which are meta/utility tools (authenticate, connect, etc.), not data lookup tools. However, it could be more explicit about the specific resource and what data is returned.

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?

No explicit guidance on when to use this tool versus alternatives. While siblings are not similar, the description does not state a clear use case (e.g., 'use this when you need PIS registration data'). It mentions platform hosting and payment but does not provide exclusions or prerequisites.

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 behavioral context by requiring the conversation array for reproduction, which goes beyond the schema. Annotations already indicate it's non-readOnly and idempotent, and the description does not contradict 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 only two sentences, with the purpose front-loaded and no filler. Every sentence contributes 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?

The tool is simple and the description covers its purpose and key usage. It lacks detail on the context parameter and post-submission behavior, but given the annotations and simple schema, this is adequate.

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 the conversation parameter, but not the context parameter, and does not clarify the exact format of the conversation array beyond being a string.

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 a bug, missing feature, or feedback, which is a specific verb+resource. This distinguishes it from sibling tools like authenticate or connect.

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 this tool (reporting issues) but does not explicitly mention when not to use it or point to alternatives. The instruction to include the conversation array also guides usage.

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 description correctly implies a safe read operation. However, it adds no further behavioral details such as the format or structure of the returned version information. The description is consistent with annotations, but does not enrich 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, front-loaded sentence with no filler words. It conveys the essential information in the most efficient way possible.

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 output schema), the description is adequate to convey its function. It could have specified the exact return format or what 'adapter versions' refers to, but for a version-check tool, the current level is 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?

The tool has zero parameters, so the baseline of 4 applies. There is nothing to describe, and the description does not need to compensate for schema coverage since there are no 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 the specific verb 'Show' and references the resource 'MCP platform and adapter versions', clearly distinguishing it from siblings like authenticate, connect, or marketplace. It is unambiguous and immediately tells the agent 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?

The description does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention exclusions. Usage is implied (e.g., when version info is needed), but it lacks explicit context or alternative references.

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, so the safety profile is covered. The description adds valuable context about the exact information returned (installed MCPs, connection status, accounts, catalog counts), which is beyond what annotations provide. It 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?

A single sentence that is front-loaded with the action and resource, and it enumerates all key return elements without redundancy. Every word adds value, making it highly 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 no parameters and no output schema, the description fully covers the tool's functionality and expected output. It specifies the scope of the returned state (installed MCPs, connection status, accounts, catalog counts) which is sufficient for an agent to use the tool appropriately.

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, the schema is fully covered and there is nothing to explain. The baseline score of 4 applies as no parameter descriptions are needed; the tool requires no inputs.

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 ('current toolkit state') and enumerates the exact contents (installed MCPs, connection status, accounts, catalog tool counts). This distinctly separates it from sibling tools like connect or authenticate, 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?

The description implies its use for querying overall toolkit status without explicit exclusions or alternatives. It provides clear context (informational read), but does not state when not to use it or recommend other tools for specific scenarios, though the context is sufficient for a simple status tool.

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