SEFAZ RJ DEC: Caixa Postal

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

Annotations show readOnlyHint=false and destructiveHint=false; description adds context about the flow (getting a link, pasting a token) and idempotency is covered by annotations. It doesn't contradict annotations, and the added behavioral details are helpful.

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, efficient and front-loaded, but the second sentence is slightly verbose with clauses; still concise overall.

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 one optional parameter and no output schema, the description covers all relevant context: how to get permanent vs session access, what happens with no args, and the token format. Sufficient for agent usage.

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%, but description fully explains the single optional `token` parameter (JWT for session login) and the no-args case to obtain the link, compensating for 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?

Description clearly states the tool authenticates to MCP.AI for IDE agents, with specific actions (login, copy token, add config) and distinguishes from siblings by its unique 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?

Explicitly explains two usage scenarios: permanent connection via config header or session-only via token input, and instructs calling with no args to get the link. Clearly differentiates from 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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description's job is to add context. It does this by explaining the return values in different states (authenticated vs. missing credentials), which goes beyond what annotations provide. No contradiction.

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 (two sentences) and front-loaded with the main purpose. It includes necessary detail about response states without redundancy. Slightly more structure could be added, but it is appropriately sized for the tool's simplicity.

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 no parameters and only a simple output (status and URLs), the description covers the key scenarios (all connected vs. missing credentials) sufficiently. Since there is no output schema, the description provides the needed return value semantics. It is complete for the tool's complexity.

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 is trivially covered (100%). The description does not need to explain parameters; it explains the tool's behavior, which is sufficient. A baseline of 4 is appropriate as there is nothing to compensate for.

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 returns connection status and URLs, with specific details about the response when all providers are connected versus when credentials are missing. It distinguishes itself from siblings like 'authenticate' by focusing on status rather than 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 implies when to use it (to check connection status, especially if authentication is needed), but does not explicitly contrast with alternatives like 'authenticate' or provide 'when not to use' guidance. However, the context is clear enough for an agent to infer appropriate 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?

The annotations are sparse, so the description carries the burden and does it well: it discloses that invoke runs one-off even when the MCP is not installed, that it returns connect or top-up links in certain billing/auth cases, that it does not bloat the tool list, and that write actions require owner/admin. This is rich behavioral context with no contradiction against 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 dense paragraph but is front-loaded with the most important purpose and then flows into required usage distinctions. It is not as scannable as a structured breakdown, but every sentence contributes substantive information, so the lack of bullets is a minor structural cost.

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 complexity, the description covers the core flow, billing, permissions, workspace flagging, and the prompt-library sub-feature noteworthy well. It omits a few items such as the exact behavior of the resume action and the return shape of most actions, so it is strong but not exhaustive.

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% with 23 parameters, and the description gives meaningful semantics for the core workflow values such as action, search, describe, invoke, and prompt-related parameters. However, many parameters like immediate, tier_slug, conversation, cancel_reason, and prompt_fields are not explained, leaving the agent to infer their meaning from property names and the action enum.

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 mcp.ai marketplace/catalog and the execution mechanism for MCP tools, then walks through a concrete search → describe → invoke flow. This distinguishes it from the sibling tools by specifying the resource it controls and the primary actions it performs.

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 selection guidance: 'prefer invoke for a single/occasional use' vs 'use install only to make an MCP PERMANENT', plus list_tools for what is callable now and request_mcp for building new MCPs when nothing fits. It also explains when auth or checkout links appear and what the agent should do.

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 already wire safety signals (readOnlyHint=false, destructiveHint=false, idempotentHint=true), so the bar is lower. The description adds minimal behavioral context—that conversation context is used for 'reproduction'—but doesn't disclose outcomes like confirmation behavior, auth expectations, or data persistence. 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 front-loaded with intent and groups its targets efficiently ('a bug, missing feature, or send feedback'). Both sentences earn their place, and the whole text is compact, though the helper instruction could arguably be structured as a parameter note.

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 only 3 string parameters, no nested objects, and no output schema, this is a simple tool that the description adequately scopes at a high level. However, it stops short of explaining message content expectations or post-submission behavior, leaving modest gaps for a mutation-like endpoint.

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%, placing the full burden on the description. Yet the text only references the 'conversation' parameter (for reproduction), leaving the required 'message' field and the 'context' field completely unexplained. This is a significant gap for the single required 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 uses a specific verb ('Report') and resource ('a bug, missing feature, or send feedback'), making the tool's purpose immediately clear. It distinguishes itself from the sibling tools (authenticate, connect, marketplace, etc.) which are all obviously different functions, though no alternatives are explicitly named.

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 instruction to 'Include the conversation array with recent messages for reproduction' implies procedural context but doesn't explicitly state when to use this instead of alternatives or list exclusions. Usage guidance is only implied through the reproduction hint, never stated as explicit conditions.

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 useful context beyond annotations: it is platform-hosted, requires no platform credentials, costs prepaid credit per consultation, and covers only non-confidential public data. No contradiction with annotations was found.

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 reasonably short but includes redundancy: 'consulta em fonte oficial' and 'consulta informação de fontes e órgãos oficiais brasileiros' express similar ideas. The LGPD sentence adds legal context but not operational value, and no parameter or usage details are 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?

With no output schema and minimal input schema descriptions, the description should explain return values, parameter relationships, and invocation requirements, but it does not. It provides broad context (payment, data sensitivity, legal responsibility) yet leaves the agent without enough detail to call the tool 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?

Schema description coverage is 0%, but the description adds no explanation of the six parameters, including required pkcs12_cert and pkcs12_pass. Parameter names like ie, cpf, and cnpj are partially self-explanatory, but ignora_nao_lidas and the certificate requirement are left unexplained.

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 a specific operation: consulting SEFAZ RJ DEC's Caixa Postal from an official source. This clearly names the resource and the action, and the official-source scope helps ground it. However, 'Caixa Postal' is not defined, so an unfamiliar agent may not know exactly what is being consulted.

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 usage context: no platform credentials are needed, queries are paid with prepaid credit, and the data is non-confidential and citizen-accessible. It implies legitimate-purpose use via LGPD but does not name alternatives or explicit when-not-to-use conditions.

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 and idempotent behavior, which the description does not contradict. The description adds no extra behavioral details, but since annotations cover the key aspects, the transparency 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 concise sentence that completely conveys the tool's purpose without unnecessary words. It is well-structured and 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?

Given the absence of parameters and the straightforward output (versions), the description fully covers the tool's functionality. No additional context is needed for an agent to use 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 tool has no parameters, so the schema is complete. There is nothing to describe beyond what the schema already provides, making this dimension trivially perfect.

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: showing the MCP platform and adapter versions. It is specific and distinguishes from sibling tools like 'toolkit_info' which likely provides broader toolkit information.

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 this tool (when version information is needed), but does not explicitly mention alternatives or exclusions. Given the simplicity, this is adequate, though a brief note on when not to use it (e.g., if only platform version is needed) could improve clarity.

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 value by specifying what the state includes (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the annotations. No contradictions found.

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 is concise and front-loaded with the main purpose ('Returns the current toolkit state'), followed by specific details. Every word earns its place, with no fluff or repetition.

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 no parameters, no output schema, and strong annotations, the description is quite complete. It lists the key components of the return value (installed MCPs, connection status, accounts, catalog tool counts). It could potentially mention the format or structure of the return, but with no output schema, the description covers the essentials well.

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 coverage is 100% (trivially, since there are no properties). The description doesn't need to explain parameters, and it doesn't. The baseline for 0 params is 4, and the description appropriately focuses on the return content 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 the tool returns the current toolkit state, listing specific elements: installed MCPs, connection status, connected accounts, and catalog tool counts. This is a specific verb+resource combination that distinguishes it from siblings like show_version (which likely shows version info) and marketplace (which likely lists available tools).

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 this is a read-only informational tool for checking the toolkit's current state, which is clear from the context. However, it doesn't explicitly state when to use it versus alternatives like show_version or marketplace, though the purpose is distinct enough that the usage context is reasonably clear.

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