SEFAZ MG DEC: Caixa Postal

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

Annotations already imply readOnlyHint=false and idempotence, and the description adds useful behavioral detail about permanent vs. session-only logins. However, it does not describe what the API returns or what happens with an invalid JWT, limiting transparency for an agent.

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 purposeful: each clause adds operative detail about either configuration, session setup, or argument usage. Though it's really one run-on paragraph, it's still scannable and information-dense.

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?

There is no output schema, so the description is expected to explain return outputs. It does for the no-arg path ('to get the link') but not for the token-paste path. For a simple authentication utility, the main interaction models are still adequately covered.

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 has a single token parameter with no description. The description compensates by explicitly identifying { token: '<jwt>' } and saying that omitting it triggers link generation. This makes the parameter semantics clear enough for invocation.

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 this is an authentication tool: 'log in in the browser, copy the access token' and 'MCP.AI for IDE agents'. It identifies the tool's role and gives concrete login context, but it does not explicitly distinguish itself from sibling tools like '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 gives highly usable guidance: the best approach is adding the Authorization header to the server config, while pasting the token gives a session-only login. It also explains when to call with no args to receive the login link. It doesn't explicitly mention what the sibling 'connect' tool should be used for, but the indication here is clear.

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 a safe, read-only, idempotent operation. The description adds meaningful conditional behavior, specifying the authenticated:true and empty pending[] state versus the credentials-missing state with connect_url and per-install URLs.

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, front-loaded sentences deliver the essential behavior without redundancy. Every clause adds meaningful detail about the return states.

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 zero-parameter status tool with strong annotations, the description is complete: it covers the read-only nature, both possible states, and the key returned values. No output schema exists, but the description sufficiently describes the expected response behavior.

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 schema coverage is 100%, so the description does not need to explain parameters. The baseline for zero-parameter tools is 4, and the description appropriately focuses on outputs 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 connection status and URLs, and further clarifies conditional behavior for both connected and missing-credential cases. This distinguishes it from siblings like authenticate and show_version.

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 the tool to check connection state, especially when credentials may be missing, and explains what response to expect. It provides clear context but does not explicitly exclude alternatives or name when not to use it.

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 noteworthy behavioral detail beyond the coarse annotations: invoke runs tools that are not installed, credential needs return a connect link, empty wallets return checkout links, writes (install/uninstall/subscribe/cancel) require workspace owner/admin, and installed MCPs don't bloat the tool list. It also discloses the distinction between installed_in_toolkit and installed_in_workspace. 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?

Rather long, but every paragraph earns its place given that this is a multi-action gateway covering a marketplace plus a prompt library. It is reasonably well organized, starting with the core purpose, then the key invoke behavior, then auxiliary actions and permissions.

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?

Taking the schema and annotations into account, the description offers a solid overview of the core orchestrator, the invoke one-off behavior, auth/billing interactions, workspace permission implications, and prompt library operations. It does not explicitly describe the 'resume' action or the shape of some responses, but it is still wide-ranging coverage for a tool of this 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?

Schema description coverage is 0%, so the description carries the burden of explaining parameter roles. It succeeds for major fields (action flow, query, mcp_id, tool_id, arguments) and the prompt library fields, but several parameters (resume, conversation, cancel_comment) are only partially covered or not introduced individually.

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 precisely identifies the marketplace as the in-platform catalog of MCPs and the way to run them, with explicit verbs for each sub-role (search, describe, invoke, install, subscribe, etc.). This differentiates it from siblings such as authenticate, connect, and sefaz_mg... by situating it as the central orchestration hub.

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-to-use guidance: prefer invoke for occasional one-off runs, use install only for making tools native, and use list_tools to see what is callable immediately. It also enumerates alternatives for billing, feedback, new MCP requests, and prompt-library operations.

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=false, destructiveHint=false, and idempotentHint=true, covering the safety profile. The description adds the context that the conversation array is needed for reproduction, which is a meaningful behavioral hint. However, it does not disclose what happens after reporting (e.g., whether an acknowledgment is returned) or any other side effects, so it remains moderately 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 exactly two sentences, both of which add value. It front-loads the purpose and then provides a specific usage tip. There is no redundant or filler text, making it highly 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?

Given the tool's low complexity (three simple string parameters, no output schema), the description is almost adequate. However, it omits explicit definitions for 'message' and 'context', which are critical for correct invocation. It covers the essential purpose and reproduction hint but leaves a gap in parameter documentation, making it moderately 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?

With 0% schema description coverage, the description must compensate, but it only hints at the 'conversation' parameter ('Include the conversation array'). The required 'message' parameter is only implicitly connected to the purpose ('Report a bug...'), and the optional 'context' parameter is completely unexplained. This leaves the agent without enough detail for correct parameter 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 explicitly states the tool's action: 'Report a bug, missing feature, or send feedback.' This clearly identifies the verb and resource, distinguishing it from sibling tools like authenticate or show_version. The purpose is unambiguous and specific.

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 tells users when to use the tool (to report bugs, missing features, or provide feedback) and gives an explicit instruction to 'Include the conversation array with recent messages for reproduction.' This provides clear context without needing to exclude alternatives, as no sibling tool serves a similar purpose.

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=true, idempotent=true, and destructive=false. The description adds valuable context around payment per query, absence of platform credentials, the non-confidential nature of the data, and LGPD-related control responsibilities. This goes beyond the annotations, though it stops short of describing output format or edge-case behavior.

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 concise and front-loaded with the core purpose. All sentences carry meaningful information, though the LGPD disclaimer and the repetition of 'official sources' add slight 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?

The tool has 5 parameters and no output schema or parameter descriptions. The description explains the general nature and commercial conditions of the call, but it does not explain required input formats, how the data is returned, pagination/date-range behavior, or any constraints on ignora_nao_lidas. This is inadequate for reliable autonomous invocation.

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 provides no parameter-level information. The tool has 5 parameters, but neither the schema nor the description explains what data_inicio, data_fim, ignora_nao_lidas, pkcs12_cert, or pkcs12_pass mean or how they should be formatted. This is a critical gap for correct invocation.

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 (consulta) and the specific resource (SEFAZ MG DEC Caixa Postal). It also clarifies that it queries official Brazilian sources, which 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?

The description provides clear context: it is hosted by the platform, requires no platform credentials, and is paid per consultation via prepaid credits. It does not explicitly name alternatives or exclusions, so it falls short of a full when-to-use vs. when-not-to-use guide.

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 only states what it shows, without detailing side effects, permissions, or output behavior. The read-only nature is implied and confirmed by annotations, but the description adds no further behavioral context.

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 redundant information, achieving optimal 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?

For a simple version-check operation, the description is fully complete. It states exactly what information is provided (platform and adapter versions) without needing to explain return formats or additional context.

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 there is nothing to describe. The empty schema is perfectly aligned with the description.

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 (Show) and the subject (current MCP platform and adapter versions), making its purpose unambiguous. It is distinct from sibling tools which perform other operations.

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 the tool (e.g., checking compatibility or verifying installation). While the operation is self-explanatory, no when-to-use or alternative references 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 declare readOnlyHint=true and idempotentHint=true, so safety is covered. The description adds behavioral context by enumerating the exact contents of the return value (installed MCPs, connection status, accounts, catalog tool counts), 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 a single, well-structured sentence that front-loads the primary purpose and enumerates what is returned. No wasted words, and it is appropriately concise for a simple informational tool.

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 zero parameters, no output schema, and strong annotations (readOnly, idempotent, non-destructive), the description covers all necessary context: it states what the tool returns, and the annotation covers behavioral safety. It is complete for an informational 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?

There are zero parameters, so the schema provides no semantics to add. The baseline for 0-param tools is 4; the description does not need to compensate for any parameter coverage gaps.

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 'Returns the current toolkit state' and lists specific details (installed MCPs, connection status, accounts, tool counts). This is a specific verb+resource description that clearly distinguishes it from sibling tools like connect or show_version.

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?

It implies usage for checking toolkit status but does not explicitly state when to use it versus alternatives or when not to use it. With siblings like show_version and connect, there is no explicit guidance on choosing this over others.

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