CADE: Processos

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

Annotations indicate idempotentHint=true and destructiveHint=false, which the description aligns with. The description adds context about the token being non-expiring for config-based auth and session-only for pasted tokens, which is useful behavioral information 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 concise and front-loaded with the tool's purpose. It provides actionable steps in a compact form, though it could be slightly more structured with clear separation of the two usage modes.

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 (one optional param, no output schema), the description covers the essential usage scenarios and provides enough context for an agent to invoke it correctly. It explains both permanent and session-based authentication, which is complete for 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?

The schema has one optional parameter 'token' with no description. The description explains that the token is a JWT to be pasted, and that calling with no args returns a link. This adds meaning beyond the schema, but the schema coverage is 0%, so the description partially compensates. However, it doesn't detail the token format or validation beyond 'jwt'.

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 for MCP.AI by logging in via browser and obtaining an access token. It distinguishes itself from siblings by focusing on authentication, though it doesn't explicitly name alternatives.

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 explicit usage scenarios: either add the token to the server config for a permanent connection, or paste it here for a session-only login. It also explains when to call with no args to get the link, giving clear context for when to use this tool.

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, covering safety. The description adds valuable behavioral context beyond annotations: payment model (prepaid credit), legal data control (LGPD), and confirmation that data is not confidential. This enriches the agent's understanding without 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 a single compact paragraph, conveying all essential context without redundancy. While it includes legal disclaimers (LGPD), these are relevant to data handling and are not excessive. It is well-structured and front-loaded with the core purpose.

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 five undocumented parameters and no output schema, the description must compensate by explaining input/output behavior, pagination, or result format. It fails to do so, leaving significant gaps for an AI agent. The legal and payment context is helpful but does not address the operational details needed for correct 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 does not explain any of the five parameters (query, pagina, processo, tipo_pesquisa, interessado_remetente). With a high parameter count and no documentation, the agent has no guidance on required formats, semantics, or relationships, making this dimension critically deficient.

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 consults CADE processes from official Brazilian sources, using a specific verb ('consulta') and resource ('Processos'). It distinguishes itself from sibling utilities by specifying the domain and official nature, leaving no ambiguity about its function.

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 use: it queries official data, requires prepaid credit, and does not need platform credentials. However, it does not explicitly mention when to avoid this tool or suggest alternatives, though the sibling list (authenticate, marketplace, etc.) makes its niche apparent. No exclusions are stated, so it falls short of a 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?

Goes beyond readOnly annotation by explaining exact responses in two cases, including the presence of 'authenticated' and 'pending' fields, and the return of 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?

The description is two sentences, front-loaded with the main purpose, and each sentence provides useful information 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?

Covers two main scenarios but does not explicitly mention the case where only some providers are connected, which could be a potential gap. However, given the simplicity, it is mostly 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?

No parameters exist in the schema, so the description correctly omits any parameter details; nothing to add.

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 it returns connection status and URLs, with specific details on two scenarios, distinguishing it from sibling tools like authenticate or toolkit_info.

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 context on when to use by describing the behavior in two situations: when all providers are connected and when credentials are missing, implying it's for checking connection status and obtaining connect URLs.

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 (non-read-only, non-idempotent, non-destructive), it reveals critical behaviors: invoke runs one-off without bloating the tool list, missing credentials return a connect link, empty wallets return a checkout/top-up link, and writes require workspace owner/admin. This is actionable context about auth, retry flows, and 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 long but densely packed and well-structured: front-loaded mission, then core flow, then key invoke behavior, then auxiliary actions, permissions, and the prompt library. Every sentence earns its place given the tool's 14-action surface area.

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?

Despite having no output schema, the description covers expected outputs (shareable mcp.ai/p/<slug> link, connect/checkout links, installed flags), billing, ownership requirements, and both the MCP and prompt-library workflows. For a 23-parameter multi-action gateway, this is unusually complete and operationally self-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?

Schema description coverage is 0%, but the description compensates substantially by giving meaning to the action enum values and key params like mcp_id, tool_id, and prompt_vars ("full text with {{variables}} filled"). However, many secondary parameters such as immediate, tier_slug, cancel_reason, and prompt_targets are not explained, so it is not a complete substitute for schema-level definitions.

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 defines marketplace as the official mcp.ai in-platform MCP catalog and execution gateway, explicitly covering capability requests like "find an MCP that does X" and "is there a tool for Y". It articulates a distinct core flow (search → describe → invoke → install) and differentiates itself from sibling tools by owning the full marketplace lifecycle.

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 usage guidance: "prefer invoke for a single/occasional use" and "Use install only to make an MCP PERMANENT", plus a clear distinction that list_tools shows "what is callable right now". It also states when request_mcp is appropriate ("asks us to build a NEW MCP when nothing fits").

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 establish a non-destructive, idempotent write (readOnlyHint=false, destructiveHint=false, idempotentHint=true), so the description does not need to restate safety. It adds actionable context about including recent conversation messages for reproduction, but does not disclose what response or side effect the caller should expect.

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 sentences front-load the purpose and then give the key reproduction instruction. No filler or 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 is low-complexity and the description covers its core purpose and main reproduction detail, but with no output schema it should state what happens after submission. The optional 'context' parameter and the required 'message' parameter also remain under-described.

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 only partially compensates: it explains that 'conversation' should contain recent messages (called an 'array' despite the schema declaring a string), while the required 'message' and optional 'context' are left unspecified. This could cause incorrect values, especially for 'conversation'.

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 clear verb-resource pairing ('Report a bug, missing feature, or send feedback') and is distinct from the unrelated sibling tools. It defines exactly what the tool is for without restating the name tautologically.

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 opening phrase gives an explicit use context: bug reports, feature requests, and general feedback. No exclusions or alternative tools are needed because none of the siblings addresses this function, though it could add 'instead of' guidance if a similar tool appeared.

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 covered. The description adds no extra behavioral details beyond what the annotations imply, such as output format or potential latency. It does not contradict annotations, but adds minimal transparency value.

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 core action and resource. There is no fluff or unnecessary detail, earning a perfect score for efficiency.

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 with no parameters, output schema, or complex behavior. The description covers the essential information (showing versions) and is complete given its trivial nature, though it could theoretically specify what exactly is returned (e.g., separate strings or combined).

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 fully covers parameter semantics. The description doesn't need to explain parameters, and this baseline score of 4 is appropriate given the lack 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 clearly states the verb 'Show' and the resource 'current MCP platform and adapter versions', making the tool's purpose explicit. It distinguishes itself from siblings like 'authenticate' or 'connect' by focusing on version 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?

No guidance is given on when to use this tool versus alternatives, such as 'toolkit_info' which might also provide system information. It simply states what it does without context on appropriate usage scenarios or 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 include readOnlyHint=true and destructiveHint=false, so the safety profile is already covered. The description adds value by specifying the exact data returned (installed MCPs, status, accounts, counts) but doesn't disclose any potential delays or the nature of the accounts (e.g., whether they are auth-related). It doesn't 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, front-loaded with the core purpose ('Returns the current toolkit state') and enumerates useful details. It is concise and efficient with no fluff, though it could be seen as slightly verbose for a zero-parameter 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?

For a zero-parameter tool with no output schema, it provides a good overview of what is returned but lacks specifics like the format of the response (e.g., list vs object) or any error conditions. Since complexity is low, it's sufficient, but it could give a touch more detail.

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 0 parametersholsters, so a baseline of 4 is appropriate per the rubric. The description adequately explains the no-input nature by focusing on what is returned, which is all that 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?

The description clearly states the tool returns the current toolkit state, listing specific elements (installed MCPs, connection status, accounts, catalog tool counts). This is specific and distinguishes it from sibling tools like '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 usage when you need an overview of the toolkit's current stateable componentsaines, but it doesn't explicitly state when to use it versus alternatives like 'show_version' or 'marketplace'. It lacks explicit exclusions or comparisons to siblings.

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