Processos Judiciais (Completa)

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

The description discloses key behaviors: calling with no args returns a link, calling with token validates a session, and the distinction between permanent and session-only. It goes beyond the annotations (idempotentHint=true) by explaining the two-flow nature and the external browser step. No contradictions 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 a single paragraph but packed with necessary instructions. It front-loads the purpose, then structures the two usage methods with 'Best:' and 'Or'. Every sentence earns its place, though slightly long, it remains clear and well-organized.

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 lack of output schema and minimal annotations, the description covers the essential flow: browser login, token retrieval, two usage modes, and how the agent should call the tool. It omits error handling or invalid-token scenarios, but for an authentication tool it is adequately 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?

The schema has one undocumented token parameter (0% coverage). The description compensates fully by explaining that token is the JWT pasted by the user, and how omitting it triggers the link-returning behavior. This adds critical meaning beyond the schema.

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: authenticating to the MCP server via browser login and token. It uses specific verbs ('log in', 'copy', 'call') and explains the resource (the server's authentication). It distinguishes from siblings by being the only auth-related tool among the listed siblings.

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 modes: permanent via config header or session-only via token parameter. It explains when to call with no args (to get the link) and when to call with token (after user pastes). While it doesn't name alternative tools, it gives clear context for the agent to decide 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?

The description discloses behavior beyond annotations by explaining the response structure for different scenarios (all connected vs. missing credentials). It adds context about the returned URLs and authenticated flag, which annotations do not provide.

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 concise sentences, front-loaded with the main purpose and then detailing conditional behavior. Every sentence adds value 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?

For a simple status tool with no parameters and no output schema, the description covers key outcomes (authenticated vs. missing credentials). However, it does not mention intermediate states (e.g., partial connectivity) or clarify what 'pending[]' contains, leaving minor gaps.

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 is 4. The description does not need to explain parameter semantics, and it does not add any unnecessary parameter 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 the tool returns connection status and URLs, with specific details about response values. It distinguishes itself from siblings like 'authenticate' by focusing on status rather than performing authentication.

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 for checking connection status, but does not explicitly mention when to use this tool over alternatives or provide exclusions. It is clear enough for a status-checking tool, but lacks explicit 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?

The description goes well beyond the annotations: it discloses that invoke runs tools one-off without installing, install makes permanent, writes require owner/admin, invoke returns connect/checkout links, and it explains billing, prompt-library behavior, and installed-in-toolkit vs workspace flags. No contradiction with the provided 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 dense single paragraph but logically organized around the core flow (search → describe → invoke) and then extended to install, billing, and prompts. Every sentence contributes value, though the length and lack of formatting (e.g., bullets) make it slightly harder to scan. Appropriate for the tool's complexity.

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 multi-action tool with 23 parameters and no output schema, the description covers the main flows, permission requirements, and special return behaviors (connect/checkout links). Minor gaps remain for exact return formats of search/list_tools and some action-specific parameters, but the overall picture is well-rounded.

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 compensates substantially by explaining the meaning of key parameters through the action flow: query/intent for search, mcp_id for describe, tool_id/arguments for invoke, and prompt_slug/vars for prompt functions. However, several parameters such as immediate, tier_slug, limit, cancel_reason, and report_context remain unexplained, so coverage is 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, encompassing discovery, description, and execution of MCPs/tools, plus a prompt library. It uses specific verbs and an action-flow narrative, and distinguishes it from sibling tools by its unique marketplace role.

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 guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT', and outlines when to use search, describe, list_tools, subscribe/cancel, report_bug, request_mcp, and prompt functions. It also specifies auth requirements and alternatives, making usage conditions very 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 declare readOnlyHint, idempotentHint, and destructiveHint. Beyond these, the description adds critical behavioral context: no credentials required, prepaid credit/payment model, data is public access (not private), and LGPD compliance responsibilities. This goes beyond the annotations by addressing authentication, financial implications, and data handling, which are valuable for the 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 concise at three sentences, front-loading the core purpose. The additional sentences about hosting, payment, and LGPD are informative and not redundant. A minor issue is the legal disclaimer, but it's relevant for compliance and not excessive.

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 3 parameters, no output schema, and the description covers many contextual aspects (payment, auth, data subject). However, it fails to explain the 'completo' parameter and does not resolve the contradiction between 'ou' in the description and the schema's required both Cpf and Cnpj. With no output schema, more detail on response structure would help, though 'com detalhes por processo' gives a hint. Overall, the description is incomplete for a tool with 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 coverage is 0%, so the description must explain parameters. It mentions 'CPF ou CNPJ' but this conflicts with the schema, where both Cpf and Cnpj are required. The boolean 'completo' parameter is not explained at all, despite the description's phrase 'com detalhes por processo' possibly alluding to it. The description adds little semantic value and leaves parameter usage ambiguous.

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: 'Consulta completa dos processos judiciais de uma pessoa ou empresa a partir do CPF ou CNPJ, com detalhes por processo.' It names a specific verb (consultar), resource (processos judiciais), and input scope (CPF/CNPJ). It also distinguishes from siblings, as none of the listed siblings (authenticate, connect, marketplace, etc.) relate to judicial process consultation.

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 clear usage context: 'Hospedado pela plataforma, sem credenciais, pague por consulta com crédito pré-pago' and 'Consulta informação de ACESSO PÚBLICO em bases e fontes oficiais.' It sets expectations for authentication and payment but does not explicitly state when not to use the tool or name alternatives. Since there are no similar sibling tools, the lack of exclusion criteria is acceptable.

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 provide idempotentHint=true, readOnlyHint=false, and destructiveHint=false. The description adds a behavioral detail beyond annotations by specifying that the conversation array should be included 'for reproduction,' implying the tool will use that data to understand the issue. However, it does not disclose other behaviors like whether a confirmation is returned or how the report is processed, so there is moderate added 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, clear sentence followed by a practical instruction. It is concise and front-loaded with the primary action, wasting no words. Every part is essential for understanding the tool's purpose and a key usage detail.

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 feedback/report tool with three parameters and no output schema, the description covers the core functionality and provides a key usage hint (conversation array). It could mention what happens after reporting, but it is reasonably complete for the tool's simplicity and the annotations fill in safety metadata (idempotent, non-destructive).

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 0% description coverage, so the description carries the burden of explaining parameters. It explicitly explains the 'conversation' parameter ('Include the conversation array with recent messages') and implies 'message' is the content of the report. However, the 'context' parameter is not explained, and the description doesn't mention parameter types or defaults beyond what the schema already shows. This is partial compensation for the schema gap.

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: 'Report a bug, missing feature, or send feedback.' It uses a specific verb ('report'/'send') and resource ('bug', 'missing feature', 'feedback'). It is obviously distinct from sibling tools, which focus on authentication, connection, marketplace, legal consultation, version, and toolkit info, so no confusion arises.

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 there is a bug, missing feature, or feedback to send. It does not explicitly mention alternatives or exclusions, but since none of the sibling tools are similar, the intended usage is unambiguous. The instruction to include the conversation array also gives practical guidance on how to use it effectively.

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, so the safety profile is clear. The description adds a small detail about reporting both platform and adapter versions but doesn't provide additional behavioral context beyond that.

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?

Single sentence, front-loaded with the verb, no wasted words.

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?

This is a trivial read-only tool with no params, strong annotations, and no output schema. The description completely covers the tool's function; nothing else is needed.

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 is empty with 100% schema description coverage, and there are no parameters. As per the rubric, a zero-parameter tool gets a baseline of 4; the description correctly doesn't attempt to document nonexistent params.

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 clearly identifies the resources ('current MCP platform and adapter versions'). It effectively distinguishes itself from sibling tools like 'toolkit_info' by focusing specifically 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?

The description implies the tool is for retrieving version info but provides no explicit guidance on when to prefer it over siblings. Since it's a simple, unconditional call, the usage is self-evident, but no alternatives or exclusions are mentioned.

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, destructiveHint=false. The description adds useful behavioral context by specifying exactly what 'state' includes (installed MCPs, connection status, connected accounts, tool counts), which goes beyond the bare name. No hidden side effects or constraints are implied, and nothing contradicts 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 action and then lists the key output components. Every word contributes meaning, with no fluff or repetition of the schema (which is empty).

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 (zero params, no output schema), the description fully captures its behavior and scope. It tells the agent exactly what to expect: a snapshot of MCPs, connection status, accounts, and tool counts, which is sufficient for a read-only informational tool. No gaps remain.

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 is 4. The description appropriately explains what the tool returns, leaving no need for parameter documentation. It adds no redundant parameter info because none exist.

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 identifies the exact resource ('current toolkit state') with enumerated details (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from sibling tools like authenticate or 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?

The description conveys the tool's role as a state/info snapshot, making its use obvious for checking toolkit status. It does not explicitly state when not to use it or list alternatives, but no overlapping sibling exists, so the context is clear enough. A minor omission is the lack of explicit 'use this when you need a summary' guidance.

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