Processos Judiciais (Agrupada)

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

Builds on the annotations (idempotent, non-destructive) by explaining the two authentication modes and what happens with or without a token. It discloses that calling with no args returns a link and that the config header yields a permanent connection, adding behavioral context beyond the structured 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 bit lengthy but every sentence contributes by explaining a distinct usage mode. It is front-loaded with the core purpose, then details the alternatives. Some minor redundancy but no irrelevant content.

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 one optional parameter and no output schema, the description covers the essential usage scenarios and user interaction. It provides enough context for an agent to decide when and how to call it, though it does not detail return values beyond 'get the link'.

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 no description for the optional 'token' parameter, but the description clarifies that it expects a JWT pasted by the user for session login. It also mentions the Authorization header format for permanent config, effectively compensating for the 0% schema coverage.

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 purpose: authenticating the user for the MCP server via browser login and token. It specifies the workflow with 'log in in the browser, copy the access token' and distinguishes between permanent and session-based authentication, making it clear and distinct from 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?

Provides clear guidance on when to use which method: config header for permanent, non-expiring connection, or pasting a token for session-only login. It also explains calling with no args to get the link. However, it does not explicitly discuss alternatives or exclusions compared to sibling tools like 'connect'.

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, covering safety. The description adds valuable state-dependent behavior (authenticated:true vs connect_url), giving agents a clear expectation of the response without repeating annotation data.

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 core purpose and followed by specific conditional details. Every word contributes to understanding the tool's behavior.

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, read-only status tool, the description adequately covers the two main return states. It does not mention partial connection states or elaborate on the pending array, but these are not critical for basic usage and annotations provide sufficient safety 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 schema has zero parameters, so the baseline for parameter semantics is 4. The description appropriately focuses on return behavior rather than nonexistent parameters, adding no unnecessary clutter.

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 conditional outcomes. While it doesn't explicitly compare to sibling 'authenticate', the focus on status inspection implicitly differentiates it from action-oriented 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 provides conditional behavior based on credential state but does not explicitly instruct when to use this tool versus alternatives like 'authenticate'. Usage context is implied through the return scenarios, but explicit guidance is missing.

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 false, openWorldHint true), the description discloses key behaviors: writes require workspace owner/admin, invoke operates one-off without adding to the toolkit, credential/payment failures return connect/checkout links and require retry, and search/describe flag installed_in_toolkit vs installed_in_workspace. This far exceeds the safety baseline set by 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 long but every sentence earns its place. It is front-loaded with a clear definition, then organizes information into core flow, install-vs-invoke guidance, write permissions, and prompt library. Despite its density, there is no fluff or repetition; it is an efficient use of text for a multi-action 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 the complexity (23 optional params, 14 actions, no output schema), the description is remarkably complete. It covers the end-to-end workflow, edge cases (auth connect link, empty wallet checkout link, retry logic), permission requirements, the distinction between one-off invoke and permanent install, and the additional prompt-library feature. It even notes how search/describe surfaces installation status. This is sufficient 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%, so the description must compensate. It thoroughly explains the 'action' enum (search, describe, install, invoke, etc.) and the purpose of core parameters like tool_id, arguments, mcp_id, and prompt_* variables. However, it leaves several parameters undocumented (e.g., immediate, tier_slug, resume, cancel_reason, cancel_comment, prompt_targets, prompt_category). It adds substantial meaning for the most important parameters but doesn't cover the full 23-parameter surface.

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 — the in-platform catalog of every MCP/tool, AND the way to run them,' and then enumerates the core flow (search → describe → invoke). It distinguishes itself from sibling tools like authenticate, connect, and report_bug by defining its unique role as catalog/runner.

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 guidance on when to use invoke vs install: 'prefer invoke for a single/occasional use' and 'use install only to make an MCP PERMANENT.' It also explains when to use subscribe/cancel, report_bug, and request_mcp, and contrasts list_tools as listing 'what is callable right now.' This is rich, actionable 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?

The annotations already indicate read-only, idempotent, and non-destructive. The description adds that the data is of public access, not private/confidential, that the client is data controller under LGPD, and that payment is required per consultation, adding useful cost and legal context 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?

Three sentences: purpose, access/payment, and legal/data nature. Each sentence adds distinct value with no redundancy, but the third sentence could be considered slightly legalistic, though it earns its place.

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 no output schema, and the description only mentions a summarized-by-court view. It does not describe the return structure, what 'completo' changes, or any limitations (e.g., which courts). The data-source transparency is good, but missing details on the optional parameter and output.

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 description mentions CPF/CNPJ as the query inputs, but does not explain the 'completo' parameter. It also says 'CPF ou CNPJ' (either), which conflicts with the schema's 'required' listing of both Cpf and Cnpj, creating ambiguity. With 0% schema coverage, it fails to adequately describe all 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 tool performs a grouped consultation ('Consulta agrupada') of judicial processes by CPF or CNPJ, with a summarized view by court. It specifies the resource (processos judiciais), the input (CPF/CNPJ), and the output format, distinguishing it from platform utility 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?

It provides context that the tool is hosted on the platform, requires no credentials, and is paid per query with prepaid credit. This is clear usage context, but it does not explicitly name alternatives or exclusions, though no direct sibling competitor exists.

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 idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds no additional behavioral context such as rate limits or post-submission outcomes; mentioning the conversation array is parameter-focused rather than behavioral. 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?

Two sentences, front-loaded with the verb and purpose. Each sentence earns its place: one states what the tool does, the other gives a critical usage instruction. No fluff.

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 three-parameter tool, the description covers the core purpose and the most important parameter (conversation). It doesn't explain the context parameter or what happens after submission, and since there's no output schema, a bit more return-value context would help. Still, the tool is simple enough that this is mostly 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 coverage is 0%, so the description must compensate. It explicitly explains the conversation parameter's purpose ('recent messages for reproduction') but leaves context unexplained and message is only implied by the tool name. Partial compensation.

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 identifies the resource as 'a bug, missing feature, or send feedback,' clearly distinguishing it from unrelated sibling tools like authenticate or show_version. The purpose is immediately clear.

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 provides clear context by instructing users to include the conversation array for reproduction, which is key usage guidance. It does not explicitly list when not to use the tool, but given no overlapping sibling tools, this 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the specific output content (platform and adapter versions), which gives useful behavioral context beyond the annotations. It does not introduce contradictions.

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 or redundant information. Every word earns its place, and the structure is optimally concise for a zero-parameter read-only 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 the tool's simplicity—no parameters, no output schema, and clear annotations—the description is fully complete. It states exactly what the tool shows, leaving no ambiguity about its function or return value.

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 trivially 100%. The baseline score of 4 applies because there are no parameters to document. The description adds no parameter information, but none 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 uses a specific verb 'Show' with a clear resource: 'current MCP platform and adapter versions'. This clearly differentiates it from siblings like authenticate or report_bug, and even from toolkit_info which likely covers broader 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 provided on when to use this tool versus alternatives. There is no mention of scenarios like checking compatibility or debugging version-related issues, nor any exclusions. The context is entirely absent apart from the purpose itself.

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, destructiveHint=false, and idempotentHint=true, covering the safety profile. The description adds meaningful context about the response content (state, connections, accounts, tool counts) beyond what the annotations convey. It does not mention output format or edge cases, but this is a read-only state query with no 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 a single, well-structured sentence. It front-loads the action ('Returns the current toolkit state') and then lists specific components. Every word earns its place, with no redundancy or extraneous information.

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, read-only tool with comprehensive annotations, the description is complete. It explains what the tool returns and the key components of the state, which is sufficient for an agent to invoke it correctly. The absence of an output schema is acceptable because the description outlines the high-level contents.

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 input schema confirms this. According to the rubric, a baseline of 4 is appropriate when there are no parameters, and the description does not need to add parameter semantics.

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 with a specific verb ('Returns') and identifies the resource ('current toolkit state'). It details exactly what is included (installed MCPs, connection status, accounts, catalog tool counts), making it distinct from sibling tools like show_version 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 implies usage for inspecting the toolkit state, but it does not explicitly state when to choose this tool over alternatives. No exclusions or alternative references are provided, leaving the decision to the agent's inference from sibling names.

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