Tribunal TJRJ: Processo

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

Annotations include readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds behavioral detail beyond annotations: it explains the two authentication modes (permanent config vs session token), the token format (JWT), and the action of getting a link if no args are provided. This enriches the agent's understanding without contradicting any 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 sentence but highly informative. It front-loads the purpose and then details usage modes. No fluff or redundancy. The length is justified given the complexity of the authentication flow, but it could be slightly more structured (e.g., separated sentences) for readability without losing meaning.

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, one optional parameter, and no nested objects. The description covers the key aspects: how to authenticate permanently or temporarily, what to pass, and the behavior when called with no args. It provides complete information for an agent to decide and invoke correctly, and the lack of output details is acceptable since the primary outcome is auth state or a 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 single parameter 'token' is a string with zero schema description coverage, so the description must compensate. It does so effectively by explaining that when a token is provided, it's a session-only login, and if omitted, the tool returns a login link. This adds critical context that the schema alone lacks.

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 with MCP.AI for IDE agents by logging in via browser and copying a token. It distinguishes itself from siblings like 'connect' and 'marketplace' by explicitly focusing on authentication. The verb 'log in' and resource 'MCP.AI' plus token handling make the purpose unambiguous.

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 guidance: recommends adding the token to the server config for a permanent connection, or using a session-only login by calling with a token or no args to get a link. It clearly explains when each mode is appropriate and gives calling instructions, which is more than sufficient for an agent to select and invoke the 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 read-only, idempotent, and non-destructive behavior. The description adds useful specifics about the response fields (authenticated, pending, connect_url) and the conditional flow, which goes beyond the structured annotations and helps the agent understand what to 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?

The description is two concise sentences that lead with the core purpose and then elaborate on the two output scenarios. Every word adds value, with no fluff 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?

For a simple tool with no parameters and no output schema, the description sufficiently explains the primary return values and the two main states. It lacks explicit details on the format of URLs or any error handling, but for a status-check tool this is quite 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 tool has zero parameters, so there is nothing to explain about parameters. The baseline score for 0 params is 4, and the description correctly does not need to add parameter details since no parameters 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 clearly states the tool returns connection status and URLs, and specifies the two distinct output states (all connected vs missing credentials). This distinguishes it from siblings like 'authenticate' by focusing on status checking 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 when checking connection status and explains conditional behavior, but it does not explicitly state when to use this tool versus alternatives like 'authenticate'. No exclusions or explicit alternative guidance is provided, so it's adequate but not explicit.

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?

With no annotations, the description carries full burden and delivers: discloses writes require owner/admin, invoke can run without installation, side effects of install vs invoke, and payment/auth flows. 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?

One dense paragraph covering 14 actions plus prompt library. Informative but lacks structure (no bullets/headers); requires careful reading. Acceptable for complexity but not concise.

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 all core flows (search, describe, invoke with auth/payment edge cases), mentions write permissions, list_tools, subscribe/cancel, report_bug, request_mcp, and prompt library. Missing explicit param semantics for many fields but the main user journeys are well documented.

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?

Description explains the action enum values and core params (query, limit, mcp_id, tool_id, arguments) through the flow narrative. However, 23 params exist and many (tier_slug, cancel_reason, prompt_targets, report_context) are never explained. Partial coverage only.

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 opens with

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 explicit when-to-use guidance: 'prefer invoke for single/occasional use', 'use install only to make an MCP PERMANENT', and 'use request_mcp when nothing fits'. Also explains when invoke returns a connect/checkout link and what to do next.

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 and destructiveHint=false; description adds the reproduction requirement but doesn't describe other behavioral aspects such as what happens on success or response format. 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?

Two concise sentences, front-loaded with the tool's purpose, no redundancy. Every word 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?

Adequate for a simple reporting tool but leaves gaps: required 'message' is not explained, 'context' is undocumented, and no output/behavioral consequences are mentioned.

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%, and description only explains the 'conversation' parameter, calling it an 'array' even though schema types it as string. Required 'message' and 'context' are not described; the 'array' vs string mismatch may mislead the agent.

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 uses specific verb 'Report' and clearly identifies the resource: 'a bug, missing feature, or send feedback', which distinguishes it from sibling tools. 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?

States clear use cases (reporting bugs/features/feedback) and explicitly instructs to include conversation for reproduction, giving practical context. However, it does not mention alternatives or exclusions, but siblings are unrelated so this is sufficient.

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 the safety profile is fully disclosed. The description adds no extra behavioral context beyond restating the action, but for such a simple tool, this is acceptable; no contradiction exists.

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, short, front-loaded sentence that conveys all necessary information without any fluff. Every word earns its place, making it highly efficient.

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 trivial complexity (no parameters, no output schema, clear annotations), the description is fully complete. There is no missing information that an agent would need to invoke 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?

The tool has zero parameters, and the schema coverage is 100% (vacuously). Per the rubric, a baseline of 4 is given when there are no parameters, and the description does not need to explain any input 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 'Show the current MCP platform and adapter versions' clearly states a specific verb ('Show') and resource ('MCP platform and adapter versions'). It is entirely distinct from sibling tools like 'connect' or 'authenticate', 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?

While no explicit alternatives or exclusions are mentioned, the tool's trivial nature (no parameters, simple read-only action) makes usage self-evident. The context is clear enough for an agent to infer when to call it, though it doesn't explicitly state 'use this to check versions' or reference siblings.

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 (readOnlyHint=true, idempotentHint=true, destructiveHint=false) already establish a safe read operation. The description adds meaningful detail about the returned content (installed MCPs, connection status, accounts, catalog tool counts), providing context beyond what annotations convey. It does not discuss caching or live freshness, but that is non-critical for a state summary.

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?

A single, front-loaded sentence that names the verb, the object, and the specific payload of the returned state. Every listed element adds value and there is no filler or restated metadata.

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 and parameterless, and the description fully captures the informational content of the response. Given strong annotations and this clear list of returned categories, the description is complete enough for an agent to know what to expect and how to use the result.

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 zero parameters, the schema imposes no burden, and the baseline of 4 applies. The description does not need to document any params because there are none; nothing is 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 uses a specific verb ('Returns') and clearly identifies the resource ('current toolkit state') plus enumerates the concrete information returned: installed MCPs, connection status, accounts, and catalog tool counts. This fully distinguishes it from siblings like show_version, which would report version details.

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 plainly implies when to use this tool: whenever you need a snapshot of the toolkit's installed MCPs, connection status, and accounts. There is no explicit alternative comparison, but the domain is self-contained and no confusion with siblings arises.

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, so the safety profile is clear. The description adds valuable context: it's hosted by the platform, requires prepaid credit, and clarifies data privacy (LGPD) and that the client is the data controller. This goes beyond annotations and provides important operational and legal 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 paragraph, reasonably concise, and front-loaded with the core purpose. It includes necessary legal and payment context without excessive verbosity. However, it could be slightly more structured, but overall it's efficient.

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 (10 optional parameters, no output schema, no parameter descriptions), the description is incomplete. It covers the purpose, payment, and legal aspects, but lacks guidance on parameter usage, expected results, or any limitations. The annotations help with safety, but the description doesn't fully compensate for the lack of schema documentation.

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 10 parameters. The parameter names are somewhat self-explanatory (cpf, oab, cnpj, numero_processo, etc.), but the description provides no guidance on how to use them, which combinations are valid, or any format requirements. With 10 parameters and no coverage, the description should compensate but doesn't.

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: consulting process information from the official TJRJ source. It specifies the resource (processo) and the court (TJRJ), and distinguishes it from generic tools by mentioning the official source and payment model. However, it doesn't explicitly differentiate from sibling tools, though siblings are mostly unrelated (auth, marketplace, etc.).

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 context: it's for consulting official Brazilian court data, with a prepaid credit model. It mentions that the data is the same available to citizens and not confidential, which gives some context. However, it doesn't explicitly state when to use this tool vs alternatives, nor does it provide exclusions or prerequisites beyond payment.

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