Processos TRT (Justiça do Trabalho)

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

Annotations already provide idempotentHint=true and destructiveHint=false, and the description adds valuable context about permanent vs session-only connections and the browser interaction required. There is no contradiction with the annotations, and the behavioral characteristics are sufficiently disclosed.

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 three sentences and covers all necessary information without excessive verbosity. The opening phrase 'MCP.AI for IDE agents' is slightly awkward but not wasteful, and each sentence contributes to understanding the tool's use.

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 one optional parameter and no output schema, the description covers the primary usage modes and the parameter's role. It does not mention response formats or error handling for invalid tokens, but it is substantially complete for an authentication tool given the available annotations.

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 a single undocumented 'token' parameter (0% description coverage). The description compensates by explaining that 'token' is a JWT for session-only login and that omitting it yields a login link, providing meaning beyond the raw 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: authentication for IDE agents via browser login and access token handling. It uses specific verbs and distinguishes itself from sibling tools like connect or marketplace by focusing on token acquisition and session management.

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 instructions for two scenarios: adding a permanent `Authorization: Bearer <token>` header to the server config, or using a session-only login by passing a JWT token as a parameter. It also explains that calling with no args returns the login link, giving clear context for when to use each approach.

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. The description adds output behavior: explaining the response structure (authenticated, pending, connect_url) based on connection state, 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?

Two sentences, front-loaded with the main purpose, and each sentence adds distinct information. 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?

Since there is no output schema, the description explains the key return cases (all connected vs credentials missing). However, it doesn't cover partial connection states, which could be a slight gap. Still, it is complete enough for a simple status-check 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 no parameters, so schema coverage is 100%. Baseline 4 applies; the description does not need to add parameter semantics since 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 states 'Returns connection status and URLs' with a specific verb and resource. It further explains two distinct outcomes (authenticated:true vs connect_url), which clearly differentiates it from siblings like 'authenticate'.

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 context for two scenarios (all providers connected vs credentials missing) but does not explicitly mention when to use this tool versus alternatives like 'authenticate'. Usage is implied rather than explicitly stated.

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 reveals key behaviors: invoke runs uninstalled MCPs one-off, credential needs return a connect link, paid tools with empty wallet return a checkout link, and writes require workspace owner/admin. It also explains the installed_in_toolkit vs installed_in_workspace flags. 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?

The description is dense and long, but every sentence carries operational value, covering the many actions and edge cases. It front-loads the primary purpose and core flow. It could be improved with bullet points or section breaks, but the lack of fluff justifies a high score.

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—14 actions, 23 params, no output schema—the description covers most core workflows: searching, describing, invoking, installing, listing, billing, reporting, requesting, and the prompt library. It also explains auth, payment, retry, and permission nuances. Missing details like how arguments are structured (JSON string) and the role of parameters like immediate or tier_slug prevent a perfect score.

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 schema description coverage at 0%, the description must compensate and does add meaning for core parameters: action is mapped to the search/describe/invoke flow, tool_id identifies the specific tool, arguments are the params passed to invoke, and prompt_slug/prompt_vars relate to the prompt library. However, many parameters (limit, immediate, tier_slug, cancel_reason, conversation, etc.) are left unexplained, leaving gaps for a 23-parameter tool.

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 is "the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them," and enumerates its core functions (search, describe, invoke, install, prompt library). This specific verb+resource framing distinguishes it from siblings like authenticate, connect, and 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?

The description provides an explicit core flow (search → describe → invoke) and gives practical guidance like "prefer invoke for a single/occasional use" and "Use install only to make an MCP PERMANENT." It also explains when invoke returns connect/checkout links and how to retry. It does not explicitly contrast with sibling tools such as connect or authenticate, but the hub nature is clear enough.

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 non-read-only and non-destructive behavior. The description adds useful context about including the conversation array for reproduction, but it doesn't disclose what happens after submission (e.g., acknowledgment, ticket creation) or any side effects. 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, each earning its place: the first clearly states the purpose, the second gives a crucial usage instruction. No redundant or vague wording.

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 description is too sparse for a tool with no output schema and undocumented parameters. It leaves gaps around how to format the 'conversation' (string vs array), the role of 'context', and what response or outcome to expect after reporting.

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. It explains the purpose of the 'conversation' parameter but not 'message' or 'context'. Also, it calls it 'conversation array' while the schema expects a string, creating ambiguity about serialization.

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 ('Report') and resources ('a bug, missing feature, or send feedback'). It effectively distinguishes this from sibling tools like 'authenticate' or 'show_version' by focusing on issue reporting.

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 for using the tool: to report issues or feedback. The instruction to include the conversation array for reproduction implies when it's useful, and there are no competing alternatives among siblings. However, it doesn't explicitly state 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful context by specifying that both 'MCP platform' and 'adapter' versions are returned, which is beyond what annotations state and clarifies the output scope.

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, coherent sentence with no filler. It front-loads the action verb and immediately specifies the object, making it maximally 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?

For a parameterless, read-only version utility with no output schema, the description fully covers what an agent needs to know: what information is returned. Combined with strong annotations, no additional context is necessary.

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 takes zero parameters, so there is nothing to clarify beyond what the empty schema already shows. Baseline for 0 params is 4, and the description appropriately makes no claims about 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 uses a specific verb ('Show') and names the exact resources ('current MCP platform and adapter versions'), making it unambiguous. This clearly distinguishes it from sibling tools like authenticate, marketplace, or report_bug, which serve 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?

While no alternatives are explicitly named, the context is unambiguous: this is a version-check utility with zero parameters. For such a simple tool, the lack of explicit usage exclusions or when-not-to-use guidance is acceptable; an agent would naturally invoke this when needing version information.

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 useful context about the return payload (state of MCPs, accounts, catalog tools), but does not disclose additional behavioral aspects like rate limits or permission requirements.

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, succinct sentence that front-loads the purpose and concretely enumerates the returned state elements. Every word adds value with no 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, read-only, parameterless tool, the description fully explains what the agent will receive. It covers all relevant aspects of the toolkit state and does not need an output schema since the return contents are clearly enumerated.

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 description has nothing to explain. The schema is empty and coverage is trivially 100%; the baseline for 0 params is 4, and the description adds no param details because none are 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 states a specific verb ('Returns') and resource ('current toolkit state') with detailed scope: installed MCPs, connection status, accounts, and catalog tool counts. This clearly distinguishes it 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?

No guidance is provided on when to use this tool versus alternatives. The description only explains what it returns, not when to invoke it or that, for example, show_version might be more appropriate for version-specific info.

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 mark the tool as read-only and idempotent, and the description adds further context: it queries public-access data, clarifies it is not private, and notes LGPD responsibilities. It also mentions the payment model, which is a behavioral trait not in 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 2 sentences and front-loads the core purpose. It packs essential operational and legal details without fluff, though it is 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?

The description covers data source, payment, and legal aspects, but with no output schema it omits any indication of return values or error behavior. The CPF/CNPJ ambiguity is also unresolved, weakening completeness.

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 names CPF/CNPJ and region as query inputs, giving them meaning beyond the schema's bare type declarations. However, it does not describe the optional 'completo' boolean, and the schema marks both Cpf and Cnpj as required, which contradicts the 'ou' (or) phrasing in the description, leaving ambiguity.

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 'Consulta processos de uma pessoa ou empresa no TRT', clearly stating the action (query) and the resource (labor court cases). It specifies the inputs (CPF/CNPJ and region), distinguishing it from the sibling tools which are 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 explains the operational context: hosted on the platform, requires no credentials, and is paid per query with prepaid credit. It does not explicitly state alternatives or exclusions, but the unique purpose among siblings makes this less critical.

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