Tribunal TRT10: Certidão Eletrônica de Ações Trabalhistas (CEAT)

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

Annotations already provide readOnlyHint=false and destructiveHint=false, but the description adds important behavioral context: that it involves browser login and token generation, that the token can be permanently configured, and that calling without args returns a link. It also implicitly communicates that this is an interactive flow requiring user action. This goes beyond the annotations, though it could disclose side effects like potential session persistence or security implications more deeply.

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, two sentences long, and front-loaded with the tool's purpose. Each sentence adds value: first explains the core mechanism, second gives two usage paths. Slight room for improvement: some redundancy between 'log in in the browser' and 'call with no args to get the link' could be trimmed, but it's appropriately sized and not overly verbose.

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 has one optional parameter and no output schema, the description covers the essential flow: how to use it, both invocation modes, and the recommended permanent setup. It doesn't explain the return value (likely a link) explicitly, but that's inferable from 'get the link'. It also lacks details on error handling or token validation, but for a simple auth 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 only defines a 'token' parameter with no description coverage (0%), so the description must compensate. It does: it explains the 'token' parameter is a JWT that the user pastes for session-only login, and that omitting it triggers a link generation. This adds semantic meaning beyond the bare schema, though it could specify format or constraints more explicitly.

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 by logging in via browser and capturing an access token. It distinguishes itself from siblings by focusing on authentication, while siblings like 'connect' or 'marketplace' imply different actions. The verb 'authenticate' with explicit resource (MCP.AI) and method (browser login) is specific and 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 explicitly provides when to use this tool and how: it gives two usage modes (session-only with a token argument, or permanent with config header), and even instructs to call with no args to get the link. It also suggests the best practice (config header) and distinguishes between session and permanent options, covering alternatives within the tool's scope. It doesn't pit it against siblings but clearly defines usage scenarios.

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 safety. The description adds value by detailing state-dependent responses (authenticated:true vs. connect_url), which is behavior beyond 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 with no filler. The description is front-loaded with the primary function and then clarifies conditional 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 with strong annotations and no output schema, the description sufficiently covers what the tool does and the possible return states. It could mention the specific format of URLs but it's 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?

Tool has zero parameters, so baseline is 4. The description provides all necessary semantic context since no parameters exist to explain.

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, which is specific and distinguishes it from sibling tools like 'authenticate' that likely initiate the connection flow. However, it doesn't explicitly mention alternatives, so it lacks the perfect clarity of naming 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 explains when each output appears (all providers connected vs. missing credentials), which gives context for when this tool is useful. It doesn't explicitly state when to use it over 'authenticate', but the implied usage is clear enough for a status-check 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 critical behavioral traits beyond the annotations. It explains that invoke works even when the MCP is not installed ('runs it pontualmente (one-off)') and avoids bloating the tool list. It details that invoke returns a connect link if credentials are needed and a checkout/top-up link if the wallet is empty, instructing to retry after user action. It also states that writes require workspace owner/admin. These details align with the annotations (readOnlyHint=false, openWorldHint=true) and add significant context 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 dense but efficient, packing the core flow, key exceptions, permission requirements, and the prompt library into a single paragraph. It is front-loaded with the primary purpose and flow, and every sentence adds value. However, the long run-on structure could be broken into clearer sections for readability, though it remains appropriately sized given 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 tool with 23 parameters, no output schema, and no parameter descriptions, the description is remarkably complete. It covers the entire decision tree: how to search, describe, invoke, install, handle credentials, handle payments, and manage billing. It also explains the prompt library side. The absence of return value details is acceptable since there is no output schema, and the description gives enough context for an agent to know what to expect from each action.

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 has 23 parameters with zero descriptions, so the description carries the burden of explaining how to use them. It does so by describing the action enum values (search, describe, install, invoke, etc.) and their roles, and clarifies key parameters like mcp_id, tool_id, and arguments through the core flow. It also explains the special behaviors of invoke (connect/checkout links) that map to arguments and prompt_vars. While it doesn't detail every parameter (e.g., prompt_title), it compensates significantly for the schema gap by providing the conceptual framework needed to use the tool correctly.

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' and explains its dual role as a catalog of every MCP/tool and the mechanism to run them. It enumerates specific capabilities (search, describe, invoke, install, prompt library) and includes example intents like "find an MCP that does X" and "consulta um CPF". This distinguishes it from sibling tools like authenticate or toolkit_info, which have narrower 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 provides explicit usage guidance, including a core flow: 'action=search discovers MCPs by intent → describe returns one MCP's full profile ... → invoke RUNS that tool.' It also states when to use install vs invoke: 'Use install only to make an MCP PERMANENT in the active toolkit ... prefer invoke for a single/occasional use.' It explains subscribe/cancel, report_bug, request_mcp, and the prompt library actions, offering clear context for when each action is appropriate.

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, and the description does not contradict them. The instruction to include the conversation array adds useful reproduction context, but it does not disclose external side effects, what happens after submission, or any potential duplicate-report concerns.

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: the first states the purpose, the second provides key usage guidance. No wasted words or repetition, and the most important information is front-loaded.

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-reporting tool with no output schema, the description covers the core purpose and one key input. However, it omits expected behavior after submission and leaves two parameters undefined, making it only minimally viable.

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 for explaining parameters. It only clarifies the purpose of the conversation field. The required message parameter and the context parameter receive no explicit semantic explanation, leaving the agent to infer their roles.

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 starts with a clear verb and resource: report a bug, missing feature, or send feedback. This clearly differentiates it from the unrelated sibling tools (authenticate, show_version, toolkit_info, 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 explicitly identifies when to use the tool (bug, feature request, feedback) and instructs to include the conversation array for reproduction. It gives clear context without exclusions, which is acceptable given that no sibling is a feedback/reporting 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, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds the 'current' nuance and clarifies it reports both platform and adapter versions, but does not disclose return format or any other behavior.

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 delivers the complete purpose with no filler. Every word contributes 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?

For a trivial zero-parameter tool with rich annotations, the description is sufficiently complete. It could mention the output format, but given the simplicity and the read-only/idempotent annotations, the current level is 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?

The tool has zero parameters and 100% schema coverage, so the baseline is 4. The description does not need to explain parameters; it appropriately focuses on what the tool returns.

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 action ('Show') and specific resource ('current MCP platform and adapter versions'). It distinguishes itself from sibling tools like authenticate or marketplace, which are unrelated to version 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?

No guidance is provided on when to use this tool versus alternatives or whether any prerequisites exist. For a simple version query this is understandable, but the description offers no explicit context.

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 adds meaningful context beyond the annotations by detailing precisely what the returned toolkit state includes. It aligns with the readOnlyHint and idempotentHint, confirming a side-effect-free read operation. It does not describe the return format or refresh behavior, but the annotations already cover the safety profile.

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, information-dense sentence that front-loads the verb and resource, then lists specific elements without any filler or redundancy. Every word contributes to the meaning, making it highly concise and well-structured.

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 no parameters and no output schema, the description is sufficiently complete, clearly listing what information is returned. It could mention whether the state is cached or real-time, but such details are not critical for a basic status-reporting tool. The description covers the essential context needed for an agent to use the tool effectively.

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 about parameter semantics. The schema is empty, and the baseline of 4 for 0-parameter tools is appropriate. The description does not need to compensate for any parameter documentation gaps.

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 resource ('current toolkit state'), then enumerates the exact items returned (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from sibling tools like show_version or connect, 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?

The description implies usage for checking toolkit state but provides no explicit guidance on when to use this tool versus alternatives. It does not mention any conditions, prerequisites, or exclusions, leaving the usage context to be inferred.

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, and the description adds meaningful behavioral context: prepaid payment, official-source limitation, non-confidential status, and LGPD controller responsibility. It does not cover response format or failure modes, but the annotation coverage lowers the burden.

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 one dense, front-loaded sentence that packs purpose, payment model, data source, and legal context without filler. It earns a high score, though a slight redundancy exists between "fonte oficial" and "fontes e órgãos oficiais brasileiros," preventing a 5.

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 no output schema, the description only implies the return is the CEAT certificate and does not explain what information the result contains. It is adequate for a simple read-only query but leaves gaps around parameter usage and expected response, so it is not fully 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?

Schema description coverage is 0%, so the description must compensate, but it does not explain the relationship between cpf, cnpj, and nome, nor that none are required. Parameter names are self-explanatory, but the agent is left without guidance on valid combinations, cardinality, or minimum identifier requirements for a CEAT lookup.

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 a CEAT (Certidão Eletrônica de Ações Trabalhistas) query for TRT10, using the resource-specific verb "consulta em fonte oficial." It is unambiguous and stands apart from the sibling tools by explicitly stating "sem credenciais da plataforma," distinguishing it from authentication/platform operations.

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: the tool is hosted by the platform, requires no platform credentials, charges prepaid credits per query, and is limited to non-confidential official data. It gives legal usage context (LGPD) but does not explicitly state when not to use it or name alternative tools, which would make it a 5.

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