Tribunal TRT16: Certidão Eletrônica de Ações Trabalhistas (CEAT)

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

Beyond the annotations, the description discloses important behavioral details: config-based auth becomes permanent and non-expiring, pasted-token auth is session-only, and no-args returns a link. It leaves some details unmentioned, such as error behavior when an invalid token is supplied.

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 compact, with no major redundancy, and all sentences contribute invocation or usage information. Its structure is slightly dense but still scannable.

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 one-parameter authentication tool, it covers persistent config, session-only login, and the no-argument link flow. It does not specify exact response shapes or failure modes, but the absence of an output schema makes this acceptable.

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%, but the description compensates for the one optional `token` parameter by explaining that it is a JWT pasted by the user and that omitting it yields the login link. This is adequate for a single optional string parameter.

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 this as the authentication tool for MCP.AI/IDE agents, explaining the browser login and token flow. It successfully conveys the tool's distinct purpose, though it does not explicitly contrast it with the sibling tool `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 gives strong situational guidance: prefer adding the token to the server config for a permanent connection, use a pasted token for session-only login, or call with no arguments to obtain the login link. It does not state exclusions or contrast with alternative auth-related sibling tools.

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, non-destructive behavior. The description adds valuable state-dependent behavioral details—what is returned when all providers are connected versus when credentials are missing—without contradicting 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 core purpose, and every clause adds meaningful information. No filler or repetition of what annotations already state.

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 tool with no output schema, the description sufficiently covers the expected return states and observable behavior. It tells the agent what to expect and when, making it complete for selection and 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?

The tool has zero parameters, so there is no parameter semantics burden. The baseline of 4 is appropriate because there is nothing for the description to explain beyond its current clear input expectations.

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 outputs. It distinguishes itself from the sibling authenticate tool by focusing on status reporting rather than initiating 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 provides clear situational context: use this to check whether all providers are connected or to retrieve connection URLs when credentials are missing. It does not explicitly name alternatives, but the use case is evident.

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, etc.), the description discloses critical behaviors: invoke works even if the MCP is not installed, returns connect/checkout links when needed, and does not bloat the toolkit. It also explains the prompt library separately, and notes that writes require privileged roles. 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 long but front-loaded with the core purpose and flow, then dives into key distinctions (invoke vs install, permissions) and auxiliary features (prompt library). It uses formatting like 'KEY:' and 'USE' to guide attention. Every sentence adds value, though the single-paragraph format with many clauses makes it dense; a few more line breaks would improve scannability without losing 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?

Given the tool's high complexity (14 actions, 23 params, permissions, auth/payment flows, prompt library), the description covers the major usage patterns, prerequisites, and side effects. It explains the search/describe/invoke chain, install vs invoke semantics, credential/top-up handling, and the prompt library. It does not detail exact return formats for every action (e.g., list_tools output), but that is beyond the essential 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?

With schema description coverage at 0%, the description compensates by explaining the key workflow parameters: action values (search, describe, invoke, etc.), mcp_id, tool_id, arguments, and prompt-related params like prompt_vars and prompt_slug. It connects parameters to concrete steps (e.g., 'describe returns... so you pick the right tool_id → invoke RUNS that tool'). However, not all 23 parameters are individually explained; some defaults and optional ones are left implicit.

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 it is 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It enumerates a core flow (search → describe → invoke) and lists 14 distinct actions, making it unmistakable what the tool does. It distinguishes itself from siblings by being the central catalog/execution hub, covering capability requests like 'find an MCP that does X'.

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?

Explicit guidance is provided: 'USE install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use.' It also states permission requirements ('Writes require workspace owner/admin') and clarifies when to use search vs describe vs invoke. Alternatives are implied through the flow description.

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 it's non-read-only, non-destructive, and idempotent. The description adds that the conversation array is used 'for reproduction', which gives minor insight into how the data is used but doesn't explain side effects, privacy, or what happens after submission. It's adequate but not rich.

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 short, front-loaded sentences. The purpose is immediate, and the instruction about the conversation array is directly relevant. 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?

For a simple reporting tool, the description covers the core use case well, but leaves the 'context' parameter entirely undocumented. Given there is no output schema or return value documentation, the description could have elaborated on expected input format or feedback reception, but overall it's 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?

Schema coverage is 0%, so description carries full burden. It clarifies 'conversation' should contain recent messages, but 'context' and 'message' are left unexplained. Missing required-field semantics for 'message' and the role of 'context' mean more burden should have been placed on the description.

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 its purpose: 'Report a bug, missing feature, or send feedback.' This provides a specific verb (report) and resource (bug/feature/feedback), and is distinct from sibling tools like 'connect' or 'marketplace' which have unrelated goals.

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 clear context on when to use (to report bugs or give feedback) and even instructs to include the conversation array for reproduction. It doesn't explicitly state when not to use or name alternatives, but the intent is clear enough for an agent to select it appropriately.

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. The description adds context by indicating the specific output (platform and adapter versions), but does not disclose additional behavioral traits such as error cases, output format, or whether any call is made.

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 concise sentence with no wasted words. It front-loads the action and object clearly.

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, parameterless, read-only version tool, this description is complete. It states exactly what information will be surfaced, and the annotations cover the safe read-only behavior.

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 parameter semantics are not a burden on the description. Baseline for 0 params is 4; no additional parameter context 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 clear, specific verb—'Show'—and specifies the resource: current MCP platform and adapter versions. This unambiguously distinguishes it from sibling tools like authenticate, connect, and report_bug.

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 phrase 'current versions' implies the appropriate use case: checking the installed platform/adapter versions. However, there is no explicit statement about when to use this over alternatives, when not to use it, or any exclusions.

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, establishing a safe read operation. The description adds value by specifying the exact content returned (installed MCPs, their connection status, connected accounts, and catalog tool counts), providing behavioral detail 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?

The description is a single, front-loaded sentence that lists all return contents without unnecessary words. It is appropriately sized for the simplicity of the tool and earns its place with zero waste.

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), the description fully covers what an agent needs to know: what action is performed and what information is returned. It provides a complete picture for a read-only state inspection 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?

The tool has zero parameters, and the schema is empty with 100% coverage, so there is no parameter information to add. The description correctly avoids inventing unneeded parameter details, which matches the baseline for a parameterless 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 uses a specific verb ('Returns') and clearly identifies the resource ('current toolkit state') with detailed components (installed MCPs, connection status, accounts, catalog tool counts). This makes it unmistakable and distinguishes it from sibling tools like authenticate or show_version, 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 when to use the tool—whenever you need an overview of toolkit state—but does not explicitly contrast it with alternatives like show_version or marketplace. There are no exclusion criteria or 'use this instead' guidance, so usage context is only implicit.

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 read-only and idempotent behavior; the description adds valuable context beyond those: no platform credentials are required, usage costs prepaid credits, the data is not confidential/secret, and LGPD compliance is explicitly put on the client side. This is useful behavioral/operational information that annotations do not capture.

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 short, front-loaded with the primary purpose, and each sentence adds relevant context such as cost, credential requirements, and LGPD implications. There is slight redundancy around "official sources" but the rest is efficient and useful.

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?

Despite good operational context, the description is incomplete for a handling agent: there is no output schema, no explanation of the returned CEAT certificate/content, and no guidance on how the three parameters relate or whether one is required. The tool has only a basic phrase, but for a realistic automated invocation, key invocation details are missing.

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 provides only names/types for cpf, cnpj, and nome, with 0% schema description coverage and no required properties. The description does not compensate: it never explains whether any identifier is required, whether CPF/CNPJ should be mutually exclusive, or what format/combination is valid. The property names provide some intrinsic meaning, but the tool cannot be reliably invoked based on current documentation.

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 names the exact action and resource: "Certidão Eletrônica de Ações Trabalhistas (CEAT), consulta em fonte oficial," making it clear that this tool queries the official TRT16 labor court certificate. It is immediately distinguishable from the sibling tools, which are platform operations like authenticate, connect, and marketplace.

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 clearly positions the tool for consulting official Brazilian public labor-labor data, notes that credentials are not needed, and states that prepaid credits are charged per query. It provides strong usage context, though it does not explicitly state exclusions or when NOT to use it, and there are no analogous court tools among siblings to compare alternatives with.

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