Tribunal TRT10: Certidão Eletrônica de Ações Trabalhistas (CEAT) - Processos Digitais

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

The description adds useful behavioral context beyond the annotations: it reveals that calling with no args returns a login link, and that pasted tokens create session-only authentication while config-header tokens are permanent and non-expiring. The behavior does not contradict the idempotentHint or other 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 compact and information-dense, packing purpose, usage modes, and call syntax into two sentences. It is not perfectly structured, but every sentence adds necessary guidance and there is little 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 simple auth tool with one optional parameter, the description is largely complete: it covers the login flow, token acquisition, permanent vs. session configuration, and invocation patterns. It does not detail the exact return value when a token is passed, but it provides enough context 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?

With schema description coverage at 0%, the description carries the full burden, and it succeeds: it explains that the optional token is a JWT, how to pass it, and what happens when it is omitted. This gives the agent clear, actionable parameter semantics beyond the bare 'token' string property.

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 centers on authenticating to MCP.AI for IDE agents, describing a login flow and token-handling behavior. It is specific to this tool's auth purpose, though it does not explicitly contrast itself with sibling tools like '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 concrete usage guidance: either configure an Authorization header for a permanent connection or paste a token for a session-only login. It clearly explains when to call without args versus with a token, though it doesn't explicitly state when not to use this tool versus alternatives.

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 non-destructive behavior. The description adds beyond annotations by specifying the conditional output shape: authenticated:true with empty pending[] versus connect_url and per-install URLs when credentials are absent. This is valuable behavioral 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 exactly two sentences, front-loaded with the main purpose, and every clause adds meaningful information about return behavior. No filler 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 zero-input, read-only status tool with rich annotations and no output schema, the description fully explains the two relevant response scenarios. It names the key fields (authenticated, pending[], connect_url) and gives enough context for an agent to invoke and interpret 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?

The tool has zero parameters and schema coverage is 100%. With no params to explain, the description is not required to add parameter semantics; the baseline of 4 is appropriate and the description does not omit anything necessary.

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 a specific verb+resource ('Returns connection status and URLs'), then clarifies the two possible result states. It clearly distinguishes from sibling tools like 'authenticate' by defining this as a status/URL inspection operation, not an auth-flow trigger.

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?

Clear context is provided: use this tool when checking whether providers are connected or when you need connect URLs. The conditional behavior ('When credentials are missing...') implies when authentication setup is needed, though it does not explicitly name 'authenticate' as the alternative.

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 annotations (readOnlyHint=false, openWorldHint=true), the description discloses critical behaviors: invoke works even for non-installed MCPs, returns connect/checkout links for auth/payment gaps, and writes require workspace owner/admin. It also explains the prompt library side-system, giving full visibility into 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 long but every section contributes value, covering core flow, edge cases, permissions, and prompt library. It is front-loaded with the main purpose and flows logically, though it is a dense single block with minor language inconsistencies (e.g., 'pontualmente') rather than structured bullets.

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 multi-action marketplace hub with no output schema, the description is remarkably complete: it covers discovery, profiling, execution, installation lifecycle, billing, reporting, feature requests, prompt library, and permission requirements. Minor omissions like the 'resume' action don't undermine overall usability.

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 23 parameters and 0% schema coverage, the description carries the burden and largely succeeds: it defines the action enum roles, the use of mcp_id/tool_id/arguments, and prompt-related fields. However, several parameters (immediate, tier_slug, cancel_reason, conversation, report_context) remain unexplained, leaving some semantics uncovered.

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 execution layer, with a specific action-based flow (search, describe, invoke). It distinguishes its role from sibling operations like report_bug and request_mcp, so the purpose is unambiguous and differentiated.

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: use search→describe→invoke for discovery/execution, prefer invoke for one-off use, install only for permanent toolkit membership, list_tools for current callables, and request_mcp when nothing fits. It clearly states when to use each internal action versus alternatives.

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 the operation is idempotent, non-read-only, and non-destructive. The description adds useful context that recent conversation messages should be included for reproduction, but it does not disclose the processing side effects or what happens after the report is sent.

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 focused sentences, front-loaded with the tool's purpose. Every sentence earns its place, and there is no vague filler.

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, this is a mostly sufficient level of detail given the annotations and simple schema. However, the required message field and optional context field are not meaningfully explained, and the absence of an output schema means the response format is never 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 description coverage is 0%, so the description carries the burden for explaining parameters. It only clarifies the conversation parameter (recent messages for reproduction); the required message parameter and context parameter are left undocumented, and the description's 'conversation array' wording does not match the schema's string type.

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 clear resource targets ('bug, missing feature, feedback'), making the tool's purpose immediately obvious. It is clearly distinct from sibling tools 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?

It explicitly states when to use the tool: for bugs, missing features, or feedback. It also instructs the agent to include the conversation array for reproduction, but it does not mention when not to use the tool or name alternative 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 readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is clear. The description adds the specific scope of what versions are shown but does not disclose return format or any additional behavioral details 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 one concise, front-loaded sentence with no filler or redundant content. Every word contributes to the tool's purpose.

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?

This is a very simple, zero-parameter read-only tool with no output schema. A single sentence fully conveys what the tool does, and the annotations cover the behavioral contract, making the description 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 the description carries no parameter burden. The baseline score of 4 applies because there is nothing for the description to explain 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 identifies the exact resource ('current MCP platform and adapter versions'). It clearly distinguishes itself from sibling tools like toolkit_info by focusing narrowly on version 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?

The description implies usage when version information is needed, but it does not explicitly state when to use this tool versus alternatives or mention any exclusions. For a trivial version-lookup tool, the implied guidance is 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value by specifying what the state includes (installed MCPs, connection status, accounts, catalog tool counts), but does not disclose behaviors like potential latency or staleness of data. With annotations covering safety, a 3 is appropriate.

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 sentence, directly front-loaded with the purpose, and avoids any filler. Every word contributes to explaining what the tool returns, making it optimally 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 zero-parameter informational tool with clear annotations and a descriptive name, the description covers the key aspects of the returned state. It doesn't detail the exact format of the output, but no output schema exists, so the description's summary of the state components is reasonably complete, though a bit more detail on the structure could enhance usefulness.

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, which the schema fully covers (100% coverage with empty properties). The description adds contextual meaning about the output (toolkit state) even though no parameters exist, making it a baseline 4.

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: returning current toolkit state, listing installed MCPs, connection status, accounts, and catalog tool counts. It distinguishes itself from siblings like authenticate, connect, marketplace, and show_version by focusing on state inspection rather than actions.

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 status, but does not explicitly state when to use it vs. alternatives. Given it's an informational tool with no alternatives for this specific state summary, the context is clear but lacks explicit 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?

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint, and the description adds meaningful context beyond them: the paid per-query behavior, absence of platform credentials, official-source nature, and LGPD data-controller responsibility. This is valuable supplementary behavioral 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 reasonably structured but includes some repetition such as 'consulta em fonte oficial' and 'Consulta informação de fontes [...] oficiais'. The information is relevant overall, but it could be tightened 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 description gives useful context about official sources, prepaid credit, non-confidential data, and LGPD compliance. However, because there is no output schema, it does not explain the response shape/certificate return or how the query parameters interact, leaving significant gaps for successful 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 schema description coverage is 0%, and the description does not explain how CPF, CNPJ, or nome should be used, which of them is preferred, or what is required. The parameter names are self-evident, but the description adds little to no 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 explicitly identifies the tool as a consultation of TRT10 CEAT (Certidão Eletrônica de Ações Trabalhistas) from an official source, with the scope of digital processes. It is clearly distinct from the sibling tools, none of which relate to tribunal certificate queries.

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 useful context: the tool requires no platform credentials, is paid per query with prepaid credit, and only accesses official data already available to citizens. It does not explicitly name alternatives or exclusions, but there are no similar sibling tools and the usage setting is sufficiently clear.

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