Tribunal TRT14: Certidão Eletrônica de Ações Trabalhistas (CEAT)

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

The description discloses the behavioral differences between passing a token (session-only) and configuring the header (permanent, non-expiring), and explains the effect of calling with no args (returns login link). This adds meaningful context beyond the annotations, which only state idempotent and non-destructive.

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 sentences, compact yet rich. It leads with purpose and then details two authentication paths. While slightly long, every clause contributes essential information, so it earns 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?

The description covers the tool's purpose, usage modes, parameter semantics, and behavioral outcomes. It lacks explicit mention of return values, but since no output schema exists, this is a minor gap given the self-explanatory nature of authentication outcomes.

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 assumes full responsibility for explaining the 'token' parameter. It defines it as a JWT, optional, used for session-only login, and explains the no-args alternative. This completely compensates for the schema's lack of detail.

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 the user via browser login and token exchange. It specifies the resource (server access) and distinguishes between permanent and session-based login, making it 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 instructions: adding the token to config for permanent access, or passing it as a parameter for session-only login, or calling with no args to get a login link. It does not explicitly compare with sibling tools like 'connect', but the authentication scope is clear.

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 detail beyond the annotations (readOnlyHint, idempotentHint, etc.) by specifying the response conditions: 'When all providers are connected, returns authenticated:true and empty pending[].' This clarifies expected behavior without contradicting 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 two concise sentences that front-load the core purpose and then provide conditional details. Every word adds value, with no redundancy or 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?

Given the tool has no parameters and no output schema, the description is highly complete. It covers the primary success case, the partial case, and the failure case (missing credentials), providing URLs and status flags. This fully satisfies the informational needs for a read-only status 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?

With zero parameters, there is nothing to explain beyond the schema. The baseline of 4 applies because the description correctly omits parameter details, and no additional semantic information 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 clearly states the tool's function: 'Returns connection status and URLs.' This specific verb-and-resource phrasing distinguishes it from sibling tools, especially 'authenticate' which actually performs authentication rather than reporting status.

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 behavioral context for when to use the tool: it explains what happens when all providers are connected versus when credentials are missing, implying it is the correct tool for checking connection state. However, it does not explicitly name alternatives for comparison, relying on the sibling list instead.

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 annotations: invoke works without installation, returns connect/checkout links for auth/payment, writes require workspace owner/admin, and install is for permanent addition. This supplements the sparse annotations (readOnlyHint=false, etc.) with rich operational 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 dense, single-paragraph wall of text but every sentence adds value. It is front-loaded with the core purpose and flow, though better structuring (e.g., bullets) would improve scannability. Still, the length is justified given the tool's 14 actions and 23 parameters.

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 the core flow, install vs invoke, billing, auth, and the prompt library, which is impressive for a tool with no output schema. It lacks detail on return formats (beyond connect/checkout links) and some secondary actions (resume, report_bug exact behavior), but overall it is quite complete for an agent to use 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 0% schema coverage, the description compensates by explaining the meaning of key parameters like action, mcp_id, tool_id, arguments, and prompt-related fields. However, it omits several parameters (limit, immediate, tier_slug, conversation, cancel_reason, etc.), leaving some semantics undefined, though the main flow is well covered.

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 catalog and runtime, with an explicit core flow (search → describe → invoke). It distinguishes itself from siblings by covering both discovery and execution of MCPs, plus the prompt library, making its purpose unmistakable.

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 guidance: prefer invoke for one-off use vs install for permanent use, use list_tools for currently callable tools, and use request_mcp when nothing fits. It also explains when to use search/describe/invoke in the core flow, giving clear alternatives and 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 indicate the tool is idempotent and non-destructive, but the description doesn't elaborate on side effects like sending a report or creating a ticket. It adds minimal behavioral context beyond what annotations already imply.

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, consisting of two clear sentences with no redundant information. It directly conveys the tool's purpose and a key requirement for the conversation parameter.

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 essential action and the need for conversation data. It does not specify the outcome or confirmation after reporting, but this is somewhat mitigated by the idempotent annotation and the simple nature of the task.

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% for parameters. The description only clarifies the 'conversation' parameter by mentioning it should contain recent messages for reproduction, leaving 'context' and 'message' unexplained. This is insufficient compensation for the lack of parameter details.

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: reporting bugs, missing features, or sending feedback. It is specific and distinguishes itself from sibling tools that likely serve different purposes like authentication or 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 implies usage when a bug or feedback needs to be reported, but does not explicitly state when to use this tool over alternatives. It lacks guidance on conditions or exclusions, though it does mention including the conversation array for reproduction.

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 minor context ('MCP platform and adapter') but doesn't go beyond what's obvious from the tool name. No contradiction with annotations, but also no additional behavioral context like return format or authentication needs.

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, clear sentence with no fluff. 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?

For a zero-parameter, read-only version-info tool with no output schema, the description is sufficient. It could theoretically mention return structure, but it's not necessary given the tool's simplicity and the presence of 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?

Tool has zero parameters, so schema coverage is trivially 100%. The description doesn't need to explain parameters; baseline of 4 is appropriate.

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 clearly states the tool shows 'current MCP platform and adapter versions', using a specific verb and resource with no ambiguity. It distinguishes itself from sibling tools like connect and authenticate which have 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?

Usage is implicitly understood (run when you need version info), but no explicit guidance is given about when to prefer this over alternatives like toolkit_info, or when not to use it. Meets the 'implied usage' criterion.

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, and the description does not contradict these. The description adds useful detail about what 'toolkit state' includes, extending beyond the generic annotation-provided 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 sentence that begins with the main action and resource, then enumerates the exact data points returned. Every word earns its place and there is no redundancy or 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?

Given the tool has no parameters, no output schema, and clear read-only/idempotent annotations, this description is sufficient. It explicitly names the categories of information the agent will receive, making the tool's scope fully comprehensible.

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 zero parameters, so the schema needs no additional explanation. The description provides the relevant semantics entirely through its explanation of what output 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 returns the current toolkit state, enumerating specific content: installed MCPs, connection status, connected accounts, and catalog tool counts. This is a specific verb+resource combo that distinguishes it from sibling tools like authenticate 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?

The description implies it should be used when an agent needs an overview or diagnostic snapshot of the current toolkit. It does not explicitly list exclusions or compare with alternatives, but the zero-parameter, read-only nature and clear resource scope make the intended usage obvious.

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 behavioral details beyond the annotations: it indicates that no credentials are needed, that payment is required, and that the data is not confidential. These are useful and do not contradict the readOnly/idempotent hints provided in 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 relatively concise but contains slight redundancy (e.g., repeating 'fonte oficial' and 'oficiais brasileiros'). Still, it is short and directly relevant, with no unnecessary 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?

It covers the core purpose, access, and cost, but lacks information about the output (e.g., what the returned certificate contains) and does not elaborate on edge cases or usage context. Given the simplicity of the tool, this is adequate but not comprehensive.

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 does not explain any of the three parameters (cpf, cnpj, nome). Since the schema lacks descriptions and the tool description provides no hints about what these parameters mean, the description adds no value to parameter understanding.

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 performs a consultation (consulta) of the Electronic Certificate of Labor Actions (CEAT) from an official source, which is a specific verb and resource. It distinguishes itself from generic sibling tools like 'authenticate' or 'show_version' by specifying the domain.

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 mentions that the query is from an official source, is hosted on the platform, requires no platform credentials, and is paid per query with prepaid credits. While this gives context on cost and access, it does not explicitly state when to use this tool versus alternatives or 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.