Tribunal TRT2: Certidão Eletrônica de Ações Trabalhistas (CEAT) - Processos Digitais

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

The description explains behavioral aspects beyond annotations: it clarifies that the tool can either return a login link (when called without token) or accept a token to complete authentication. It also contrasts permanent vs session-only modes. It does not contradict the idempotentHint annotation, but it omits details about response format and potential errors, leaving some gaps.

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 composed of three dense sentences with no fluff. It front-loads the core purpose and then details usage patterns. It is slightly longer than necessary but each part adds value, so it earns a 4 rather than 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?

Given the lack of an output schema, the description covers the main workflow and parameter usage well. However, it does not describe the expected result of a successful login (e.g., confirmation message or stored state), nor any error conditions (like invalid token). For a simple auth tool, it's fairly complete, but additional outcome details would push it to 5.

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 an optional 'token' string with no description, but the tool description fully explains its meaning: passing a JWT token initiates login, and omitting it returns a link. This adds complete semantic meaning beyond the 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 authenticates to MCP.AI, with specific verb 'log in' and resource 'MCP.AI', and distinguishes from sibling tools like connect and marketplace by focusing on token acquisition and login flow.

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 explicit usage instructions: the best practice of adding the token to the server config for a permanent connection, and the alternative of passing the token as a parameter for session-only login, plus how to call with no args to get the link. This clearly defines when and how to use the 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 readOnly, idempotent, and non-destructive behavior. The description adds valuable conditional behavior: authenticated=true with empty pending[], and connect_url/per-install URLs when credentials are missing. 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 sentences, no wasted words. The first sentence states the core purpose, and the second explains the key conditional outcomes. Information is front-loaded and easy to parse.

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, the description covers both success and failure states and mentions the return payload elements. It does not fully specify the structure of pending[] or per-install URLs, but this is not essential for correct invocation and is partly covered by 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?

This tool has zero parameters and an empty schema properties object, so parameter semantics are not applicable. The baseline for a zero-parameter tool is 4; the description appropriately focuses on output behavior instead.

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 names the resource ('connection status and URLs'). It also distinguishes this from sibling tools like authenticate by focusing on read-only status 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 gives clear behavioral context (all providers connected vs. credentials missing) that implies when this tool is useful. However, it does not explicitly state when to use connect versus authenticate or other sibling tools, so usage guidance is implied rather than 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 give only readOnlyHint=false, openWorldHint=true, no idempotency. The description adds substantial behavioral context beyond these: invoke runs one-off without installing or bloating the tool list, credential/wallet states return connect/checkout links with an explicit retry instruction, writes require owner/admin, and publish_prompt returns a login-free share link. No contradiction with annotations. Minor gap: does not describe the output format of invoke/search results.

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?

Every sentence carries real information and the content is front-loaded with the core purpose. However, it is a single ~300-word unbroken paragraph with no bullets, headers, or action breakdown — the 14 actions and their nuances blur together. Length is justified by complexity, but the lack of structure significantly hurts scannability for an agent parsing this description.

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 14 actions, 23 params, minimal annotations, and no output schema, the description is remarkably complete: the core flow, invoke edge cases (non-installed execution, connect/checkout retry loop), install-vs-invoke decision, permission requirements, installed_in_toolkit vs installed_in_workspace flags, and the entire prompt library subsystem are all covered. Gaps: exact shape of describe's profile output and mechanics of conversation/vars params. Still, it's about as complete as a hub-tool description gets without becoming bloated.

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 the description carries the full burden. It meaningfully explains the core workflow parameters (action enum, mcp_id, tool_id, arguments, query, prompt slugs/vars) by mapping them into the search→describe→invoke flow and the prompt library. However, several params remain unexplained (conversation, tier_slug, immediate, request_name, cancel_reason/cancel_comment, prompt_targets). Partial compensation for the 0% coverage, but a 23-param surface deserves more param-level 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 this is the mcp.ai marketplace — the catalog of every MCP/tool AND the mechanism to run them. It explicitly enumerates each action's purpose (search discovers, describe returns a profile, invoke runs, install makes permanent, etc.) and distinguishes itself from sibling tools like authenticate/connect/toolkit_info. For a composite tool with 14 actions, the purpose is exceptionally well defined.

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?

Extremely explicit usage guidance: 'prefer invoke for a single/occasional use' vs 'use install only to make an MCP PERMANENT', the auto-retry flow after connect/checkout links, and 'request_mcp asks us to build a NEW MCP when nothing fits'. It also documents the write-permission requirement (owner/admin). This is model usage guidance — when, when-not, and named 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 provide basic mutability information (readOnly=false, destructive=false, idempotent=true). The description adds the useful behavior that the conversation array is needed for reproduction, but does not describe post-submission behavior or data handling. There is no contradiction with 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 only two sentences: the first states the purpose, the second gives actionable guidance about the conversation parameter. It is tightly written with no 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 bug-reporting tool, the description covers the core purpose and the key reproduction requirement. The lack of an output schema and the unexplained 'context' parameter are minor gaps, but the tool is still understandable enough for an agent to invoke correctly.

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. It clarifies the 'conversation' parameter's purpose (reproduction via recent messages) and implies 'message' is the report text, but leaves 'context' completely unexplained. Compensation is incomplete for a 3-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 uses the specific verb 'Report' and names the exact resources: bugs, missing features, and feedback. This clearly differentiates the tool from its unrelated siblings like authenticate and show_version.

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 for when to use the tool: to report a bug, missing feature, or feedback. It does not name alternatives or exclusions, but the sibling tools are unrelated, so this is not a meaningful gap.

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 read-only, idempotent, and non-destructive behavior. The description adds no additional behavioral details, but it is consistent with 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, clear sentence with no redundant information. It effectively conveys 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?

With no parameters and no output specification, the description fully explains what the tool does. Combined with the annotations, it provides complete 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?

There are no parameters in the input schema, so there is nothing to explain. The description is sufficient.

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 shows current MCP platform and adapter versions. It uses a specific verb and resource, distinguishing 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 that this tool is for retrieving version information, which is clear for typical usage. However, it doesn't explicitly mention alternatives or when not to use it, but given its simple nature, it's adequate.

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 detail about the output but does not disclose additional behavioral traits such as authentication requirements, rate limits, or potential side effects. The readOnlyHint annotation covers the main non-mutating aspect, but no extra context is provided.

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, clear sentence that efficiently conveys the tool's purpose and output without unnecessary details. It is well-structured and easy to parse.

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 getter with no parameters and no output schema, the description fully explains what the tool returns. It does not require additional context to be usable.

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, and the schema coverage is complete (empty schema). The description does not need to elaborate on parameters, so this meets the baseline expectation.

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 and enumerates the specific details included (installed MCPs, connection status, accounts, and catalog tool counts). This makes the purpose unambiguous and distinct from sibling tools like 'show_version'.

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 the tool is for retrieving toolkit state, but it does not explicitly state when to use it or contrast it with alternatives. Since no sibling tool is closely related, this 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 and idempotentHint=true, so the safety profile is known. The description adds valuable context: payment requirement (pre-paid credit), data source (official Brazilian sources), and privacy responsibility (client as controller). It reveals that the tool incurs cost, which is not in annotations, and clarifies the data is not confidential.

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, each sentence adds meaningful information: the first states the core function and source, the second covers operational and legal aspects. It is appropriately sized and front-loaded with the purpose. 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?

While the annotations cover read-only and idempotent behavior, the description does not explain what the tool returns (no output schema exists) or how parameters should be provided. It also omits any note about parameter requirements (e.g., needing at least one of CPF/CNPJ) and does not detail post-consultation steps. The tool is moderately simple, but the lack of parameter and output information leaves significant gaps.

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% and the description does not mention the parameters (cpf, cnpj_raiz) at all. With no explanation of what these fields represent or their usage (e.g., either CPF or CNPJ root), the agent has no guidance on how to populate them. The description completely fails to compensate for the sparse 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 it consults the CEAT certificate for TRT2, mentioning specific verb ('consulta') and resource ('Certidão Eletrônica de Ações Trabalhistas'). It distinguishes itself from generic platform siblings (authenticate, connect, etc.) by focusing on a specific tribunal and document type.

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 about the tool's purpose (official source, citizen-accessible data) and operational constraints (pre-paid credit, LGPD compliance). It does not explicitly state when to use it versus alternatives, but no similar consultation tools exist among siblings, so exclusions are implicit.

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