Infrações Trabalhistas (MTE)

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

The description adds context beyond the annotations by explaining the browser-based login flow, the two connection modes (permanent vs. session-only), and the token-handling behavior. It does not contradict the idempotentHint, as repeated calls with the same token are harmless. Minor gap: no mention of error behavior or response format, but the core behavior is transparent.

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 moderately sized but every sentence contributes necessary information. It front-loads the purpose and uses a clear 'Best... Or...' structure. It could be slightly more structured, but it is efficient and not 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?

The description covers the essential aspects: purpose, two authentication methods, and exact call patterns. There is no output schema, and the return value (e.g., a link or success message) is not specified, but for an authentication tool, this is acceptable and the description is complete enough for an agent to invoke it 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?

The input schema has one 'token' property with no description (0% coverage), but the description fully compensates: it explains when to provide a token ('paste it here') and when to omit it ('no args to get the link'), and specifies the expected format ('{ token: "<jwt>" }'). This adds complete 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 is for authentication: 'log in in the browser, copy the access token.' It distinguishes between permanent (config header) and session-only (token) login, and the verb 'authenticate' is specific to the resource. This clearly differentiates it from siblings like 'connect' 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?

Explicit guidance is provided: 'Best: add it to this server's config as a header... for a permanent, non-expiring connection. Or paste it here for a session-only login.' It also explains the exact call patterns for token vs. no-args, leaving no ambiguity about when to use each method.

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 false. The description adds useful context on return values in two scenarios (all connected vs missing credentials), which goes beyond the annotations. No contradictions.

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 that immediately state the primary output and then explain behavior under specific conditions. Every sentence adds value with no 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 simple no-parameter status tool, the description fully explains the output format in both normal and degraded states. No output schema exists, but the description covers what the agent needs to know about return values.

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 takes zero parameters, so there are no parameter semantics to clarify. Per rules, 0 params merits a baseline of 4, and the description does not need to compensate for schema 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 returns connection status and URLs, with specific behavior for connected vs missing credentials. This distinguishes it from siblings like authenticate, which perform authentication 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 when to use the tool (to check connection status) and explains expected outputs in different states, but does not explicitly exclude alternatives or mention when not to use it. The context is clear enough for an agent to choose this over authenticate.

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, destructiveHint=false), the description discloses important behavior: invoke runs a one-off tool execution without adding the MCP to the toolkit, returns connect or checkout links for auth/billing gaps with a retry instruction, and install/uninstall/subscribe/cancel are permanent/write actions requiring owner/admin. It also mentions installed_in_toolkit vs installed_in_workspace flags.

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 block of prose with multiple embedded clauses and a bilingual phrase ('pontualmente'), making it harder to scan. It contains valuable information, but structure is weak — no bullet lists or clear separation of the marketplace domain, prompt library, and billing/subscription behaviors. It is not concise given the number of concepts packed in.

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 complex multi-action tool with no output schema, the description covers the core flows, auth and payment edge cases, write permissions, installed flags, and the prompt library. Gaps remain: the 'resume' action is listed but never explained, and normal return value behavior for invoke/describe/search is not described. Still, the description is substantially complete for an agent to operate the tool successfully in most scenarios.

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 full burden, and it does explain core parameters like action, tool_id, mcp_id (implicitly), query, and arguments. However, many parameters remain unexplained: limit, immediate, tier_slug, conversation, cancel_reason, cancel_comment, report_context, and most prompt_* parameters. The description compensates for part of the gap but leaves a large remainder undocumented.

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' — an in-platform catalog and runner for MCPs/tools, plus a prompt library. It states concrete verbs (search, describe, invoke, install, subscribe, request) and distinguishes this tool from siblings by focusing on discovery, one-off execution, and permanent installation.

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 flow guidance: search → describe → invoke, with a clear explanation of when to use invoke vs install ('prefer invoke for a single/occasional use', 'install only to make an MCP PERMANENT'). It also explains list_tools for currently callable tools, request_mcp for unmet needs, and that writes require workspace owner/admin.

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. The description adds valuable context: no credentials needed, pay-per-query, accesses public data, and LGPD compliance responsibilities. 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?

Three sentences, each adding distinct value: purpose, access/payment, and privacy/legal context. No redundancy, though the LGPD sentence is somewhat verbose. Overall efficient.

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?

Covers access, payment, and data classification, but lacks explanation of the 'completo' parameter and the CPF/CNPJ requirement discrepancy. No output schema, so a brief note on response contents would improve completeness. Moderate coverage overall.

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 must compensate. It mentions CPF/CNPJ but implies either/or while schema requires both, creating ambiguity. The 'completo' parameter is not explained, leaving a significant semantic gap.

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: 'Consulta infrações trabalhistas registradas pelo Ministério do Trabalho e Emprego' with specific verb (consulta) and resource. It also specifies inputs (CPF/CNPJ), distinguishing it from generic sibling tools.

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: hosted on platform, no credentials required, paid via prepaid credit, and focuses on public data. It does not explicitly mention alternatives or when-not-to-use, but sibling tools are unrelated, so this is acceptable.

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 readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description adds that the conversation array aids reproduction, which is useful context. However, it says nothing about side effects, submission limits, or what happens after reporting, leaving some behavioral ambiguity.

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 providing value. It is front-loaded with the purpose and immediately gives the key usage instruction. 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 bug-report tool, the description covers the main action and the key reproduction hint. However, it omits explanation for 'context' and does not clarify the output/confirmation behavior. Given the minimal schema annotations, this is a moderate gap.

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 has 0% description coverage, so the description must explain the parameters. It only clarifies 'conversation' (as an array) but not 'message' or 'context'. Moreover, it calls 'conversation' an array while the schema types it as a string, adding confusion rather than resolving 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 uses a specific verb ('Report') and names the resource ('a bug, missing feature, or send feedback'), making the tool's purpose immediately clear. It also distinguishes this from sibling tools, which are unrelated (auth, connect, marketplace, 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 instruction to 'Include the conversation array with recent messages for reproduction' gives direct usage guidance. There are no similar sibling tools, so no explicit alternatives are needed, but the description could mention when to prefer this over other channels.

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?

With annotations already declaring readOnly, idempotent, and non-destructive behavior, the description adds the specific content shown (platform and adapter versions) but doesn't provide additional behavioral context. 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?

A single, concise sentence effectively communicates the tool's function with no unnecessary words or repetition.

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 tool with no output schema, the description is sufficient. It clearly states what the tool does, and nothing crucial is 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 tool has zero parameters, so schema coverage is trivially 100%. Per the baseline for 0-param tools, a score of 4 is appropriate; there are no parameter semantics to supplement.

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 verb 'Show' and the resource 'current MCP platform and adapter versions', providing specific scope. It distinguishes itself from siblings like toolkit_info by focusing specifically on versions.

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 purpose implies the usage context: when you need to know the MCP platform and adapter versions. It is clear and unambiguous, though it doesn't explicitly mention 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.

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

Annotations already declare readOnlyHint=true, and the description reinforces this by describing a read-only state query. It adds behavioral context by listing the specific categories of information returned (installed MCPs, connection status, accounts, catalog tool counts), going beyond the annotation's bare safety flags.

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, well-structured sentence that front-loads the main purpose and uses a colon-separated list for details. Every word is informative; no filler or redundant phrasing.

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 stateless read-only tool with no parameters and no output schema, the description fully explains what the tool returns, making it complete for an agent to decide invocation and interpret results. Annotations cover safety, and the description covers content.

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 takes zero parameters, and the schema has 100% coverage (empty properties). No parameter explanation is needed, and baseline for 0 params is 4. The description adds no parameter semantics, but none are required.

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 resource ('current toolkit state'), then enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from siblings like show_version 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 for checking the current state of the toolkit, but it does not explicitly state when to prefer this tool over siblings or mention any exclusions. Clear context is provided, but no direct when-to-use guidance.

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