MTE: Certidão de Débitos Trabalhistas

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

The description discloses the browser-based flow, token handling, and session vs permanent options. It doesn't contradict annotations (readOnlyHint=false, idempotentHint=true). It adds context about the expected IDE agents (Cursor) and the link generation, though it doesn't explicitly state side effects like storing tokens in memory or on disk. With annotations present, the description adds reasonable value.

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, densely packed with necessary information. The first sets audience context, the second explains all invocation modes. No redundancy, front-loaded with 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?

The description covers the full authentication flow: browser login, token retrieval, permanent vs session options, and input/output behavior (link when no args). It doesn't specify error handling or exact return values, but for a simple auth tool with no output schema, this is sufficient. Could benefit from mentioning what happens after token submission, but overall complete.

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 must explain the 'token' parameter. It does this clearly: 'call with { token: "<jwt>" }' after user pastes, and also explains the no-arg case to get the link. This fully compensates for the sparse schema and adds meaning to the 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 states the tool's purpose: authenticate to MCP.AI for IDE agents. It specifies the action (log in, get token) and distinguishes it from sibling tools by being the only authentication-related tool. It provides a specific resource (MCP.AI) and the verb 'authenticate'.

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 usage instructions are given: best practice for permanent connection (add token to config) vs session-only login (paste token or call with no args to get link). It explains when to use each method and even provides alternative configuration approach. No ambiguity in when to call this 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 readOnlyHint=true and idempotentHint=true, so the tool is known to be a safe read. The description adds real value by disclosing the conditional response behavior (authenticated:true with empty pending[] vs. connect_url and per-install URLs when credentials are missing), which goes 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?

Two concise sentences, front-loaded with the primary purpose and immediately followed by behavioral details. Every phrase earns its place with no 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 zero-parameter, read-only status tool with safe annotations, this description fully covers the necessary behavior, including conditional responses. No output schema or additional context is needed for an agent to use 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?

There are zero parameters, making the schema trivially complete at 100% coverage. The description thus has no param semantics to add, and the baseline of 4 for a zero-parameter tool 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?

The description uses a specific verb+resource ('Returns connection status and URLs') and adds precise scope by detailing the two possible states (all providers connected vs. missing credentials). This clearly differentiates it from sibling tools like `authenticate`, `marketplace`, and `toolkit_info`.

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 implies this is for checking connection status, not performing authentication, which is covered by `authenticate`. However, it does not explicitly mention when NOT to use it or name alternative tools directly.

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 only provide generic hints (readOnlyHint=false, openWorldHint=true, etc.), so the description carries the burden. It discloses that invoke runs tools without installing them, that writes require workspace owner/admin, that missing credentials return a connect link, and that empty wallet returns a checkout link. This is rich behavioral context well 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 long but logically structured: core flow, invoke behavior, install vs invoke, permissions, then prompt library. Nearly every sentence adds needed information for a 14-action tool, though a few examples and the Portuguese word 'pontualmente' add minor noise.

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, auth/billing edge cases, permission requirements, and the prompt library. With no output schema, it does not fully describe return formats for search, list_tools, or describe, but it provides enough context for an agent to select and invoke the tool correctly 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 description coverage, the description must compensate heavily. It explains the action enum, mcp_id, tool_id, arguments, and prompt_* fields indirectly through the flow, but many parameters (limit, query, immediate, tier_slug, conversation, cancel_reason, cancel_comment, report_context, prompt_category, request_details, prompt_description) are never individually explained. It partially compensates but leaves 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 identifies the tool as the mcp.ai marketplace catalog and execution layer, with an explicit core flow (search → describe → invoke) and a secondary prompt library. It distinguishes itself from siblings by naming its many actions and their 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 gives explicit when-to-use guidance: prefer invoke for one-off use, use install only for permanent toolkit additions, use list_tools for currently callable tools, and use request_mcp when nothing fits. It also explains when connect/checkout links require user action before retrying.

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 useful context beyond this: it is a paid consultation, does not use platform credentials, returns non-confidential citizen-available data, and places LGPD responsibility on the client. This meaningfully supplements the annotation-based 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 front-loads the core purpose in the first clause and keeps the overall length moderate. It includes necessary legal/commercial context, though 'fonte oficial' and 'fontes e órgãos oficiais brasileiros' are somewhat redundant.

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 purpose, access model, data sensitivity, and legal responsibility, but it omits parameter usage guidance and any indication of the response format. With six parameters and no output schema, this leaves noticeable gaps for an agent to invoke the tool 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 carries the burden for explaining parameters, but it does not mention or clarify login_cpf, login_senha, cpf, cnpj, pkcs12_cert, or pkcs12_pass. Some parameter names are partially self-explanatory, but the distinction between login credentials and query target fields is left entirely to the agent.

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 consulting the official MTE Labor Debt Certificate source ('MTE: Certidão de Débitos Trabalhistas, consulta em fonte oficial'). This is a specific verb+resource pairing that distinguishes it from generic siblings 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 implies when to use the tool (to query an official Brazilian labor debt certificate) and adds practical constraints like prepaid credit and no platform credentials. However, it does not explicitly state when not to use it or name alternatives, leaving usage guidance mostly 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 declare idempotentHint: true, destructiveHint: false, readOnlyHint: false. The description adds the note to include conversation array for reproduction, which is mildly useful behavioral context, but doesn't describe any other traits like async behavior or response format. It doesn't contradict annotations, and provides some value, so 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?

Two sentences, first gives purpose, second gives key instruction. No fluff, perfectly concise and well-structured.

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 tool is simple (3 params, one required, no output schema). The description covers the main action and the one non-obvious parameter (conversation). It doesn't explain return values, but with no output schema and simple nature, this is acceptable. Given annotations and schema, the description is fairly complete.

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 has 0% description coverage, so the description must clarify parameters. It explains the 'conversation' parameter ('include the conversation array with recent messages for reproduction'), but does not explain 'message' or 'context'. Since it adds meaning for at least one parameter, but not all, it's a 3.

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: 'Report a bug, missing feature, or send feedback.' It specifies a verb (report) and resource (bug/feature/feedback), and is distinct from all sibling tools (authenticate, connect, marketplace, etc.), so it's 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 tells what the tool is for but gives no explicit guidance on when to use it vs alternatives or any exclusions. It doesn't mention any prerequisites or context like 'only for internal issues' or 'after trying other tools.' It's clear enough but lacks explicit when/when-not guidance.

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, covering safety. The description adds what versions are shown (platform and adapter) but not return format or additional side effects. Given strong annotations, the description provides sufficient supplemental context without contradiction.

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 that fully conveys the tool's purpose. No extraneous information or redundancy. Front-loaded with the action and target.

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, clear annotations, no output schema), the description is adequate. It identifies what is shown but does not specify output format (e.g., text vs. JSON). Slight room for improvement in detailing return structure, but overall complete for a version check 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, so schema coverage is trivially complete. Baseline is 4. The description does not add parameter-specific details because there are none, and none are needed. The description's mention of 'platform and adapter' aligns with the empty 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's function: 'Show the current MCP platform and adapter versions.' This uses a specific verb ('Show') and identifies the exact resource (versions). It is distinct from sibling tools like 'authenticate' or 'connect', 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 usage (e.g., checking versions for diagnostic purposes) but does not explicitly state when to use this tool versus alternatives. No exclusions or comparisons to siblings like 'toolkit_info' are provided, leaving the agent to infer context.

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, so the safety profile is covered structurally. The description adds context about what the returned state contains but does not go beyond the annotations to reveal additional behaviors (e.g., data sensitivity/permissions). Consistent with the annotations — no contradiction.

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, front-loaded sentence ('Returns the current toolkit state:') followed by a colon-delimited enumeration of the exact data returned. Every word earns its place, with no fluff 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-parameter, read-only tool with strong annotations and a rich description enumerating the output fields, the description is complete. No output schema exists, but the description adequately conveys what the agent should expect, compensating for the missing structured return type.

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, the description trivially covers 100% of the schema (an empty object). Per the rubric, 0-param tools get a baseline of 4 since there's no parameter semantics to enhance; the description need not compensate for any 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?

Uses a specific verb ('Returns') with a clear resource ('the current toolkit state') and enumerates precise data points (installed MCPs, connection status, accounts, catalog tool counts). The description is specific enough to distinguish it from siblings like 'authenticate' or 'connect', though it doesn't explicitly name them.

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 — the tool surfaces the current toolkit state, implying when an agent would call it (to inspect environment status). However, it does not explicitly name alternatives like 'show_version' or state when NOT to use it, so it misses the top score by lacking explicit exclusions.

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