MPT MT: Certidão Negativa de Feitos

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

Annotations only say idempotent, read-only=false, not destructive. The description adds meaningful behavioral context: the tool can return a login link, accept a JWT for session auth, and suggests a config-based permanent auth path. It doesn't explicitly state whether calling with a token changes server state, but the idempotent annotation covers repeated calls.

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 run-on sentence with several clauses and embedded instructions, making it somewhat dense and hard to parse quickly. While it is information-rich and front-loads the key action, the structure could be cleaner with separate sentences for permanent vs session auth.

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 one optional parameter and no output schema, the description covers the main usage scenarios: getting the login link, pasting a token, and configuring a permanent header. It doesn't describe response shapes, but for an auth tool with this simplicity, the coverage is adequate.

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 burden. It explains that the optional `token` parameter is a JWT to be pasted for session-only login, and that omitting it returns the login link. This clearly adds meaning beyond the bare string 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 purpose: authenticating an IDE agent via browser login and access token. It distinguishes two modes (config header for permanent connection, inline token for session-only) and provides an alternative call style with no args to get the login link. It is not a textbook verb+resource phrasing but is specific and understandable.

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 explicitly walks through when to use each invocation pattern: add the token to config for a permanent, non-expiring connection, or paste it for session-only login. It tells the agent exactly how to call the tool with or without the token, which is strong usage 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, destructiveHint=false, which are consistent with a status check. The description adds context about different states (authenticated:true vs pending[] and connect_url), which is useful. However, it doesn't disclose any rate limits, permission requirements, or return format details beyond what's given. Since annotations cover safety profile, 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, front-loaded with the primary purpose, and then elaborates on two possible states. Every word adds value; no fluff or repetition. Excellent conciseness.

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, no output schema, simple status output), the description is mostly complete. It covers the main output fields (authenticated, pending, connect_url) and their meaning. However, could mention that the per-install URLs are returned in case of missing credentials, which is already implied. Slight gap: doesn't explicitly state what 'all providers' includes or whether partial connection states exist beyond the two examples. But for a status tool, this is adequate.

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 there is no parameter burden on the description. The description focuses on return behavior which is the only meaningful semantic content. With no parameters, the description effectively communicates what the tool outputs, which is more relevant than parameter details. Baseline 4 for zero-param tools.

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 details about authenticated state and pending array. It distinguishes from siblings by focusing on status retrieval rather than authentication actions (authenticate) or other informational tools (show_version, toolkit_info). Slight deduction for not explicitly contrasting with siblings, but purpose is explicit and actionable.

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 connection status, and by listing typical scenarios (all connected vs missing credentials) it guides when to use this tool. However, it doesn't explicitly exclude alternatives or mention cases where other tools might be preferred, such as when needing to initiate auth (authenticate) or view version info. It provides clear context 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 description goes well beyond the annotations by disclosing that writes require workspace owner/admin, that invoke runs tools one-off without installing them, that credential/payment gaps return connect/checkout links, and that search/describe flag installation status. No contradiction with the annotations was found.

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 dense and front-loaded with the core flow. It covers multiple action groups, permissions, billing, and the prompt library without obvious filler. It could be improved with paragraph breaks or bullet-like structure, but every sentence adds meaningful operational context.

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 parameters, and no output schema, the description covers the core flow, auth requirements, billing behavior, and prompt-library features well. However, it omits parameter-level detail for many actions, does not explain the 'resume' action, and does not describe return shapes for search or list_tools, leaving gaps for correct 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?

Schema description coverage is 0% and there are 23 parameters, so the description carries the full burden. It explains the action enum and the high-level roles of mcp_id and tool_id, but it does not explain many other parameters such as arguments, immediate, tier_slug, prompt_body, prompt_vars, cancel_reason, or report_context. This is insufficient for reliable parameter selection across all actions.

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, high-level purpose: 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It clearly explains the core search → describe → invoke flow and distinguishes the tool's role from siblings like toolkit_info and report_bug by enumerating its own action surface.

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 usage guidance: 'prefer invoke for a single/occasional use,' 'use install only to make an MCP PERMANENT,' 'list_tools lists what is callable right now,' and 'request_mcp asks us to build a NEW MCP when nothing fits.' It also explains when invoke returns connect or checkout links and when retry is appropriate.

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 mark the tool as read-only, idempotent, and non-destructive. The description adds useful behavioral context: no platform credentials, per-query prepaid billing, non-confidential official data, and LGPD controller responsibility. This goes beyond the annotations and does not contradict them.

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 front-loaded with purpose, followed by operational, billing, and legal context. Each sentence contributes meaningful information, though the LGPD sentence is somewhat dense but still relevant.

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, billing, authentication model, and data sensitivity, while annotations cover safety. However, with no output schema and no parameter guidance, the agent is left uncertain about expected return values and how to supply CPF/CNPJ, leaving a notable completeness 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 provides only 'cpf' and 'cnpj' with no descriptions and 0% description coverage, and the description does not explain how these parameters relate to each other or how to choose one. The param names are recognizable, but the description adds no semantic value beyond the raw 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 operation: 'Consultar' a 'Certidão Negativa de Feitos' from official Brazilian sources. It names the specific resource and action, and the sibling tools are generic platform utilities, so this tool is easily distinguished.

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 usage context: it is a paid, prepaid-credit consultation against official public sources, requiring no platform credentials. It does not explicitly name alternatives or when-not-to-use, but the context is sufficient among the listed siblings.

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 declare the tool as not read-only (has side effects), not destructive, idempotent, and not open-world. The description aligns with this by framing an action of 'sending feedback' that affects external state. It adds nuance that conversation data is used for reproduction. However, it doesn't disclose side effect details like whether data persists, rate limits, or retry implications — though idempotency is already annotated. The description adds some context but doesn't go deep 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 effectively convey the tool's purpose and key usage guidance. The most critical information is front-loaded, and there's no redundancy or filler. Every word serves a 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?

For a simple 3-parameter reporting tool with no output schema and no nested objects, the description covers the primary workflow of submitting feedback and including reproduction context. However, it falls short on explaining the 'context' parameter and the distinction between 'message' and 'conversation.' Given the low complexity, this is adequate but has clear 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?

With 0% schema description coverage, the description must compensate, but it only explains one parameter: 'conversation' (recent messages for reproduction). It fails to clarify the meaning of 'context' (what kind of context is expected) or deepen understanding of 'message' beyond being self-evident. The description partially assists with the conversation parameter but leaves significant ambiguity for the others, which is a notable gap given the lack of schema documentation.

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' with a clear resource: 'a bug, missing feature, or send feedback.' This unambiguously states what the tool does. None of the sibling tools (authenticate, connect, marketplace, mpt_mt_cnf_consultar, show_version, toolkit_info) overlap with bug reporting, so the purpose inherently distinguishes this tool from its siblings.

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 context by instructing to 'Include the conversation array with recent messages for reproduction,' which effectively guides on what to supply. However, there's no explicit when-to-use vs. when-not-to-use guidance, and no sibling is mentioned as an alternative. The guidance is implied rather than explicit, fitting 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, so the safety profile is well covered. The description adds no additional behavioral context beyond what annotations provide, but the tool is simple with no side effects. It could mention it requires no authentication or returns textual information.

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, front-loaded with the action ('Show') and resource ('MCP platform and adapter versions'). Zero waste, perfectly concise for its 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?

Given the tool's simplicity, no parameters, and rich annotations, the description is adequate. It could mention what type of output to expect (e.g., version strings) but the tool name and description already convey the purpose clearly. Sibling tools include toolkit_info and report_bug, which are separate, so this is complete enough.

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 doesn't need to explain any. Schema coverage is 100% (vacuously). The description adds no parameter semantics, but the absence of parameters makes this a non-issue, hence a baseline 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, with a specific verb ('show') and resource ('versions'). It distinguishes from siblings like authenticate and marketplace, though it could be more explicit about what 'MCP platform and adapter versions' means.

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?

No explicit guidance on when to use this tool versus alternatives. However, for a version-checking tool, usage context is fairly obvious. It is implied for diagnostic or informational purposes, but lacks explicit context or 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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds behavioral context by detailing the returned state fields (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond what annotations state. 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?

The description is a single, concise sentence that front-loads the key verb and resource, then efficiently enumerates the details. Every word 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 no-parameter introspection tool with good annotations and no output schema, the description provides a complete picture of what the tool returns. It covers the main aspects of toolkit state, making it sufficient for an AI agent to know what to expect.

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 there is nothing to explain. Baseline for 0 params is 4. The description does not need to compensate for parameter documentation since none exist.

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 identifies a clear resource: 'current toolkit state'. It enumerates exactly what is included (installed MCPs, connection status, accounts, catalog tool counts), which distinguishes it from sibling tools like show_version or 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?

The description implies usage: when you need to inspect the toolkit state, this is the tool. However, it does not explicitly state when to use it over alternatives or provide exclusions. It's a straightforward info retrieval tool, so implied usage 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.