MPT MG: Certidão Negativa de Feitos

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

Beyond annotations (readOnly=false, idempotent=true, destructive=false), the description adds context about browser login and two modes of token usage. However, it doesn't fully disclose side effects like whether it modifies server configuration or only sets a session, leaving some ambiguity about permanent vs session-only behavior.

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 well-structured sentence that conveys all essential information without redundancy, front-loading the purpose and then detailing usage. Every clause earns its place and there is 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?

Given the tool's simplicity (one optional parameter, no output schema), the description covers the main use cases and behavior adequately. It explains how to obtain a permanent connection and a session login, and what to do with the token. It doesn't specify return values or error handling, but for an auth tool this is acceptable.

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 explains the token parameter: it's a JWT for session login, and omitting it returns a login link. This adds meaning beyond the schema (which only defines token as a string without description), clearly covering both required and optional usage.

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 MCP.AI for IDE agents by logging in via browser and obtaining an access token. It specifies the verb 'authenticate' and resource 'MCP.AI server access', distinguishing it from sibling tools like 'connect' by focusing on token-based 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?

It provides explicit usage guidance: either configure a permanent header or use a session token by passing the token parameter or calling with no args to get a login link. It clearly explains when to use each mode but does not explicitly compare with alternatives or state when not 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?

The description adds significant behavioral context beyond the annotations. While annotations indicate readOnlyHint: true and idempotentHint: true, the description reveals conditional behavior: when all providers are connected it returns authenticated:true and empty pending[], and when credentials are missing it returns connect_url. This explains the state-dependent nature of the output, which is not captured in the annotations. 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 extremely concise: two sentences, front-loaded with the main purpose ('Returns connection status and URLs'). Every sentence provides necessary detail (the conditional outputs) with no fluff or repetition. 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 tool with no parameters, no output schema, and simple read-only behavior, the description is complete. It explains the two possible outcomes (authenticated with empty pending[], or connect_url when credentials are missing) and mentions per-install URLs. The annotations already cover safety and idempotency. This is sufficient context for an agent to correctly invoke and interpret the tool's response.

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 schema provides no parameter documentation. The description does not need to explain parameters since there are none. The baseline for a zero-parameter tool is 4, and the description adds no parameter-specific information because none exists, so a 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?

The description states a clear purpose: 'Returns connection status and URLs.' This is a specific verb (returns) with a defined resource (connection status and URLs), and it distinguishes itself from sibling tools like authenticate (which likely performs authentication) and show_version (which shows version info). The description is not a tautology and clearly indicates what the tool does.

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. It explains two scenarios (all connected vs. missing credentials) and what the output will be in each case. However, it does not explicitly instruct when not to use it or compare it to alternatives like authenticate. The context is clear but lacks explicit exclusions, so it earns a 4 rather than a 5.

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?

Despite annotations already declaring readOnlyHint=false and openWorldHint=true, the description adds rich behavioral context: writes require 'workspace owner/admin', invoke runs tools 'one-off' without installing them, missing credentials return a connect link, and paid tools with an empty wallet return a checkout/top-up link. It also discloses environment distinctions (installed_in_toolkit vs installed_in_workspace) and that mcp.ai/p/<slug> links 'open without login'. 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?

The content is dense and every clause adds value, but it is effectively a wall of text: one massive first sentence uses run-on em-dash/ellipsis breaks to cover the entire marketplace flow, and the prompt library addition is bolted on as a final sentence. It is front-loaded appropriately (core flow first) and wastes no words, yet the lack of any structural formatting for a 14-action tool makes it harder to parse than necessary.

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 enormous surface (23 params, 14 enum actions, no output schema, no annotated parameters), the description admirably covers the core flow, permission model, auth/billing edge cases, and sub-features. Gaps remain: the 'resume' action is never explained, no return-value or error semantics are given for any action, and the boundary with sibling tools connect/authenticate is only implicit. These are acceptable given message-length constraints on a single 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 0% schema description coverage across 23 parameters, the description must compensate, and it explains the critical action/mcp_id/tool_id orchestration ('every tool with its id + params, pricing, auth' so you pick the right tool_id) and the prompt_vars intent ('with {{variables}} filled'). However, a long tail of params — limit, query, message, immediate, tier_slug, cancel_reason, conversation — is never clarified, requiring inference for this sprawling surface.

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 states a specific verb+resource+scope: it is 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them', and lays out the exact core flow: 'action=search discovers MCPs by intent → describe returns one MCP's full profile ... → invoke RUNS that tool'. It names concrete capability requests ('find an MCP that does X', 'consulta um CPF') and differentiates the prompt library sub-feature ('about ready-made prompt TEXT rather than MCPs'). It clearly distinguishes from siblings like show_version and toolkit_info by being the catalog/execution tool.

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 everywhere with clear when-to-use vs. alternatives: 'Use install only to make an MCP PERMANENT in the active toolkit', 'prefer invoke for a single/occasional use', and 'request_mcp asks us to build a NEW MCP when nothing fits'. It handles edge cases (when the MCP is NOT installed, empty wallet, missing credential → connect/checkout links) and even prescribes follow-up behavior ('the user opens it, then you retry').

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 readOnly and idempotent, but the description adds value by mentioning prepaid payment, lack of platform credentials, non-confidential data, and LGPD responsibility. This goes beyond the annotations 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?

The description is a single paragraph with essential operational info (payment, hosting, legal) and purpose. It's a bit dense but not verbose. 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?

No output schema, but description explains it's a consultation of official data, not confidentialasi no details on response format or error handling. Given the tool's simplicity, it's adequate but could be enhanced with more details.

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 no descriptions per parameterts, and the description does not explain the role of cpf/cnpj. Since coverage is 0%, the description should compensate, but it only says it's a consultation. The names are self-explanatory but without guidance on optionality or format, it's weak.

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: 'Certidão Negativa de Feitos, consulta em fonte oficial' – a specific verb (consultar) and resource (negative certificate). It distinguishes itself from generic sibling tools like authenticate or report_bug by focusing on official Brazilian data consultation.

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's for official consultation, but does not explicitly state when to use it vs alternatives, nor any exclusions. It mentions it's for official Brazilian dataional purposes and the client's responsibility, but no direct guidance on conditions or 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 declare readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds no behavioral context beyond input guidance (conversation array). It does not explain what happens after submission, any side effects, or authentication requirements. With annotations present, the bar is lower, but the description still adds little beyond the schema.

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 short sentences, front-loaded with purpose and a key usage hint. No filler 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?

Given the simple nature of the tool (reporting feedback), the description and annotations are adequate. It covers what to include (conversation) but doesn't mention behavior like throttling or response format. Since there's no output schema froesn't need to. Annotations cover side effects. For a simple write operation, 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 schema has 0% description coverage, so the description must compensate. It explains the 'message' parameter implicitly (the bug/feature/feedback content) and explicitly mentions 'conversation' for reproduction. However, the 'context' parameter is left unexplained. With 0% schema coverage and 3 params, this partially compensates but not fully, scoring 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.' This is a specific verb (Report) and resource (bug/feedback), and it distinguishes from siblings like authenticate or marketplace by focusing on bug reporting.

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 an explicit instruction to include the conversation array with recent messages for reproduction, which is a clear usage context. It does not explicitly state when not to use it or name alternatives, but the context is fairly obvious (use when you encounter a bug or want to send feedback).

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, so the safety profile is covered. The description adds the specific behavioral detail that it returns platform and adapter versions, which goes beyond the annotations without contradicting 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 a single, concise sentence that front-loads the core purpose. There is zero redundancy, and every word adds value. It is appropriately sized for the tool's simplicity.

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, read-only version query, the description is complete. It explicitly states what versions are shown (platform and adapter) and implies no side effects. No output schema exists, but the return content is straightforward, so additional detail is unnecessary.

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, and schema coverage is 100% (empty schema). The baseline for no parameters is 4, and the description does not need to add parameter details since none exist. It adequately describes the tool's action without parameter-specific information.

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 'Show the current MCP platform and adapter versions' uses a specific verb ('Show') and resource ('MCP platform and adapter versions'), clearly distinguishing it from sibling tools like authenticate or connect. It precisely states what the tool does without ambiguity.

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 indicates the tool's purpose (querying version info), making its usage context obvious. It does not explicitly mention alternatives, but no alternative exists among the siblings for this specific task, so the implicit guidance is sufficient.

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 safe, non-destructive nature is established. The description adds valuable context by specifying what the returned state includes (installed MCPs, connection status, accounts, catalog tool counts), going beyond the annotation hints.

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, well-structured sentence that leads with the primary action 'Returns' and compresses all relevant information into a short, readable format without any filler 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?

The tool is simple (zero parameters) and the description thoroughly covers what the tool does and what it returns. It enumerates the key output components—installed MCPs, connection status, connected accounts, and catalog tool counts—making the description complete even without an output schema.

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 and the schema is empty, so there are no parameter semantics to clarify. The baseline for zero-parameter tools is 4, and the description does not need to add parameter information 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 the specific verb 'Returns' and clearly identifies the resource as 'the current toolkit state', then enumerates the exact contents (installed MCPs, connection status, connected accounts, catalog tool counts). This clearly distinguishes it from sibling tools like authenticate and connect, which are action-oriented.

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 this tool is used when you need an overview of the toolkit's state, but it does not explicitly state when to use it versus alternatives, nor does it mention any exclusions or when-not-to-use scenarios. It provides clear context but no explicit usage guidance.

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