MPT AL: Certidão Negativa de Feitos

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

Annotations declare idempotentHint=true and destructiveHint=false, which the description does not contradict. The description adds context about the browser flow, token expiration (permanent vs session-only), and the fact that calling with no args returns a link. It doesn't detail the output format, but it explains the flow sufficiently 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 a single paragraph that is dense but front-loaded with the main purpose and use cases. It covers multiple scenarios without verbosity, but the sentence structure is slightly run-on and mixes advice with usage instructions, so it could be better organized.

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 param, no output schema, annotations cover safety), the description adequately explains the authentication flow, both permanent and session-based, and points to the login link. It doesn't mention the exact return of the link, but that is likely minor. The sibling tools don't require differentiation beyond the core purpose.

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 one optional token string parameter with 0% description coverage. The description explains that token is a JWT pasted by the user, and that omitting it yields a login link. This adds substantial meaning beyond the bare schema definition, though it could be more explicit about the token's format.

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 explicitly states the purpose: to log in via browser, copy access token, and optionally set it for permanent or session-only authentication. It clearly distinguishes this from sibling tools like connect or marketplace by focusing on authentication for IDE agents.

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?

Provides clear when-to-use guidance: recommends adding the token to server config for permanent connection, or calling with token for session-only, or with no args to get the link. It differentiates between two modes of usage and gives concrete steps, which helps the agent decide how to invoke 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 indicate readOnly, idempotent, and non-destructive behavior. The description adds concrete details about the response format (authenticated:true, empty pending[], connect_url) and the conditional behavior, enriching the transparency 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 concise (two sentences), directly states the function, and logically presents the two possible outcomes. It avoids redundancy and is 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?

Although there is no output schema, the description provides enough detail about the return value structure (authenticated field, pending array, connect_url for toolkit and per-install) to understand the tool's behavior. It does not cover error cases or edge scenarios, but for a simple status check, it is adequately 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?

The tool has no parameters, so the description correctly reflects that no input is required. The schema coverage is complete (zero parameters), and there is no ambiguity to clarify.

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, distinguishing it from sibling tools like authenticate (which performs authentication) by focusing on status retrieval. It also specifies the two possible outcomes (authenticated:true with empty pending, or connect_urls when credentials missing), making the purpose 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 implies usage when checking connection status and provides outcome examples, but it does not explicitly state when not to use this tool versus alternatives like authenticate. However, given the clear distinction in purpose, the usage context is reasonably implied.

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, the description discloses that invoke runs tools one-off without installing, that writes require workspace owner/admin, that invoke may return connect/checkout links, and that search/describe flag installed status. It also explains the prompt library's shareable link behavior. 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 description is dense and every sentence adds useful information, but it is one long paragraph covering many distinct concerns (core flow, permissions, prompt library). It is front-loaded with the main purpose, though bullet structure would improve scannability.

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 23-parameter, multi-action tool with no output schema, the description covers the main flows, permissions, key edge cases, and the separate prompt library. It does not describe return shapes for search/describe/list_tools, but it provides enough context for an agent to select and invoke the tool correctly in most cases.

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 and 23 parameters, the description must compensate, and it does explain the action enum values and the role of tool_id/mcp_id in the flow. However, many parameters (e.g., prompt_vars, tier_slug, immediate, cancel_reason, conversation) are not described individually, leaving their semantics to inference.

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 definition ('the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them') and immediately gives the core search → describe → invoke flow. It clearly distinguishes the tool's scope from siblings by covering both catalog discovery and execution, plus the prompt library.

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 gives explicit guidance: prefer invoke for single/occasional use, use install only to make an MCP permanent, use request_mcp when nothing fits, and use subscribe/cancel for per-MCP billing. It also explains when invoke returns a connect or checkout link and says to retry after the user completes the action.

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 destructiveHint=false, and the description adds meaningful operational context: the tool is hosted by the platform, requires prepaid payment, uses publicly available non-confidential data, and assigns LGPD controller responsibility to the client. 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 description is three sentences long and front-loaded with the core purpose. Each sentence adds relevant context (official source, payment/credentials, data governance), though there is slight redundancy between 'fonte oficial' and 'fontes e órgãos oficiais'.

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 that this is a simple read-only query with no output schema, the description covers operational and legal aspects well. However, it omits crucial invocation details: which parameter(s) to provide and whether they are mutually exclusive or optional. This is a significant gap for correct tool 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 the description does not mention the parameters 'cpf' or 'cnpj' at all. It does not clarify whether at least one is required, how they combine, or what format is expected. The property names themselves give some hint, but the description does not compensate for the schema 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 a specific verb ('consulta') and a specific resource ('Certidão Negativa de Feitos' from MPT AL), which distinguishes it from the infrastructure-oriented sibling tools. It is precise and unambiguous about 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 provides useful context for when to use the tool: it queries official Brazilian sources, requires prepaid credit, and does not need platform credentials. It does not explicitly list exclusions or compare to alternative query tools, but the siblings are all infrastructure/utility tools, so no alternative query tool exists to disambiguate.

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 idempotentHint=true, readOnlyHint=false, destructiveHint=false, openWorldHint=false. The description adds the guidance about including the conversation array for reproduction, which is useful context. However, it does not disclose what happens after reporting (e.g., whether it's asynchronous, whether it returns a ticket ID), nor does it mention auth or rate limits. With annotations present, the bar is lower, but the description adds only moderate context beyond 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 concise: two sentences, front-loaded with the primary purpose, and includes the key usage hint. Every word earns its place. 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?

Given the tool's complexity (simple feedback/report tool), the description covers the main purpose and mentions the conversation array. The schema has a required 'message' and optional 'context' and 'conversation' with defaults, but the description doesn't clarify the 'context' parameter. However, given the simplicity, the description is mostly complete. Slight gap on context param.

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 for parameter meaning. The description mentions 'conversation array' and 'reproduction', which maps to the 'conversation' parameter. It also implies 'message' is the main content. However, it does not explain the 'context' parameter at all. With 3 params and 0% coverage, the description 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 states the tool's purpose: 'Report a bug, missing feature, or send feedback.' It uses specific verb 'report' and specifies the resource (bug, feature, feedback). It also mentions the conversation array for reproduction, which distinguishes it from generic feedback 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 implies when to use this tool (when reporting issues or sending feedback) and provides a clue about usage ('Include the conversation array with recent messages for reproduction'). However, it does not explicitly state when not to use it or mention alternatives among 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 already declare readOnlyHint=true and destructiveHint=false, so the description doesn't need to restate safety. It adds value by specifying exactly what information is shown (platform and adapter versions), which is extra context 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?

The description is a single, focused sentence with no filler or redundancy. It is front-loaded with the verb and clearly states the resource, making it maximally 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?

For a simple version-checking tool with no output schema or parameters, the description adequately conveys what the tool returns (platform and adapter versions). It might be slightly enhanced by noting the format (e.g., 'as text'), but given the simplicity and annotation support, it is sufficiently 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?

The tool has zero parameters, and the schema has full coverage (100%). Per the rubric, a zero-parameter tool gets a baseline of 4. The description doesn't need to explain parameters since there are none.

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 ('Show') and a clear resource ('current MCP platform and adapter versions'), making the tool's function unambiguous. It naturally distinguishes from siblings 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 context is clear: use this tool when you need to check the installed versions. There are no explicit alternatives or exclusions, but the tool's purpose is self-evident and no competing sibling exists, so some guidance is implied rather than stated.

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 declare readOnly, idempotent, and non-destructive, so the description need not repeat those. It accurately describes the behavior (returns state) without introducing contradictions, and the description adds clarity about what state elements are returned.

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 but well-structured with a clear subject and an enumerated list. It is concise while conveying all necessary information without 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?

Given that there is no output schema, the description adequately explains what the return value contains (installed MCPs, connection status, accounts, catalog counts). This provides enough context for a caller to understand the tool's result without additional documentation.

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 zero parameters (100% coverage), so no parameter descriptions are needed. Per the rubric, a high schema coverage baseline of 3 applies, and the description does not address parameters, which is fine 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 clearly states that it returns the current toolkit state and enumerates the exact components included (installed MCPs, connection status, accounts, and catalog counts). This is specific and distinguishes it from sibling tools like authenticate or connect, which have 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 when to use it (when you need to inspect the toolkit state), but does not explicitly state conditions or contrast it with alternatives. Given the sibling tools, it's clear this is for read-only information, but explicit guidance is lacking.

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