NFe Inutilizações

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

The description discloses key behavioral traits beyond annotations, such as the two modes (permanent via config vs session-only token), the fact that the token is a JWT, and the workflow of obtaining a link first then authenticating. However, it doesn't mention error cases or response details, which would add more context.

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 about 60 words but packs in all essential information: purpose, best practice, alternative, and exact call patterns. It is well-structured with clear separation of options, and every sentence adds value 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?

The tool is simple with one optional parameter and no output schema. The description covers the main workflow and user scenarios well, but doesn't explicitly state what the tool returns (e.g., a link or success message). Given the tool's simplicity, this is a minor 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 input schema has only a 'token' property with no description, but the description thoroughly explains its meaning and usage: it's an optional JWT for session-only login, and omitting it returns a login link. This fully compensates for the 0% schema coverage.

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 tool's purpose: authentication for MCP.AI in IDE agents, detailing the browser login and token acquisition flow. It clearly distinguishes from sibling tools by focusing on token handling, while other tools like connect or marketplace have different scopes.

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 when-to-use guidance: it recommends adding the token to the server config for a permanent connection, or pasting it for session-only login. It also gives invocation patterns: call with no args to get a link, or with a token after pasting, leaving no ambiguity about usage.

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=true, destructiveHint=false), the description discloses specific behavioral outcomes: when all providers are connected, it returns authenticated:true and empty pending[]; when credentials are missing, it returns connect_url for the toolkit and per-install URLs. This adds valuable context about expected response states.

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 and well-structured: two sentences, front-loaded with the primary purpose, followed by conditional details. Every sentence adds value 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?

For a simple, parameterless, read-only tool, the description is complete. It covers the two main scenarios (all connected vs. missing credentials) and specifies the relevant output values. No output schema exists, so the description adequately substitutes for return value 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 tool has zero parameters, so the baseline is 4. The description correctly does not attempt to explain parameters, and the schema coverage is trivially 100%. No additional parameter semantics are needed.

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: 'Returns connection status and URLs.' It uses a specific verb ('Returns') and a clear resource ('connection status and URLs'), and the conditional behavior differentiates it from sibling tools like 'authenticate' (which presumably performs authentication rather than checking status).

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: this is a read-only tool to check connection status and retrieve URLs. It implies usage when you need to know whether providers are connected or need connection URLs. However, it does not explicitly name alternatives or state when not to use it, so it falls short of 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?

The description reveals key behaviors beyond the openWorldHint/readOnlyHint annotations: invoke can run uninstalled MCPs one-off, returns auth/payment links instead of failing, and writes require admin role. It also discloses the non-mutating nature of search/describe and the mutating nature of install/uninstall/subscribe/cancel, enriching the agent's understanding of side effects.

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 dense paragraph but is logically structured: it opens with the core purpose, then the main flow, key one-off behavior, edge cases (auth/payment), permission requirements, and finally the prompt library. Every sentence contributes value, though the length and density may slightly reduce scannability. It earns a 4 rather than 5 because it could be broken into clearer sections or bullets.

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 (23 parameters, 14 actions) and no output schema, the description is remarkably complete: it covers the core search-discover-invoke flow, auth and payment link behavior, install vs invoke trade-offs, permissions, billing actions, and the separate prompt library. Missing but minor: specific return shapes for search/list_tools and the exact role of 'immediate' or 'tier_slug'. Still strong 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?

With 0% schema description coverage, the description compensates by explaining the meaning of the action parameter (search, describe, invoke, install, etc.) and the interplay between mcp_id, tool_id, and arguments. It also clarifies prompt-related parameters (prompt_vars, prompt_slug) via the prompt library explanation. However, it does not exhaustively cover parameters like limit, immediate, tier_slug, or conversation, leaving some ambiguity for obscure fields.

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 marketplace as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It explains the core flow (search → describe → invoke) and distinguishes list_tools from the discovery functions, setting it apart from sibling tools like report_bug 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?

Explicit guidance is provided throughout: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use,' and 'list_tools lists what is callable right now.' It also describes when invoke returns connect/checkout links and notes that writes require workspace owner/admin. This directly answers when to use this tool versus 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=true, idempotentHint=true, destructiveHint=false. The description adds valuable context: data is of public access, not private/confidential, and the client is data controller under LGPD. This goes beyond annotations and helps an agent understand the sensitivity and legal framing.

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 and front-loaded with the core function. It includes necessary context about hosting, payment, and legal aspects. While the LGPD clause adds length, it is relevant and does not feel wasteful. 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?

For a simple read-only query tool, the description covers purpose, access mode, payment, data sensitivity, and legal responsibility. It does not describe the return format, and the 'completo' parameter remains ambiguous, but overall the context is sufficient for an agent to understand the tool's capabilities.

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 compensate. It mentions CNPJ and ano ('a partir do CNPJ e do ano'), which clarifies the purpose of those required parameters. However, the optional parameter 'completo' is not explained, and no format/validation guidance is provided. Description partially compensates but misses the optional param.

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 'Consulta as inutilizações de numeração de Nota Fiscal Eletrônica' which is a specific action on a specific resource. It distinguishes from sibling tools which are generic (authenticate, connect, marketplace) and unrelated.

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: 'Hospedado pela plataforma, sem credenciais, pague por consulta com crédito pré-pago' and indicates public access data. This tells when to use it (pay-per-query, no auth) but does not explicitly exclude alternatives or state when not to use.

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 idempotentHint=true and readOnlyHint=false. The description adds behavioral context by specifying that the conversation array is needed for reproduction, implying the tool sends or uses this data. It does not contradict any annotations, and the added context is valuable beyond what annotations provide.

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 with no wasted words. The first sentence states the purpose, and the second provides a key usage hint. It is front-loaded and appropriately compact.

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?

Overall, the description is adequate for a simple bug reporting tool, but it has clear gaps: only one of three parameters is mentioned, there is no guidance on expected output, and parameter semantics are not fully clarified. The annotations cover safety aspects, but the description is not complete enough on its own.

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. It only mentions the 'conversation array' but calls it an 'array' while the schema defines it as a string (likely JSON). It does not explain the required 'message' parameter or the optional 'context' parameter. This is insufficient for an agent to correctly populate all parameters.

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 with a specific verb+resource: 'Report a bug, missing feature, or send feedback.' This distinguishes it from siblings like 'marketplace' or 'show_version', which have unrelated functions.

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 usage context by instructing to 'Include the conversation array with recent messages for reproduction.' While it doesn't explicitly say when not to use the tool, the sibling tools are unrelated, so no exclusions are necessary. The purpose itself implies appropriate use cases.

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, which fully cover the safety profile. The description adds the specific resource that is being queried (platform and adapter versions), which is useful context, but it does not disclose additional behavioral traits such as return format or potential error conditions.

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 is front-loaded and free of unnecessary elaboration. Every word contributes to the understanding of the tool's 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 zero-parameter, read-only version query, the description is adequately complete. It could optionally mention the exact structure of the output, but given the absence of an output schema and the straightforward nature of the task, this is not a critical omission.

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 input schema is empty. The baseline for zero parameters is 4, and the description correctly implies that no inputs are required, which aligns with 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's function with a specific verb ('Show') and a well-defined resource ('current MCP platform and adapter versions'). It effectively differentiates from sibling tools like 'authenticate' or 'marketplace', which serve entirely 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 purpose is self-evident from the description and the sibling tools are clearly unrelated, so the appropriate usage context is clear. However, there is no explicit when-to-use or when-not-to-use guidance, though this is unlikely to cause confusion given the tool's simplicity.

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 the specific content of the state (installed MCPs, connection status, accounts, catalog tool counts), which provides useful context 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 sentence that front-loads the primary action and then lists the return components without any unnecessary 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?

There is no output schema, so the description must convey what the tool returns. It does so by enumerating the four components. Given the simplicity (no params, no side effects), this is 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 doesn't discuss them. The baseline score for 0 params is 4.

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 ('current toolkit state') and enumerates the included information (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from siblings like show_version or connect.

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 does not explicitly state when to use this tool over alternatives, nor does it mention sibling tools or exclusions. Usage is implied by the description of what it returns, but no direct guidance is provided.

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