Detalhamento Negativo

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

The description discloses behavioral traits beyond annotations: calling with no args returns a login link, while providing a token authenticates. It notes the difference between permanent and session-only connections. It does not contradict the idempotentHint or destructiveHint, and adds context about token handling.

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 composed of three sentences, each adding value: purpose, best practice, and alternative. It is front-loaded with the tool's purpose, though the opening phrase 'MCP.AI for IDE agents' is slightly verbose but still relevant 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 simple tool with one optional parameter and no output schema, the description covers both invocation patterns (with/without token) and the token format. It explains the authentication flow sufficiently, though it doesn't detail error cases or response structure, which are not required given the minimal complexity.

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 only defines 'token' as a string with no description (0% coverage). The description explains the token is a JWT access token and explicitly states it is optional ('with no args to get the link'), fully compensating for 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 states the tool authenticates for MCP.AI, providing specific usage: logging in via browser and copying an access token. It clearly distinguishes between permanent config-based auth and session-only token auth, which differentiates it from potential siblings like '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?

It explicitly recommends the best practice (adding a header to the server config for a permanent connection) and the alternative (pasting a JWT for a session-only login). It also clarifies when to call with no args to get the link, giving clear context for each invocation mode.

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 read-only and idempotent hints, and the description adds valuable context about response variations: authenticated:true with empty pending[] when all connected, and connect_url when credentials are missing. This explains state-dependent behavior beyond the structured 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 main purpose and followed by conditional details. Every sentence earns its place with no redundant information.

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 no output schema, the description explains return values (status and URLs) and covers the two main scenarios (all connected vs. missing credentials). It doesn't detail what 'pending' means or provide sample outputs, but for a simple read-only status tool, this is largely sufficient.

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?

No parameters exist, so the description doesn't need to explain any. The empty schema covers all parameters, and the description correctly focuses on the tool's functionality rather than parameter details.

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 response states. It distinguishes itself from siblings like authenticate by focusing on status retrieval rather than initiating authentication, though it doesn't explicitly name alternatives.

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 retrieving URLs when needed, but doesn't explicitly state when to use this tool vs. authenticate or other siblings. The behavior descriptions for different states provide some context, but no direct 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 indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context beyond these: the tool is hosted on the platform, no credentials are needed, it queries bureaus and official databases, and it involves prepaid credit costs. It also notes LGPD compliance responsibilities for the customer. This enriches behavioral understanding without contradicting 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 compact block of three sentences, each conveying useful information: the resource queried, operational details (hosting, payment, credentials), and legal compliance. It is front-loaded with the primary purpose and avoids unnecessary fluff. A slightly more structured format (e.g., bullet points) could improve scannability, but it remains concise and 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?

Given the moderate complexity of a credit consultation tool, the description provides useful context about data sources, cost, and legal basis, but it lacks information about the return format or how the 'completo' parameter alters the response. With no output schema, the absence of return-value details leaves some ambiguity. Overall, it is adequate but not fully complete for an agent to invoke the tool with complete expectations.

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 explain the parameters explicitly. It hints that CPF and CNPJ correspond to physical and legal persons, respectively, but it does not clarify why both are required in the schema nor what the 'completo' boolean controls. This is a significant gap for a low-coverage schema, as the description fails to compensate for the undocumented 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 function: it consults negative credit information (outstanding debts) for individuals or legal entities, listing specific categories like protests, lawsuits, and recoveries. The verb 'Consulta' and resource 'informação de crédito' are specific, and the scope is well-defined. Since sibling tools are unrelated platform utilities (authenticate, marketplace, etc.), there is no 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 provides clear usage context: it is hosted on the platform, requires no credentials, and incurs a prepaid credit charge per consultation. It also specifies a legal basis requirement (e.g., risk analysis requested by the holder), which indicates when use is appropriate. However, it does not explicitly name alternatives or state conditions when this tool should not be used, though none of the sibling tools are comparable.

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 annotations, it discloses one-off invocation behavior, auth/checkout link fallbacks, permission requirements, and the fact that invoke works even when the MCP is not installed. 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 packed into one long paragraph, which hampers scannability. It begins with a clear value statement but mixes in foreign-language examples and lacks bullet points or section breaks.

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, 14-action tool, it covers most workflows and return types (profiles, connect/checkout links, shareable prompt links). It omits explicit result shapes for search/list_tools and the resume action, so not fully 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?

With 0% schema description coverage, the prose explains action values and key parameters (query, mcp_id, tool_id, arguments, prompt_vars, prompt_slug). However, several params like limit, immediate, tier_slug, resume, and prompt_targets are not explicitly tied to actions, leaving 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 official mcp.ai marketplace—a catalog and execution layer for MCPs, with explicit verbs like 'discovers', 'describe', 'invoke', and 'list_tools'. It distinguishes from siblings by outlining a core flow and covering a 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?

Provides explicit guidance: 'use install only to make an MCP PERMANENT', 'prefer invoke for a single/occasional use', and describes the search→describe→invoke sequence. It also states that writes require workspace owner/admin, giving clear prerequisites.

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, readOnlyHint=false, destructiveHint=false. The description adds the requirement to include the conversation array for reproduction but does not disclose side effects or what happens after reporting. This is minimal but not contradictory.

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 with no filler, delivering the purpose and the key usage instruction efficiently.

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 has an input schema with required and optional parameters, the description does not explain return values, the expected format of the conversation parameter (e.g., JSON-encoded string vs array), or the purpose of context. It is adequate for a very simple tool but leaves important 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?

The schema has 0% description coverage. The description explains the conversation parameter as an array with recent messages, but does not clarify the 'context' or 'message' parameters. Since 'message' is required and fairly self-explanatory, the main gap is the unexplained 'context' 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 specifies the action ('Report a bug, missing feature, or send feedback') and the resource (bug/feedback), which is distinct from the sibling tools. It immediately communicates 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?

It provides clear context on when to use the tool (when reporting issues) and instructs to include the conversation array for reproduction, which is a usage guideline. However, it does not explicitly mention when not to use or compare with alternatives, but the sibling tools are unrelated.

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 the specific output (platform and adapter versions) but no additional behavioral context such as authentication requirements or return format. With annotations present, this is acceptable.

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?

Single sentence with no wasted words. Fully front-loaded and immediately comprehensible.

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?

With zero parameters and no output schema, the description is complete enough for an agent to know what the tool does and what to expect (version information). No missing context is critical.

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?

Tool has zero parameters, so the schema carries no burden and description need not compensate. The description adds context about what the tool shows (versions) which is sufficient. Baseline for zero 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?

Clear, specific verb ('Show') with explicit resource ('current MCP platform and adapter versions'). Distinguishes from siblings like toolkit_info (which likely provides broader information) and authenticate/connect (unrelated). No 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?

No explicit when-to-use or alternative guidance is provided. The purpose implies its usage (for checking versions), but there's no mention of when to prefer this over siblings like toolkit_info. This is implied usage, not explicit 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 readOnly, idempotent, and non-destructive behavior. The description adds context about what exactly is returned (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the annotation tags. No contradictions 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 a single, well-structured sentence that front-loads the action ('Returns') and concisely lists the key pieces of information. Every word earns its place 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 simple read-only info tool with no parameters and no output schema, the description fully covers the key return items. It gives enough detail for an agent to know what to expect without needing a formal 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, so the baseline is 4. The description does not need to explain parameter semantics, but it effectively describes the output content, which is the main information a user needs.

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 the tool returns the current toolkit state and enumerates specific details (installed MCPs, connection status, accounts, catalog tool counts). This is a specific verb+resource and distinguishes it from siblings like authenticate 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 implies a use case: check the current state of the toolkit. However, it does not explicitly state when to prefer this over siblings or mention alternatives/exclusions. Thus usage guidance is only implicit, not explicit.

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