Score de Crédito

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

Annotations indicate idempotent and non-destructive behavior. The description adds context about the token flow, permanent vs session-only logins, and mentions returning a link when called with no args. It does not explicitly detail error handling or security implications, but the added context is valuable.

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 bit dense but each sentence adds essential information. It is structured with 'Best' and 'Or' to separate options, making it readable despite its length. No wasted 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?

For a simple optional-parameter auth tool with no output schema, the description covers usage, token semantics, and both authentication modes. It lacks details on failure scenarios or the exact link format, but is reasonably complete for its 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?

Schema coverage is 0%, so the description carries the burden. It explains the 'token' parameter is a JWT for session-only login and that omitting it yields a login 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 clearly states the tool's purpose: authenticate an MCP.AI server for IDE agents by logging in via browser and obtaining an access token. It distinguishes between permanent configuration and session-only login, providing specific guidance.

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 explains when to use each mode: add token to config for a permanent connection, or paste token for session-only login. It also says to call with no args to get the link, giving clear usage context.

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 read-only, idempotent, non-destructive behavior. The description adds value by detailing the specific return shapes (authenticated:true with empty pending[], or connect_url and per-install URLs), which is useful behavioral 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 concise (two sentences) and well-structured: first a general statement, then conditional details. Every sentence provides essential information without waste, making it easy to parse quickly.

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 (0 params, read-only, clear output variations) and strong annotations, the description fully covers the necessary context. It explains both success and failure states, and no output schema exists to require additional return 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 there is nothing to explain. The baseline for 0 params is 4, and the description adds no parameter-specific information because none are needed. It correctly focuses on the no-input nature implicitly.

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, and explains the two different states (all connected vs. missing credentials). This is specific and distinguishes it from siblings like 'authenticate' (which likely initiates auth) and 'toolkit_info' (general 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?

The description implies usage for checking connection status by describing output variations, but it does not explicitly state when to use this tool versus alternatives (e.g., 'use authenticate to initiate missing connections'). It provides context but no direct usage guidance 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?

Beyond annotations (readOnly, idempotent, non-destructive), the description discloses the hosting model, absence of credentials, prepaid billing, data sources (bureaus/official bases), legal basis requirement, and LGPD controller responsibility. This is rich behavioral context and does not contradict 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?

Four sentences, front-loaded with purpose, then relevant operational context. No wasted words, though it is a dense paragraph rather than structured 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?

For a simple read-only query with no output schema, the description provides substantial context: purpose, data sources, payment, legal/regulatory compliance. The main gap is parameter semantics and expected return format, but overall it covers the critical operational aspects.

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 should explain parameters, but it does not. It mentions physical vs legal entity but never maps CPF/CNPJ/completo, and the schema's requirement of both CPF and CNPJ seems inconsistent with 'ou' (or) semantics. No guidance on the optional 'completo' 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 states the tool provides credit score and risk analysis for individuals or legal entities, and explicitly says it queries credit bureaus and official databases. This distinguishes it from sibling tools like authenticate or marketplace, which are 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 gives clear usage context: it is a prepaid, credential-free credit query requiring a legal basis under LGPD. However, it does not explicitly state when to prefer this tool over alternatives or when not to use it, so it falls short of full exclusion 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?

Beyond annotations (readOnlyHint=false, openWorldHint=true), the description discloses that invoke runs uninstalled MCPs one-off, returns connect/checkout links when auth or payment is needed, and that writes require workspace owner/admin. It also reveals installed_in_toolkit vs installed_in_workspace status flags, adding significant behavioral 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 lengthy but each section adds distinct operational detail: core flow, invoke semantics, install vs invoke, permissions, and prompt library. It leads with a clear definition and is dense rather than redundant, though it could benefit from bullet points for readability.

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 with no output schema, the description is remarkably complete. It covers edge cases like auth/checkout links, permissions, billing, installed status, and the prompt library, leaving little ambiguity about the tool's overall behavior and scope.

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%, but the description adds meaning to the central 'action' enum by explaining each action's purpose (search, describe, invoke, install, etc.) and references key parameters like tool_id, mcp_id, and prompt_vars. However, many optional parameters (limit, query, immediate, tier_slug) are not explicitly described, though their names and defaults make them reasonably understandable.

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 mcp.ai marketplace, a catalog and execution platform for MCPs. It enumerates distinct capabilities (search, describe, invoke, install, subscribe, prompt library) and differentiates from sibling tools like authenticate and show_version.

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 outlines the core flow search→describe→invoke. It also contrasts list_tools and explains when to use subscribe/cancel/report_bug/request_mcp and the prompt library.

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?

With annotations already covering readOnly/destructive/idempotent hints, the description adds the behavioral note that the conversation array is needed for reproduction. It doesn't describe submission effects, duplicates, or expected response, but doesn't contradict 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 sentences, front-loaded with the purpose, then a single instruction. No wasted words, but under-specification of parameters slightly reduces information density.

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 3-parameter tool with no output schema and no schema descriptions, the description fails to explain the required 'message' parameter and 'context', and gives no indication of return values or post-submission behavior. It covers only the conversation parameter, leaving significant 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?

Schema description coverage is 0%, so the description must compensate. It only explains the 'conversation' parameter and omits 'message' (required) and 'context' entirely, leaving their semantics unclear.

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 'Report' and lists three purposes (bug, missing feature, feedback), clearly identifying the tool's role. It distinguishes from sibling tools which are unrelated, 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?

Provides explicit instruction to include the conversation array for reproduction, which is actionable. However, it doesn't state when to prefer this tool over alternatives or exclude any cases, leaving usage context 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds no extra behavioral context beyond stating the action, but that is sufficient for such a simple read-only operation.

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, front-loaded sentence with no waste. It immediately states the action and the target resource, making it highly 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?

Given the tool's simplicity (no params, no output schema, strong annotations), the description fully captures the necessary context for an agent to select and invoke it. No further detail is required for a version display operation.

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 has no parameter details to add. Per the rubric, a baseline of 4 applies when there are no params. The description is consistent with the empty 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 resource ('current MCP platform and adapter versions'). It distinguishes from sibling tools like authenticate or marketplace, as none of those relate to version information.

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 to retrieve version information. No explicit exclusions or alternative comparisons are provided, but the description makes the use case obvious. The sibling 'toolkit_info' could overlap, but the specificity of 'platform and adapter versions' mitigates ambiguity.

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 value by describing the returned data (MCPs, connection status, accounts, catalog tool counts), giving the agent a picture of what to expect. It does not need to repeat safety hints, and there are 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, tightly written sentence that front-loads the primary action ('Returns') and then lists the concrete components. Every word earns its place; there is no redundancy or filler. 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?

For a tool with no parameters, no output schema, and a straightforward read-only function, the description fully specifies the return value. It covers all the information an agent needs to decide to call it and interpret its result. Given the low complexity, 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 zero parameters, so the schema trivially covers 100% of parameters. Description adds no parameter semantics, but with no parameters there is nothing to clarify. Per rubric, the baseline for 0 params is 4, and no additional explanation is 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 starts with the specific verb 'Returns' and clearly identifies the resource: 'current toolkit state'. It enumerates the exact contents (installed MCPs, connection status, connected accounts, catalog tool counts), which distinguishes it from sibling tools like authenticate or connect. This is a model of purpose clarity.

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 conveys a clear context: this is the tool to inspect overall toolkit status. While it doesn't explicitly say 'use this when you need an overview' or exclude alternatives, the sibling tools (authenticate, connect, etc.) each have distinct actions, making the usage context obvious. A 4 is appropriate for clear context without explicit when/when-not guidance.

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