Inabilitados BACEN

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 behavioral context by explaining the two modes (permanent vs. session), the fact that it can generate a login link, and that the config method is non-expiring. This 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 three sentences and front-loaded with the purpose. It's slightly dense but every sentence provides necessary information (purpose, permanent config, session login). The structure is logical, moving from high-level to specifics.

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), the description covers the essential usage modes, parameter meaning, and behavior. It doesn't describe the return value or error cases, but for an authentication tool with no output schema, this is adequate.

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 only a 'token' string with no description (0% coverage). The description compensates fully by explaining the token is a JWT for session login, showing the exact call syntax, and clarifying that calling with no args returns a link. This adds significant meaning beyond the bare 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 purpose: to authenticate by logging in via browser and providing an access token, or getting a login link. It uses specific verbs like 'log in' and 'copy the access token', and distinguishes the token-based session login from the permanent config method. This differentiates it from 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?

The description provides clear usage context: it explains when to use the config header for a permanent, non-expiring connection vs. pasting a token for session-only login, and how to call with no args to get the link. However, it doesn't explicitly mention alternatives or when not to use this tool compared to sibling tools like 'connect'.

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, and the description adds substantial extra behavioral context: hosted by platform, no authentication, per-query cost, and LGPD compliance responsibility. This goes beyond the structured annotations and gives the agent actionable expectations.

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 front-loaded with the core purpose and uses three sentences to add payment, auth, and legal context. Each sentence contributes value; no redundant filler, though the LGPD detail could be seen as secondary.

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 tool with two parameters and no output schema, the description covers key operational aspects: purpose, access method, cost, and data sensitivity. The missing documentation for 'completo' prevents a perfect score, but overall 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?

Schema description coverage is 0%, so the description must compensate. It mentions CPF as the identifier but completely omits the optional 'completo' boolean parameter, leaving agents without guidance on its meaning. This is a significant 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 uses a specific verb ('Verifica') and names the exact resource ('Quadro Geral de Inabilitados do Banco Central'), with the input (CPF) clearly stated. It is unmistakably distinct from the unrelated platform-level siblings.

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 operational context: no credentials required, prepaid credit payment, and public access. It does not explicitly list when-not-to-use or alternatives, but the sibling tools are platform utilities, so the use case is sufficiently implicit.

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 mark the tool as read-only and idempotent. Description adds specific behavioral details: authenticated:true and empty pending[] when all providers are connected, and connect_url when credentials are missing. Consistent with annotations, no 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?

Two sentences, front-loaded with the primary action, no unnecessary words. Efficiently covers both main scenarios.

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 parameterless status-check tool with no output schema, the description adequately covers return values and conditional behavior. It gives enough detail for an agent to understand what to expect.

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?

Zero parameters, so baseline is 4. Description adds no parameter info (none needed), but explains the output semantics that depend on system state, which is appropriate for a no-arg tool.

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?

Description clearly states the tool returns connection status and URLs, with specific behavior for authenticated and missing-credential states. This is distinct from sibling tools like authenticate or marketplace.

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 context for when to use: to check connection status and obtain URLs. Implicitly indicates when alternatives might be relevant (e.g., authenticate), but no explicit exclusions or direct sibling comparisons.

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 false, destructiveHint false), the description discloses permission requirements for writes, the one-off execution behavior of invoke, connect/checkout link fallbacks with retry instructions, and the distinction between installed_in_toolkit vs installed_in_workspace. This is rich, non-obvious 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 long but information-dense, covering a complex multi-action tool without filler. It front-loads the core flow and highlights critical caveats. A bulleted structure could improve scannability, but every sentence earns its place.

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 high complexity (23 params, no output schema), the description covers the most important operational aspects: search/describe/invoke flow, install vs invoke semantics, auth/payment fallbacks, permissions, and the prompt library. It leaves some actions like resume and several params unexplained, but overall provides a strong operating manual for an agent.

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% with 23 parameters, and the description compensates by explaining the meaning of key actions and a few parameters (action, mcp_id, tool_id, arguments, prompt_vars implicitly). However, many parameters like immediate, tier_slug, conversation, report_context, prompt_title, and cancel_reason remain undocumented, leaving the agent to infer their purpose from the action context.

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 with a distinct dual role: cataloging MCPs and executing them. It names explicit actions like search, describe, invoke, install, and the prompt library, making it easy to distinguish from sibling tools 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 provides a core flow (search → describe → invoke), explicitly contrasts invoke vs install, states when to use request_mcp for gaps, and explains subscribe/cancel/report_bug. It tells the agent when to prefer invoke for one-off use and install for permanent toolkit membership.

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, covering high-level behavior. The description adds only the instruction to include the conversation for reproduction, which is more of a parameter guideline than a behavioral trait. It does not disclose any side effects, such as where the report goes or if data is sent externally.

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 purpose and immediately adds the key instruction. There is no filler or redundancy; every clause earns its place.

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 three string parameters and no output schema, the description covers the core purpose and gives one reproduction hint. However, it lacks details on expected formats (e.g., conversation string vs. array), what to place in 'context', and any post-submission behavior. While annotations provide some safety context, the description leaves enough ambiguity that an agent might misformat inputs.

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 mentions the 'conversation array' and its purpose for reproduction, but does not clarify that 'conversation' is a string (JSON array string) per the schema, nor does it explain the 'message' and 'context' parameters beyond the tool's general purpose. Significant gaps remain for parameter understanding.

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 ('Report') and resource ('a bug, missing feature, or feedback'). It distinguishes from siblings because none of the sibling tools (authenticate, connect, marketplace, etc.) relate to reporting or feedback.

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 for when to use the tool: to report a bug, missing feature, or feedback. It also gives a specific instruction to include the conversation array. However, it does not explicitly mention when not to use it or alternative tools, though the sibling list makes alternatives unlikely.

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, establishing a safety profile. The description adds minimal context ('current') but does not disclose return format or potential variations. Since it's a simple read, this is adequate but not rich.

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?

One clear, concise sentence that immediately conveys the tool's function. No wordiness 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?

For a simple version query with no parameters and strong annotations, the description is sufficient. It lacks an output schema and does not specify the exact response structure, but the tool's simplicity makes that less 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?

There are zero parameters, so the description does not need to explain parameter usage. The baseline is 4 for no-param tools, and the description provides enough context about what is returned.

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') with a clear resource ('current MCP platform and adapter versions'). It clearly distinguishes from sibling tools like authenticate, connect, and report_bug, 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 description clearly implies when to use the tool (when version information is needed) and no alternatives are listed among siblings. However, it lacks explicit when-not-to-use or exclusionary 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 the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral context by specifying exactly what state information is returned (installed MCPs, connection statuses, connected accounts, catalog tool counts), 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?

A single, tightly packed sentence that front-loads the action ('Returns') and immediately lists the concrete information items. No filler words or redundant details.

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 no-parameter info tool with no output schema, the description fully specifies the returned content. There is no missing information that would hinder an agent's ability to invoke and use the tool correctly.

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 input schema is empty and fully describes the parameter space; the description doesn't need to explain parameter semantics. There is nothing more to add.

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 ('Returns') and resource ('current toolkit state'), and enumerates the key information returned (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from sibling tools that perform actions 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 clear use case: use this tool to inspect the current toolkit state. While it doesn't explicitly mention alternatives or exclusions, the context is clear enough given the sibling tool names, which focus on actions rather than state inspection. This meets the 'clear context, no exclusions' level.

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