SCR Banco Central (Detalhado)

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

The description adds context beyond the annotations: it reveals the browser-based flow, the return of a login link when no args are given, and the distinction between permanent and session-scoped authentication. It does not contradict the annotations (idempotentHint true) and provides useful behavioral detail, though it omits potential error cases.

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 informative but somewhat run-on, bundling multiple instructions into a single paragraph. The front-loading of 'MCP.AI for IDE agents' and the browser login step is good, but the sentence structure could be more organized for faster parsing. Still, every part contributes value.

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 no output schema and one optional parameter, the description covers the essential aspects: the two auth modes, how to obtain the link, and how to use the token. It is sufficiently complete for an agent to invoke the tool correctly, though it does not detail the response on success or failure beyond the link.

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 that the token is a JWT pasted from the browser and that omitting the token triggers a link response. This gives the single parameter clear semantic meaning beyond just its type and optionality.

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 the MCP server for IDE agents via browser login and token. It distinguishes this from siblings by providing concrete instructions for the authentication flow and mentions the permanent config option, which is specific to this tool.

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 explains when to use the config header (permanent) versus the session token (session-only), and when to call with or without the token argument. This is clear, actionable guidance that helps the agent decide the appropriate invocation.

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 non-destructive behavior. The description adds value by detailing conditional return states (authenticated:true with empty pending[] vs connect_url when credentials missing), which is beyond annotation coverage.

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?

Description is two sentences, front-loaded with purpose, and provides relevant conditional details without any redundant or extraneous text.

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 no output schema, the description explains the two primary return scenarios (all providers connected vs missing credentials). However, it does not address partial connection states, which could be a potential gap for a status-checking tool.

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 offers no semantic content. According to calibration, 0 params baseline is 4. The description does not need to add parameter information.

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 'Returns connection status and URLs' with a specific verb and resource. It implicitly distinguishes from sibling 'authenticate' by focusing on status rather than establishing a connection.

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 but does not explicitly state when to use this tool versus alternatives like 'authenticate'. There is no direct comparison or 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 the annotations (readOnly=false, openWorld=true, idempotent=false, destructive=false), the description reveals critical behaviors: invoke runs uninstalled tools without bloating the toolkit, returns connect/checkout links for auth/payment issues (then retry), one-off install require owner/admin, and prompt links open without login. These are non-obvious, actionable traits disclosed fully, with no contradiction to 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?

Every sentence is information-dense and earns its place, but the entire description is one giant paragraph without line breaks or sectioning, making it harder to scan. The front-loaded purpose statement helps, but the structure could be improved with bullet points or separate blocks for the marketplace flow, prompt library, and permissions.

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 description is remarkably complete for a tool with 14 actions and no output schema. It covers all actions, the core user flow, auth and payment edge cases, permission requirements, installed-state flags, and the prompt library's shareable-link behavior. No aspect of the tool's operation is left unexplained, making it nearly self-sufficient 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?

With 0% schema description coverage, the description carries the whole burden. It explains the meaning of key parameters: action's 14 enum values are all described, tool_id/arguments are contextualized in the invoke flow, mcp_id in describe/install, and prompt_* params in the prompt library. However, several params like limit, immediate, conversation, report_context, request_details, and prompt_targets are never explicitly mentioned, so the compensation is strong but incomplete.

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 opening sentence clearly defines the tool: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It goes on to explain the core search → describe → invoke flow, and contrasts invoke vs install, making the tool's role distinct from siblings like authenticate/connect/report_bug. This is a specific, differentiated purpose statement.

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 explicit when-to-use guidance: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT.' It also explains when to use search/describe, subscribe/cancel, report_bug, request_mcp, and the prompt library actions, and notes owner/admin requirements for writes. Clear decision rules and alternatives are provided.

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 provide idempotentHint=true and destructiveHint=false, so the safety profile is known. The description adds valuable behavioral context by telling the agent to include the conversation array for reproduction, which helps set expectations for how the tool should be invoked beyond what annotations disclose.

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 purpose and then provides a critical instruction. Every word earns its place, and there is no redundancy or irrelevant detail.

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 bug reporting tool, the description covers the main purpose and reproduction guidance, but it lacks clarity on the required 'message' parameter and the response/outcome behavior. Since there is no output schema, more context on return values or side effects would be helpful, though not critical for a straightforward reporting action.

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 ('Include the conversation array with recent messages for reproduction'), but does not clarify what 'message' (required) or 'context' mean. This leaves the most important parameter under-specified.

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 resources 'bug, missing feature, or send feedback.' This is distinct from sibling tools like authenticate or show_version, which have unrelated functions, so 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 tells the agent when to use this tool ('Report a bug, missing feature, or send feedback') and provides a key usage instruction ('Include the conversation array with recent messages for reproduction'). It does not explicitly state when not to use alternatives, but the guidance is clear enough for typical scenarios.

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 and idempotent behavior. The description adds significant context beyond that: no credentials needed, per-query prepaid credit, and LGPD responsibility, which are not captured in 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 three sentences, each carrying essential information: purpose, hosting/pricing, and legal compliance. There is no wasted wording.

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 description omits critical invocation details: the expected format for MESANO (e.g., MMYYYY) and the logic behind requiring both CPF and CNPJ simultaneously. While it provides legal and billing context, the ambiguity around required fields and optional 'completo' parameter makes the tool not fully self-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?

With 0% schema description coverage, the description must compensate. It hints at CPF/CNPJ for 'pessoa física ou jurídica' and MESANO for 'mês e ano de referência', but it does not explain the 'completo' boolean or clarify why both CNPJ and CPF are marked required in the schema. This leaves key parameters underspecified.

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: 'Detalhamento das operações de crédito... no SCR do Banco Central' by month and year for individuals or legal entities. This provides a specific verb and resource, distinguishing it from generic 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 gives clear context: hosted by the platform, prepaid billing, and a requirement for legal basis (e.g., risk analysis). It does not explicitly name alternatives, but there are no sibling tools performing this type of credit query, so the absence of exclusions is acceptable.

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 covered. The description adds no additional behavioral context such as output format or limitations, marking it as adequate but not enhanced.

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 that fully conveys the tool's purpose without any redundant wording. It is an excellent example of conciseness for a simple tool.

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 trivial in scope, annotations provide safety guarantees, and the description fully explains what it does. There is no missing context for an agent to misinterpret or misuse this tool.

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 does not need to explain parameter meanings. The baseline of 4 applies because there is no parameter information to supplement.

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 resource 'current MCP platform and adapter versions'. It is unambiguous and distinct 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 implies usage for checking version info, and there is no competing sibling tool. However, it does not explicitly state when to prefer this tool over others, 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description does not need to restate safety. It adds useful context by detailing exactly what state is returned (installed MCPs, statuses, accounts, catalog counts), which goes beyond the annotation metadata.

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 core purpose and uses a compact list to convey all key return elements. Every word contributes value; there is 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?

Given the tool has no input schema, no output schema, and only annotations, the description fully specifies what the agent can expect from the call (installed MCPs, statuses, accounts, catalog counts). This is complete for a read-only state-inspection tool.

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 compensates by explaining what the tool returns, which is the most relevant semantic information for an agent invoking it.

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 the current toolkit state, enumerating specific details (installed MCPs, connection status, connected accounts, catalog tool counts). It is distinct from siblings like show_version, which focuses on version info, and marketplace, which likely handles discovery.

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 context that this is a state-inspection tool, implying it should be used when an overview of MCP connections and catalog counts is needed. It does not explicitly mention when not to use it or name alternatives, but sibling tool names and the descriptive content make its niche reasonably clear.

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