SCR Banco Central (Resumo)

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

Annotations already indicate idempotent and non-destructive behavior. The description adds context about the two modes (permanent config vs session-only) and the behavior of calling with no args (returns a link). It does not disclose error handling or side effects like invalidating prior tokens, but the added context is valuable within the annotation baseline.

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 and runs on, but it is front-loaded with the purpose and every clause adds needed information. It is efficient for the amount of guidance provided, though it could be split into clearer sentences.

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 absence of an output schema, the description covers the core invocation patterns and expected outcomes for the no-args case (returns link). It does not explicitly state what the response is when a token is provided, nor error cases, but the tool is simple enough that this is not a critical 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 schema only defines 'token' without description (0% coverage). The description fully compensates by explaining that the token is a JWT, that it can be omitted to get a login link, and that providing it performs a session login. This is precisely the semantics an agent 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 explicitly states the tool's purpose: to authenticate for MCP.AI in IDE agents by logging in via browser and copying an access token. It clearly distinguishes this from sibling tools by focusing on the authentication/login flow, not just repeating the name.

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 usage scenarios: best practice is adding the token to server configuration for a permanent connection, or pasting it for a session-only login, or calling with no args to get the link. This gives clear when-to-use and how-to-invoke guidance, effectively differentiating between options.

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 safety profile is covered. The description adds valuable context about response states (authenticated:true vs connect_url), going beyond 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 two sentences, front-loaded with the core purpose, and each sentence adds meaningful detail about return states. 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?

Given the low complexity and no output schema, the description explains the main return conditions well. However, it does not cover partial connectivity scenarios (some providers connected, others not), leaving a small gap in completeness.

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 burden. Baseline 4 is appropriate as there are no parameter semantics to clarify.

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 conditional behaviors (authenticated:true vs connect_url). This is a specific verb+resource+scope, and the differentiation from siblings like authenticate is implicit but clear.

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 this is for checking connection status, but it does not explicitly state when to use this over alternatives like authenticate. No when/when-not guidance is provided, only behavior descriptions.

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 behavioral nuances beyond annotations: invoke runs one-off without installing, returns connect/checkout links when needed, and writes require workspace owner/admin. It explains the 'retry' flow and the prompt library, adding operational detail the annotations lack.

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 longer than typical but well-structured, starting with the core value proposition and then systematically covering the flow, install vs. invoke, permissions, and the prompt library. It is front-loaded and organized, though a few phrases could be tightened without losing meaning.

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 complex tool with 23 parameters and 14 actions, the description covers the primary use cases, safety, and the prompt library, which is sufficient for initial selection. It does not detail return values (no output schema) or edge cases like pagination, but the overall guidance is substantial.

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 coverage, the description adds meaning for core parameters like action, mcp_id, tool_id, and arguments by explaining their role in the discover-describe-invoke flow. However, many secondary parameters (limit, immediate, tier_slug, cancel_reason, etc.) remain undocumented, so it doesn't fully compensate for 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 identifies the marketplace as 'the in-platform catalog of every MCP/tool, AND the way to run them,' with a specific core flow (search → describe → invoke). It distinguishes itself from siblings like authenticate or show_version by naming its own scope and actions.

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 guides when to use invoke vs install: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT.' It also covers capability requests, lists action categories, and notes permission requirements for writes.

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 and destructiveHint=false, covering key safety aspects. The description adds context that the conversation parameter aids reproduction, which is a useful behavioral detail. However, it does not disclose what happens after reporting (e.g., whether a ticket is created, if confirmation is returned), leaving some ambiguity. This matches a mid-range score where annotations reduce the burden but additional context is still limited.

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 two-sentence, front-loaded statement: first states the action, then the key usage instruction. Every word serves a purpose, with no redundancies or filler. It is an ideal length for the tool's simplicity.

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?

Despite its brevity, the description effectively covers the core action and a crucial usage detail (conversation array). Given the tool's simple nature, no output schema, and annotations covering idempotency/destructiveness, it is nearly complete. It could be improved by mentioning expected result or response, but overall it meets the needs for an agent to correctly invoke the 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?

Schema description coverage is 0%, so the description must compensate. It explicitly explains the conversation parameter's purpose ('with recent messages for reproduction'), but does not clarify the 'message' or 'context' parameters. 'Message' is self-explanatory, but 'context' remains vague. The description provides partial compensation, earning a middle score.

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 opens with a specific verb phrase 'Report a bug, missing feature, or send feedback' and clearly identifies the tool's resource (bug/feature/feedback). It distinguishes itself from unrelated siblings like authenticate and show_version by outlining an unambiguous purpose.

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 guidance on how to use the tool, specifically instructing to 'Include the conversation array with recent messages for reproduction.' While it does not explicitly mention alternatives, no sibling tool serves the same feedback-reporting function, so the context is clear. It lacks an explicit 'when not to use' but this is a minor gap.

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, and non-destructive behavior. The description adds meaningful context: no credentials are needed, it is pay-per-consultation with prepaid credit, and the client is responsible for LGPD compliance. This goes beyond 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, front-loaded with the core purpose. It efficiently conveys the product name, alternative phrasing, payment model, and legal obligations. Slightly dense but each sentence adds 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?

The core purpose, payment model, and legal constraints are covered, but the description does not explain the 'completo' parameter or the response format (no output schema exists). For a prototype-like tool with minimal parameters, this is acceptable but leaves clear 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 maps CPF to 'pessoa física' and CNPJ to 'pessoa jurídica', but it does not mention the optional 'completo' parameter at all. The agent would not understand the meaning or impact of 'completo'.

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 a summary of credit operations in the SCR of the Central Bank, and explicitly says 'Consulta informação de crédito', identifying the action. It distinguishes itself from generic platform sibling tools (authenticate, marketplace) by focusing on a specific credit bureau query.

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 for when to use: it is a paid, credential-free consultation of credit information, and it explicitly states a legal basis is required (e.g., risk analysis requested by the data subject). It does not explicitly name alternatives, but siblings are not competing credit tools, so the context is sufficient.

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 no additional behavioral context beyond stating the action, such as return format or side effects, but 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?

The description is a single, grammatically correct sentence that is front-loaded with the verb and resource. Every word earns its place, with no redundancy or filler.

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 tool with annotations already covering safety, the description is complete. It does not need to elaborate on output schema or side effects, as the purpose is straightforward and fully conveyed.

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, and the schema is trivially 100% covered. With zero parameters, the description need not explain any parameter semantics; the described behavior sufficiently maps to the tool's use.

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') and identifies the resource ('current MCP platform and adapter versions'), making the tool's purpose immediately clear. It also distinguishes itself from sibling tools by focusing on version information rather than actions like authentication or connectivity.

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—when you need to know current versions—but does not explicitly state when to use this tool versus alternatives. No exclusions or alternative tool references are provided, so guidance is only 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 known. The description adds context about what state is returned (MCPs, connection status, accounts, catalog tool counts), which is beyond the annotations. No additional behavioral notes (e.g., latency, side effects) are needed for a read-only info tool.

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 leads with the action and then lists the specific data points. Every phrase contributes meaningful information—no filler, tautology, 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?

With no parameters and no output schema, the description carries the full burden of explaining what the tool returns. It does so completely by listing the four categories of state information. This is fully adequate for an agent to decide when to invoke the tool and 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?

The tool has zero parameters, so the description has no obligation to explain parameters. The baseline for parameterless tools is 4; the description adequately addresses what the tool does without any 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 uses a specific verb ('Returns') and names the exact resource ('current toolkit state'), then enumerates the contents: installed MCPs, connection status, connected accounts, and number of catalog tools. This clearly distinguishes it from siblings like show_version (which likely reports version) and connect/authenticate (which perform actions).

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 makes the tool's context obvious: it provides a state snapshot. It does not explicitly mention when to use it versus alternatives, nor does it state exclusions. However, the enumerated contents (installed MCPs, connection status, accounts, tool counts) implicitly signal that this is the go-to tool for assessing toolkit health or availability, which is sufficient given the sibling set.

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