Análise de Crédito PF Completa

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

Annotations already declare the tool as non-read-only, idempotent, and non-destructive. The description adds that the config method yields a non-expiring connection and the token method is session-only, and that no-args returns a link. However, it does not disclose exact return values or error behavior, leaving some gaps.

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 run-on paragraph that mixes user instructions with tool behavior, opening with a confusing label. It could be restructured into clear steps or bullets; while each sentence carries information, the lack of organization makes it harder 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?

For a simple tool with one optional parameter and no output schema, the description covers the primary usage patterns. However, it omits explicit return-value details for token-based calls and any error cases, leaving the tool's behavior only partially specified.

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 offers a single optional 'token' string with no description (0% coverage). The description clarifies that the token is a JWT for session login and that calling with no args provides a link, giving essential meaning to the parameter that the schema lacks.

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 indicates the tool handles authentication for IDE agents, with two modes (permanent config header and session token). It doesn't use a crisp 'verb+resource' structure and the opening 'MCP.AI for IDE agents' is more of a label, but it does distinguish the tool's role from siblings by explaining the auth flow.

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 scenarios: 'Best: add it to this server's config as a header' for permanent access, or 'paste it here' for a session, including calling with no args to get a link. It doesn't mention when not to use this tool or alternative tools explicitly, but the conditional guidance is actionable and clear.

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 value by detailing the return behavior (authenticated:true with empty pending[], or connect_url/per-install URLs), but it does not specify partial connectivity scenarios, leaving a minor transparency gap.

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 just two sentences, front-loaded with the primary purpose. Every clause adds specific information about condition-based outputs, with no filler or repetition.

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 (no params, no output schema), the description covers the main outcomes well. However, it omits the case of partial connectivity where some providers are connected and others are not, which could be a realistic scenario for a connection status 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 doesn't need to add parameter information, and it correctly focuses on the return value logic.

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', using a specific verb and resource. It distinguishes from sibling 'authenticate' by focusing on status rather than performing authentication, and the contextual details about authenticated:true and connect_url reinforce its role.

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 by explaining what happens in two scenarios: when all providers are connected and when credentials are missing. However, it does not explicitly mention alternatives or when not to use this tool, though the sibling context implies 'authenticate' is for initiating auth.

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, idempotent, non-destructive behavior. The description adds valuable context beyond annotations: no credentials, prepaid payment, queried bureaus, and LGPD/legal basis obligations. This enriches the agent's understanding of operational and compliance aspects.

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?

Three sentences, each adding meaningful information: purpose, operational context, and legal note. 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?

The description covers purpose, data sources, pricing, and legal basis, but the unexplained 'completo' parameter is a clear gap. Without an output schema or parameter descriptions, the tool is not fully specified.

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 provides context for the CPF parameter ('a partir do CPF') but completely omits the boolean 'completo' parameter, leaving its function ambiguous. This is a significant gap for a tool with only two 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 performs a complete credit analysis of an individual from CPF, enumerating the data types (registration data, score, pendencies, history). This specific verb+resource combination distinguishes it from the unrelated sibling tools.

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: hosted by the platform, no credentials, prepaid credit per consultation, and legal basis requirement. It doesn't explicitly exclude alternatives, but no similar sibling exists, so the context is sufficient for usage.

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?

Goes far beyond annotations by disclosing that invoke runs one-off even when the MCP is not installed, without adding to the tool list; that install/uninstall/subscribe/cancel write operations require workspace owner/admin; and that search/describe flag installation state. These are actionable behavioral insights not present in the annotation flags.

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 (~200 words) but well-structured, front-loading the core flow and then expanding on invoke behavior, install guidance, and prompt library. Each section earns its place given the tool's 14 actions, though a slightly tighter wording would improve scannability.

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?

Covers the full lifecycle: discovery, profiling, invocation, installation, billing, permissions, feedback, and prompt library, plus credential/checkout flows. Misses explicit mention of some parameters (resume, immediate, tier_slug) but provides enough overall context to guide an agent for most use cases.

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?

Despite 0% schema description coverage, the description explains core parameters: action (enumerated search/describe/install/invoke etc.), mcp_id, tool_id, arguments, prompt_slug, prompt_vars, prompt_body. It clarifies the search→describe→invoke flow and that get_prompt fills {{variables}}, giving real semantic meaning to schema properties.

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 opens with 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' clearly stating the tool's dual role as catalog and execution interface. It distinguishes from siblings like authenticate or connect by positioning itself as the central hub for discovering/invoking MCPs and managing prompts.

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 when-to-use guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT'. Differentiates sub-actions like list_tools, report_bug, and request_mcp, and gives conditional behavior for missing credentials or wallet funds (connect/checkout links).

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 disclose idempotent and non-destructive behavior. The description adds context about including the conversation array but does not elaborate on post-submission effects or return values. Minimal added value beyond 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 that are front-loaded with the action and scope. No unnecessary words or repetition; every word 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 reporting tool with no output schema, the description covers the core function and key input guidance. It could mention what happens after submission, but that is not essential given the tool's simplicity.

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 clarifies the 'conversation' parameter's role in reproduction, but 'context' remains unexplained, and 'message' is only inferable from the tool's purpose. Partial compensation for the 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 clearly states the tool's function with a specific verb 'Report' and resource 'bug, missing feature, or feedback'. It distinguishes itself from siblings like 'authenticate' or 'show_version' by its unique support/meta nature.

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 that this is the reporting channel and explicitly instructs to include the conversation array for reproduction. However, it does not offer exclusions or alternatives, though siblings are unrelated so 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 declare readOnlyHint, idempotentHint, and non-destructive. The description aligns with these and clarifies the specific content (platform and adapter versions), but adds no additional behavioral details beyond 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?

Single sentence, direct, 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?

Simple 0-parameter, read-only tool; the statement fully conveys what the user will get (versions). No output schema required.

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 zero parameters, so description needs no parameter semantics. Baseline of 4 is appropriate.

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 the specific verb 'Show' with a clear resource: 'current MCP platform and adapter versions.' This differentiates from sibling tools like authenticate or report_bug, which target different 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?

No explicit usage guidance or alternatives are mentioned. However, the tool name and description imply its use when version information is needed. There is no when-not-to-use 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 readOnlyHint, idempotentHint, and destructiveHint, safely covering the mutation profile. The description adds useful context about what exact state components are returned (installed MCPs, statuses, accounts, tool counts), providing transparency about the output scope 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 a single concise sentence that front-loads the primary action ('Returns the current toolkit state') and then lists the specific components without unnecessary words. Every phrase 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?

Given that the tool has no parameters and no output schema, the description adequately covers both purpose and return content. It names all key aspects of the toolkit state (MCPs, status, accounts, catalog tool counts), making it complete 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?

The tool has zero parameters, so the baseline for parameter semantics is 4. The description does not need to explain parameters, and it sufficiently describes what the tool returns, which is the only relevant semantic content.

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 the specific verb 'Returns' and details the exact contents: installed MCPs, their connection status, connected accounts, and catalog tool counts. This makes the tool's purpose unmistakable and clearly distinguishes it from action-oriented siblings like connect and authenticate.

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 it clear that this tool is for inspecting toolkit state, which contrasts with the action-oriented siblings. However, it does not explicitly state when to use this tool over alternatives or provide exclusions. The context implies usage for state checks, but explicit guidance is absent.

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