Análise de Crédito PF

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

Annotations already indicate idempotent and non-destructive behavior. The description supplements this by explaining the different outcomes of calling with vs without a token, and distinguishes session-only from permanent connections. It does not detail error handling or token storage, but covers the primary behavioral variations.

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 moderately concise, with three sentences. The 'Best' configuration instruction adds context but some may be extraneous for the AI agent's direct tool invocation. Still, it is well-structured and action-oriented.

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 one-parameter tool with no output schema, the description covers the core purpose, usage modes, and parameter semantics. It doesn't describe return values or failure modes, but these are not essential given the simplicity and existing annotations.

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 fully compensates by explaining the 'token' parameter's role (a JWT access token) and the optional behavior when omitted. It explicitly shows usage examples with { token: '<jwt>' } and no-args invocation, which adds complete semantic 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 identifies the tool as an authentication tool for MCP.AI in IDE contexts, using verbs like 'log in' and specifying the resource (access token, browser login). It distinguishes from siblings by focusing on access token handling, making its purpose unambiguous.

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 instructions for both invocation modes (with token for session-only login, without args to get a link) and further clarifies the permanent option via config header. This provides clear when-to-use guidance versus alternative approaches, including an explicit 'Best' recommendation.

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 this as read-only and idempotent. The description adds value by explaining the two states: all providers connected returns authenticated:true and empty pending[], while missing credentials returns connect_url and per-install URLs. This provides meaningful 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 two sentences, front-loaded with the main purpose, and each sentence provides concrete details without redundancy. It is an appropriately concise and well-structured description.

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 simplicity of the tool and lack of an output schema, the description effectively covers the main use cases and return states. It explains what is returned when all providers are connected and when credentials are missing, which is sufficient 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?

The tool takes zero parameters, so there is no parameter ambiguity. The empty schema fully covers this, and no additional explanation is needed. Baseline for 0 params is 4; the description adds no extra need, so a 5 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 clearly states the tool returns connection status and URLs, with specific behavior for all-connected and missing-credential cases. It is specific about the resource and verb, but does not explicitly differentiate from sibling tools like 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 implies the tool is used to check connection status and obtain URLs, but it does not explicitly state when to use it versus alternatives, nor does it provide exclusions or prerequisites. Context is present but not framed as 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, idempotent, non-destructive), the description adds cost implications (prepaid credit), lack of credentials, and LGPD compliance responsibilities for the client. This enriches the agent's understanding of side effects and prerequisites.

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 and front-loaded, delivering purpose, access model, cost, and legal context in just three sentences without unnecessary fluff.

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 largely complete for a read-only consult tool: it states purpose, returned data types, cost model, access method, and legal requirements. The only notable gap is the unexplained 'completo' parameter, but this does not severely impact overall 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 CPF parameter is explicitly described as the query key, but the optional 'completo' boolean is not explained at all. With schema description coverage at 0%, the description fails to compensate for the undocumented parameter, leaving the agent to guess its effect.

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 a credit consultation for individuals based on CPF, listing the specific data returned (dados cadastrais, score, pendências, histórico). It distinguishes itself from sibling tools since none of the siblings are credit-related.

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 context for usage: hosted by the platform, no credentials, pay-per-query with prepaid credit, and requires legal basis. It clearly implies when to use this tool but does not explicitly exclude alternatives, though none are present among siblings.

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?

Discloses key behaviors beyond annotations: invoke runs tools even when not installed, does not bloat the tool list, returns connect/checkout links when needed, requires workspace owner/admin for writes, and prompt links open without login. This is far richer than the generic readOnlyHint/openWorldHint flags and adds actionable 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 dense and information-rich, covering the main flow, special invoke behavior, billing, permissions, and the prompt library. Every sentence adds value, but the single-paragraph structure could benefit from bullet points or short sections to improve scannability for such a multi-action 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?

Given the tool's complexity (14 actions, 23 params, no output schema), the description is remarkably complete: it explains the core discovery/running cycle, special invoke semantics, install vs invoke, list_tools, billing actions, bug reporting, MCP requests, and the prompt library, including permission and login implications.

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 description explains the core parameters through the flow narrative (action, tool_id, mcp_id, prompt_slug/prompt_vars implied) and covers the main action branches. However, with 23 parameters and 0% schema description coverage, it does not individually clarify lesser-used ones like immediate, cancel_comment, request_details, or prompt_targets, leaving some reliance on parameter names.

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, a catalog and runtime for MCPs, with a concrete search→describe→invoke flow. It distinguishes itself from sibling tools by positioning itself as the meta-tool that discovers and runs others, not a specific domain action.

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 decision guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT', plus when to use search/describe/list_tools. It also explains when invoke returns connect/checkout links and to retry afterward, and notes owner/admin 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 provide safety profile (idempotentHint=true, destructiveHint=false, readOnlyHint=false). The description adds the behavioral requirement to include conversation for reproduction, which is useful. However, it does not disclose side effects like data transmission or ticket creation, so it does not fully illuminate the tool's behavior.

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 primary purpose. Both sentences are informative: the first states the action, the second gives a key usage detail. There is no fluff 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?

The tool is relatively simple with no output schema and minimal annotations. The description covers the primary purpose and the key parameter (conversation), but lacks explanation for the context parameter and does not describe any return values or side effects. This leaves a moderate completeness gap, especially given the 0% schema description coverage.

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 descriptions are absent (0% coverage). The description adds meaning only for the conversation parameter, explaining its role in reproduction. It does not explain the message or context parameters, leaving 'context' ambiguous. Additionally, the description calls conversation an 'array' while the schema types it as a string, which could cause confusion.

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 report a bug, missing feature, or send feedback. It uses a specific verb ('report') and resource (bug/feedback), and distinguishes it from sibling tools that are unrelated. The mention of reproduction via conversation adds 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 gives clear context for when to use the tool—whenever there is a bug, missing feature, or feedback. It also provides a usage instruction: include the conversation array. However, it does not explicitly mention alternatives or when-not-to-use cases, so it stops 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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds no further behavioral details (e.g., return format), but for a simple read-only version query, this is acceptable though 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?

A single sentence that directly states the action and the target information. No filler, perfectly sized for a trivial 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?

Given the tool's simplicity — no parameters, read-only safety annotations, no output schema — the description is fully complete. It tells the agent exactly what the tool does with no missing context.

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 zero parameters, the schema is empty and the description's 'current' implies no input is needed. This satisfies the baseline for a parameterless tool; the description doesn't need to add meaning beyond what the schema shows.

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 names the exact resource ('current MCP platform and adapter versions'), making the tool's purpose unambiguous. It clearly distinguishes from sibling tools like authenticate, connect, or marketplace, which focus on 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?

The description provides clear context for when this tool is appropriate — whenever version information is needed. It doesn't explicitly list exclusions or alternatives, but no sibling tool overlaps with this functionality, so the guidance is effectively complete.

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 and idempotentHint, so the safety profile is covered. The description adds valuable context about what the returned state includes (installed MCPs, connection status, accounts, tool counts), enriching behavioral understanding beyond the schema.

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 sentence that front-loads the key verb ('Returns') and efficiently lists the returned content without redundancy. Every phrase 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 zero-parameter state inspection tool with no output schema, this description is complete: it tells the agent exactly what information will be returned (installed MCPs, connection status, accounts, tool counts). No critical context is missing.

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 this dimension is 4. The description properly omits parameter details since there are none to document, and the schema confirms no inputs are 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 uses a specific verb 'Returns' and clearly identifies the resource: 'current toolkit state'. It enumerates concrete details (installed MCPs, connection status, accounts, catalog tool count) that distinguish it from siblings like show_version or 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 the usage context clear: call this to inspect toolkit state. It doesn't explicitly mention when not to use it or name alternatives, but given zero parameters and its informational nature, the intended usage is obvious. It stands apart from connection/auth tools.

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