CVM Processos Sancionadores

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

Annotations already signal idempotency and non-read-only, and the description adds valuable context about the two authentication modes (non-expiring header vs session-only). It explains that calling with no args returns a link, and with a token authenticates. No contradictions with 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 reasonably concise, with three sentences that front-load the purpose and then provide usage details. It includes some extraneous context like 'MCP.AI for IDE agents (Cursor, etc.)' but this helps clarify the intended environment. The information is well-structured for quick reading.

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 simple (one optional param, no output schema), and the description covers both authentication flows and the no-arg behavior. It does not mention return values beyond 'get the link', nor error handling, but given the idempotent and non-destructive annotations, this feels adequate. It could be improved by stating what happens after successful token submission.

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 schema description coverage at 0%, the description carries the full burden. It explains the 'token' parameter is a JWT to paste, that it is optional (since no-args is allowed), and its role in obtaining a session-only login. This is sufficient for practical use, though it does not specify the exact format beyond 'jwt' or potential validation rules.

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 is for logging in and obtaining an access token, with specific instructions for both permanent (config header) and session-only (token argument) authentication. It distinguishes itself from sibling tools like 'connect' by explicitly framing it for MCP.AI and IDE agents.

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 two clear usage paths: 'Best: add it to this server's config...' for a permanent token, or 'paste it here for a session-only login...' for temporary access. It also explains the no-arg case for retrieving the login link. However, it does not explicitly compare itself to the 'connect' sibling tool, so some agent might still be unsure when to choose this over alternatives.

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, non-destructive behavior. The description adds valuable state-dependent context: it explains the meaning of 'authenticated:true', empty 'pending[]', and the presence of 'connect_url' and per-install URLs when credentials are missing. This goes beyond 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 two sentences, front-loaded with the main purpose, then detailing the two states. Every sentence earns its place with 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?

The description covers the main scenarios but leaves the partial-connection case ambiguous (what happens if some providers are connected and others not?). It also doesn't detail the exact response structure beyond 'authenticated', 'pending', and URLs. Given the tool's simplicity and no output schema, it is mostly complete but with minor 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?

The tool has zero parameters and schema coverage is 100%. Baseline is 4 for 0-parameter tools. The description does not need to cover parameters and adds no irrelevant details.

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', using a specific verb and resource. It distinguishes behavior under two conditions (all connected vs missing credentials), which differentiates it from the sibling 'authenticate' likely used for initiating authentication.

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 when to use (checking connection status) but does not explicitly state 'use this when...' or mention alternatives like 'authenticate'. It provides context about expected outputs under different conditions, which helps infer usage, but lacks explicit when-to-use vs alternatives.

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 readOnly, idempotent, and non-destructive hints. The description adds valuable behavioral context: payment with prepaid credit, no authentication required, and LGPD data-controller responsibilities, which are not captured in 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 four sentences covering purpose, access model, data nature, and legal responsibility. Each sentence adds useful information, though the legal disclaimers slightly extend the length.

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 key operational aspects (paid, no auth, public data) and legal considerations, but lacks details about the response format and does not resolve whether one or both identifiers are needed. Since there is no output schema, more guidance on returned data would be helpful.

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, but it only names CPF/CNPJ as identifiers without format or usage details. It fails to explain the optional 'completo' parameter, and its 'ou' (or) wording conflicts with the schema's requirement for both CPF and CNPJ.

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 consults CVM sanctioning administrative processes for individuals/legal entities using CPF or CNPJ. The verb 'Consulta' is specific, and the scope (CVM, sanctions, pessoa física/jurídica) is unambiguous. It distinguishes from unrelated 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?

It provides clear context on when to use: hosted by the platform, no credentials, prepaid credit, and access to public data. It does not explicitly name alternatives or exclusions, but the sibling tools are unrelated. Minor ambiguity arises from saying 'CPF ou CNPJ' while the schema requires both parameters.

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 discloses important behavioral traits beyond annotations: writes require workspace owner/admin, invoke is a one-off execution that does NOT bloat the tool list, install makes the MCP permanent, and the prompt library allows sharing via a link that opens without login. It even explains failure paths (connect link, checkout link) and retry behavior, which is much richer than the annotation flags alone.

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 long, dense paragraph, but each section earns its place: core flow, KEY invoke behavior, install vs invoke, and the prompt library. It uses labels like 'Core flow:' and 'KEY:' to aid scanning. It could be tightened, but for a tool with 14 actions, the length is justified and it remains well-structured.

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 provides comprehensive context: it covers all action categories, auth constraints, failure modes, and even the prompt library. It explains the two major sub-domains (MCP execution and prompt retrieval) well enough for an agent to select actions and invoke parameters correctly. The absence of output schema is mitigated by describing what each action returns (profile, links, shareable URL).

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?

Although schema description coverage is 0%, the description compensates significantly by mapping actions to their parameter roles (e.g., action=search, mcp_id for describe, tool_id+arguments for invoke, prompt_slug for get_prompt). It does not explain every parameter (e.g., immediate, tier_slug, conversation), but the core action-specific parameters are contextualized. Given the large parameter count, the partial coverage is reasonable.

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 introduces the tool as the 'official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It explains the core search → describe → invoke flow and covers actions like install, subscribe, and the prompt library, making the tool's broad scope understandable. It doesn't explicitly compare itself to siblings like authenticate/connect, but its marketplace identity is unambiguous and distinct.

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?

Usage guidance is explicit and prescriptive: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT'. It also explains what happens when credentials are missing or wallet is empty, and tells the agent to retry after the user completes the connect/checkout. The description even distinguishes installed_in_toolkit vs installed_in_workspace, giving clear context for interpreting search results.

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 convey that this is a write operation (readOnlyHint=false) and non-destructive. The description adds that the conversation array should be included for reproduction, which is useful context, but does not disclose additional behavioral traits like rate limits or response handling. No contradiction with 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 sentence with two clauses, no filler. The primary purpose is front-loaded, followed by a concise usage instruction, making it efficient and well-structured.

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 annotations and no output schema, the description covers the core action and the key reproduction context. However, it omits the meaning of 'context' parameter and what happens after submission (e.g., confirmation), leaving minor gaps but nothing 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?

The schema provides zero parameter descriptions, so the description must compensate. It clarifies the 'conversation' parameter by asking for an array for reproduction, but leaves 'context' completely unexplained and 'message' only implied as the report content. This is partial compensation at best.

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 'Report' and identifies three distinct targets: a bug, missing feature, or feedback. This clearly differentiates the tool from sibling tools like authenticate or marketplace, establishing a distinct 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 implies usage for reporting issues and provides a how-to instruction ('Include the conversation array with recent messages for reproduction') but does not explicitly state when to use this tool vs alternatives or mention any exclusions. The purpose statement carries the usage context.

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 the word 'current' to indicate a live query, but does not disclose output format or other behavioral details, so it only modestly supplements 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?

A single concise sentence that is front-loaded with the verb and resource. Every word earns its place, and there is no superfluous content.

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, no output schema) and the annotations covering safety, the description fully explains what the tool does. It is complete for its intended use, and no additional context is needed.

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 input schema has zero properties and there are zero parameters, so the baseline is 4. The description does not need to add parameter semantics since there are none to describe.

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' and identifies the precise resource 'current MCP platform and adapter versions', clearly distinguishing it from sibling tools like authenticate or connect. It leaves no ambiguity about what the tool does.

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 information but does not explicitly state when to prefer this tool over alternatives. There are no exclusion criteria or when-not-to-use guidance, so it falls at the 'implied usage' level.

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 and destructiveHint=false, so the safety profile is known. The description adds value by detailing what is returned, but it does not disclose additional behavioral nuances such as data freshness, potential errors, or whether the information is cached. Overall, the description is consistent with annotations and provides minimal extra transparency.

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 lists the main result components without redundancy. Every phrase adds meaning, making it efficient and easy to parse.

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 there is no output schema, the description successfully conveys what the tool returns: installed MCPs, their connection status, connected accounts, and catalog tool counts. The tool's complexity is low, and the description covers all necessary context for a user to understand the tool's purpose and output.

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; therefore the input schema fully covers parameter needs. The description appropriately focuses on the output rather than parameters, matching the baseline for zero-parameter tools.

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' with a clear resource—'current toolkit state'—and enumerates the exact components (installed MCPs, connection status, connected accounts, catalog tool counts). This differentiates it from siblings like show_version and authenticate, 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 implies that this tool is for gaining an overview of the toolkit, but it does not explicitly state when to use it over alternatives such as show_version or marketplace. No exclusions or alternative mentions are provided, so usage 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.