MPT SC: Certidão Negativa de Feitos

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

The description discloses behavioral details: it can modify server config (permanent) or work session-only, and calling with no args returns a link. It does not mention all side effects, but annotations already cover idempotency and destructiveness.

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 relatively concise, using two sentences to cover both usage modes and the parameter. However, it is slightly wordy with phrases like 'Best:' and 'Or,' but remains clear 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?

Given the tool's simplicity, the description is complete: it explains both authentication flows, the token parameter, and the no-arg call. It does not require additional context for correct usage.

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 one property (token) with no description, but the description explains the token is a JWT and indicates it can be omitted (no args) to get a link. This fully covers the parameter's meaning and usage.

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: authentication for IDE agents. It explains two methods (permanent config and session-only) and provides clear steps, distinguishing it from other 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 gives explicit usage instructions, including when to use permanent vs. session-only login and how to call with or without a token. However, it does not compare with sibling tools or state when not to use it.

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 the tool read-only, idempotent, and non-destructive, so the description does not need to repeat that. It adds useful context about the response format, such as the connect_url and per-install URLs, which goes beyond annotations. No contradictions.

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 then clarifying conditions. Every sentence adds value with 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?

Given the simple nature of the tool (no parameters, no output schema), the description is sufficient to convey behavior. However, it could be more complete by explicitly mentioning the response format includes authenticated boolean and pending array, which it does, but it might also state that no input is 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 tool has no parameters, so the schema covers all parameter semantics (100%). The description does not need to add parameter details and adds value by explaining the output conditions, making it a baseline-plus for a parameterless tool.

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, specifying outcomes for different states (authenticated vs. missing credentials). It differentiates from siblings like authenticate and show_version by focusing on status rather than the act of authenticating or version info.

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, but it does not explicitly state when to use it versus authenticate or other tools. It provides context about what responses mean but lacks direct guidance on when or when not to use it.

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, the description discloses that invoke runs one-off without installing, returns connect/checkout links requiring user action then retry, and that writes need owner/admin. It also covers billing, installed flags, and prompt-library behavior, with no contradiction to 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 dense and front-loaded with the core flow, and every sentence adds information. It is a long single paragraph with mixed-language phrasing ('pontualmente'), so slightly less concise/structured than a bulleted version, but still efficient for a 14-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?

For a high-complexity tool with 23 params, no output schema, and no required params, the description covers the full action surface, auth requirements, billing edge cases, install-vs-invoke semantics, and the prompt library. The only minor gap is not detailing every action-specific parameter, but the core flow and return-link behaviors are sufficiently 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 coverage, the description compensates by explaining action values, tool_id selection, arguments, prompt_vars, prompt_slug, and tier/pricing context. However, several params (resume, immediate, conversation, cancel_reason, report_context, request_details) are left to their schema names, so it doesn't fully cover all 23 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 opens with 'official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them' and then lays out the core search→describe→invoke flow. It clearly distinguishes the tool from siblings by positioning it as the catalog-and-execution hub, not just a single-purpose utility.

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 contrasts invoke vs install ('prefer invoke for a single/occasional use'; 'Use install only to make an MCP PERMANENT'), explains when connect/checkout links appear, and directs request_mcp to 'when nothing fits'. It also states write operations require workspace owner/admin, giving clear when-to-use and 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?

The description adds behavioral details beyond annotations: it is a paid service with pre-paid credit, queries official sources, and clarifies data responsibility under LGPD. These are useful non-obvious traits, though it does not mention potential side effects or failure modes.

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, dense sentence that covers multiple aspects (purpose, payment, data source, privacy) without excessive wordiness. It could be broken into clearer segments, but it is not overly verbose.

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 lacks an output schema, and the description does not explain the return format or possible errors. It also does not specify which parameter is required or optional, leaving significant gaps for a user to understand the tool's full behavior.

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 only parameter names (cpf, cnpj) without any descriptions. The description does not clarify the meaning, requiredness, or validation rules of these parameters, leaving semantic ambiguity.

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: consulting negative certificates from official sources. It is specific about the type of certificate (Certidão Negativa) and distinguishes itself from unrelated sibling tools like authenticate or show_version.

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 some context (payment, data responsibility) but does not explicitly state when to use this tool versus alternatives or when not to use it. It lacks direct guidance on appropriate usage 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 are present (readOnlyHint=false, destructiveHint=false, idempotentHint=true), so the bar is lower. The description adds context about requiring the conversation array for reproduction, which is useful behavioral insight beyond the annotations. No contradiction.

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 concise sentences, front-loaded with the main purpose, no 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?

Given the tool's simplicity堪3 params, one required, no output schema—the description is adequate but not fully complete. It explains the conversation parameter's purpose, but 'context' remains unexplainedholistically. For a simple tool, it's sufficient but not exemplary.

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 coverage is 0%, so description must carry the weight. It explains the conversation parameter's purpose but doesn't explain 'context' or 'message' beyond obvious. The description partially compensates but not fully—message is clear, context is vague, and conversation is explained.

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 a specific purpose: report a bug, missing feature, or send feedback. It uses a strong verb ('report') and identifies the resource (bug/feature/feedback), which distinguishes it 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 gives concrete guidance on when to use (report issues) and how to use (include conversation array). It doesn't explicitly mention alternatives or when not to use, but the purpose is clear enough. Since siblings are unrelated (authentication, version info), no conflict arises.

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. The description is consistent with these and adds no contradiction. Since the tool is trivial, it does not need to add more 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 a single, concise sentence with no unnecessary words. It is front-loaded and contains all necessary information.

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 version-checking tool with no parameters, an output schema, and comprehensive annotations, the description fully suffices. The agent has everything needed to invoke it correctly.

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 there is no semantic gap. Per the rubric, a baseline of 4 is appropriate for tools with no 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 shows the current MCP platform and adapter versions. It uses a specific verb ('Show') and a specific resource, and it is 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 is clear about when to use it, but does not explicitly mention alternatives or exclusions. However, the use case is obvious, so an agent can infer the appropriate 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, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds behavioral context by specifying what state information is returned, which is useful beyond the annotations. It does not mention potential latency or freshness, but for a read-only info tool this is a minor 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 a single, well-structured sentence that front-loads the action and result. It avoids filler, lists all key return items, and earns its place entirely.

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?

There is no output schema, so the description carries the responsibility for describing return content. It does a solid job by listing installed MCPs, connection status, connected accounts, and catalog tool counts. It could mention return formatting or real-time behavior, but for a zero-parameter informational tool, the description is sufficiently complete.

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 parameters, and schema description coverage is 100%, so there is nothing for the description to add about parameters. The baseline for 0-param tools is 4, and the description correctly avoids inventing parameter 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 uses a specific verb ('Returns') and identifies the resource ('current toolkit state'), then enumerates the exact content (installed MCPs, connection status, accounts, catalog tool counts). This makes the tool's purpose unambiguous and clearly distinguishes it from siblings like show_version, which likely reports version details.

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 establishes clear context: the tool is for inspecting the toolkit's state (installed MCPs, statuses, accounts, catalog counts). While it doesn't explicitly name alternative tools for exclusion, the detailed list of contents makes it obvious when this tool is appropriate compared to show_version or authenticate.

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