SEFAZ BA: IPVA Notificado

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

Annotations already declare idempotentHint=true and destructiveHint=false, so safety profile is known. The description adds that a permanent header connection is non-expiring and session-only is temporary, but doesn't describe return values, side effects (e.g., storing tokens), or failure modes. This is additional context but not rich behavioral disclosure.

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 covering purpose, permanent setup, and session login. Front-loaded with the main action, then branching usage. No redundant phrases; each sentence carries distinct 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 single-optional-param tool with no output schema, the description is fairly complete. It covers authentication flow, permanent vs session, and how to invoke with/without token. Missing error conditions or post-auth response details, but not critical for a simple auth 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?

With 0% schema coverage, the description must compensate. It explains that 'token' is a JWT, is optional (no args allowed), and the two usage modes. However, it doesn't specify token validation, format details beyond JWT, or behavior when token is omitted or invalid. Some meaning added but incomplete.

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: authenticating an IDE agent to MCP.AI by logging in and obtaining an access token. It distinguishes from siblings like 'connect' and 'marketplace' by focusing on authentication flow and token handling.

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: recommended permanent header config, session-only token paste, and no-args to get login link. While it doesn't mention when to use alternative tools, it gives clear step-by-step invocation patterns, which is sufficient given the tool's unique role.

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 conditional behavior: authenticated:true with empty pending[] when fully connected, and connect_url plus per-install URLs when credentials are missing. It does not explain partial connection states or pending[] semantics, but the added context goes 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 core purpose ('Returns connection status and URLs'), and every sentence adds meaningful behavioral detail. 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?

For a zero-parameter, read-only status tool with strong annotations, the description covers the main return states and URLs. It lacks detail on partial connection scenarios and what pending[] represents, but the tool's simplicity and annotation coverage make the description reasonably 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 tool has zero parameters and 100% schema coverage, so there is no parameter semantic burden on the description. The baseline for zero-parameter tools is 4, and the description appropriately focuses on return behavior instead of 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 clearly states the tool returns connection status and URLs, with a specific verb and resource. It is distinguishable from siblings like authenticate by its status-reporting focus, though it does not explicitly name sibling alternatives.

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 tool is used to check connection status, and it describes two relevant states (all connected vs. missing credentials). However, it does not explicitly state when to prefer this tool over authenticate or other siblings, nor does it provide exclusion criteria.

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?

It discloses important non-obvious behaviors beyond annotations: invoking an uninstalled MCP runs it one-off without adding it to the toolkit, installs make tools natively available in future sessions, and install/uninstall/subscribe/cancel require workspace owner/admin. It also covers paid wall and authentication/connect checkouts, which are critical operational details.

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, covering identity, core flow, invoke vs installation, permissions, payments, and prompt-library functionality. It is a long single block and could benefit from bullets or section breaks, but each sentence contributes distinct decision-relevant information, so little is wasted.

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, no output schema, and many behavioral variations, the description is unusually complete: it explains the search flow, return links for payment/auth, permit requirements, installed vs. uninstalled behavior, and the prompt library. It still lacks explicit output expectations for some enumerated actions like resume, and a few parameters are left underspecified.

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 carries the semantic burden. It explains the main action parameters (action, query, mcp_id, tool_id, arguments, prompt_*, cancel_*) and how they fit into the workflow. Some parameters remain unexplained, though, such as limit, immediate, conversation, request_name, and resume, so the coverage is strong but not complete for a 23-parameter dispatcher.

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 by defining the tool as "the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them," which is specific and clearly distinguishes it as the marketplace/runtime owner. It also lays out the core flow: search discovers, describe returns details, invoke runs, and install makes permanent.

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 when-to-use guidance: "prefer invoke for a single/occasional use," "Use install only to make an MCP PERMANENT," and "list_tools lists what is callable right now." It also explains the retry flow when credentials or payment are needed, which is exactly the kind of decision support an agent needs.

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 cover idempotency and non-destructiveness, but the description adds that including the conversation array aids reproduction, which is useful behavioral context. However, it does not describe side effects like report storage or confirmation responses, which would be valuable even with annotations present.

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, front-loaded with the primary purpose and followed by a key usage instruction. Every word earns its place, with no unnecessary 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?

Given the simple schema and lack of output schema, the description reasonably covers purpose and a key input. However, it leaves ambiguity about the conversation parameter's format (string vs array) and does not explain what the tool returns or does after reporting, making it only partially complete for a downstream agent.

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 must compensate. It explicitly explains the conversation parameter ('conversation array with recent messages') and implies the message parameter through 'report a bug.' The context parameter remains unexplained, leaving a gap in full parameter understanding.

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: 'Report a bug, missing feature, or send feedback.' This specific verb+resource combination distinguishes it from siblings like authenticate or show_version, leaving no ambiguity about what it 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?

It provides clear context for when to use the tool by mentioning bug reports, feature requests, and feedback. The instruction to include the conversation array for reproduction gives a concrete usage guideline, though it does not explicitly mention alternatives or exclusions.

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 read-only and idempotent annotations, the description adds details about payment with prepaid credits, lack of platform credentials, and legal compliance (LGPD), providing useful 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 somewhat verbose with legal disclaimers and payment information, but the core purpose is front-loaded and it is not excessively long.

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 lacks explanation of parameters and expected output, leaving significant gaps for a query tool. It does mention official source and payment, but not the result structure or how to use the inputs.

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 does not explain the 'paf' or 'renavam' parameters, adding no semantic meaning beyond the raw schema. The schema has no descriptions, so the tool is uncompensated for this 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 it is a query for IPVA notified status from an official source, distinguishing it from generic 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 does not explicitly state when to use this tool versus alternatives, but the purpose is clear and it mentions payment and official source, offering some contextual 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=true and destructiveHint=false, so the agent knows it is safe. The description adds that it returns version information, but does not specify the format or whether it includes both platform and adapter separately. It provides minimal additional behavioral context beyond annotations, which is acceptable for a simple, non-mutating 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, concise sentence that is entirely informative with no fluff. It is front-loaded with the action 'Show' and resource 'versions'. Perfectly sized for a no-parameter 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, no output schema), the description is mostly complete. It states what it returns (version information). Might benefit from mentioning that it requires no setup or that it is safe to call, but given the annotations cover safety, this is sufficient.

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?

Since the tool has zero parameters, there are no parameter semantics to clarify. The schema coverage is 100% (vacuously), so the description's job is minimal. It adequately names the resource (versions) but doesn't need to say more about 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's purpose: to show current MCP platform and adapter versions. The verb 'Show' and resource 'versions' are specificociative, and it distinguishes from sibling tools by focusing on version information rather than authentication, connection, or marketplace 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 implies usage for checking the current environment versions, which is a clear context. It doesn't explicitly provide exclusions or alternatives, but given the zero-parameter, read-only nature. It is distinguished from siblings by not performing actions like authenticating or connecting, but this is not explicitly stated.

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 establish read-only, non-destructive, idempotent behavior. The description adds valuable context by enumerating the exact state contents returned (installed MCPs, connection status, accounts, catalog tool counts), going beyond the 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?

A single, well-paced sentence that front-loads the core purpose and then lists the contained information. Every word earns its place; no filler or repetition exists.

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, annotation-rich state inspection tool with no output schema, this description adequately communicates what the returned state will include. The tool's simplicity means the description is sufficiently complete for selection and invocation.

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 the schema confirms no properties. The baseline for no-parameter tools is therefore appropriate at 4; the description correctly communicates that the tool returns state without requiring input.

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 starts with a strong verb ('Returns') and the resource ('current toolkit state'), then specifies exact content: installed MCPs, connection status, accounts, and catalog tool counts. This clearly distinguishes it from siblings like show_version, authenticate, and 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 clearly implies this is the introspection/status tool for the toolkit, which gives context on when to use it. However, it does not explicitly state when not to use it or compare it with siblings like show_version, so it falls short of fully explicit guidance.

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