SEFAZ MG: Simulação de Parcelamento IPVA

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

Annotations are minimal (readOnlyHint=false, idempotentHint=true, destructiveHint=false), so description carries the burden. It discloses behavior: with token, it logs in; without, it returns a link. It also explains the permanent vs session-only distinction. 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 front-loaded with purpose, then covers best practice and alternatives in a compact, well-structured manner. Each sentence adds value: purpose, permanent config, session login. No redundant or filler 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 it's a simple authentication tool with no output schema and one optional parameter, the description covers both usage modes and setup guidance. It lacks details on error handling or post-auth state, but that's not essential for this tool's complexity.

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 has one optional string 'token' with 0% description coverage, so description must explain it. It does: token is the JWT the user pastes, and calling without args returns the login link. This fully clarifies the parameter's role and optionality.

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: authenticate for MCP.AI in IDE agents via browser login and token. It specifies the exact action (log in, copy access token) and distinguishes from unrelated siblings like marketplace or report_bug by focusing on 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?

It provides clear usage context: best to add token to config for permanent access, or paste for session-only login. It explains when to call with token vs no args. Though it doesn't explicitly mention alternatives for authentication, the sibling list suggests no other auth tool, so guidance is adequate.

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 declare readOnlyHint and idempotentHint, and the description adds context about what is returned in different states (authenticated:true vs. connect_url). This goes beyond the annotations and properly conveys the tool's behavior without 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 tight sentences, front-loaded with the purpose, then the conditional outcomes. 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 status tool with no output schema, the description fully covers the two possible outcomes (authenticated vs. missing credentials) and is adequately complete. Annotations cover safety traits.

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 description doesn't need to explain parameter semantics. The baseline of 4 applies because the schema already covers the empty parameter set, and the description adds no unnecessary detail.

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 returns connection status and URLs, and distinguishes between the two states (authenticated vs. missing credentials). This is specific and distinct from 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 implies its use for checking connection status but does not explicitly say when to use it versus alternatives. It doesn't mention when not to use it or point to other tools like authenticate for credential handling.

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 reveals key behavioral traits beyond the sparse annotations: that invoke runs tools even when not installed (one-off, no toolkit bloat), that it returns a connect link for missing credentials or a checkout link for empty wallet (followed by retry), and that writes require workspace owner/admin. These details are not present in 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?

While longer than typical descriptions, it is logically organized and every sentence adds critical operational context: core flow, permissions, payment/connect links, and prompt library. It front-loads the purpose and efficiently handles edge cases without 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 tool's breadth as a multi-action marketplace plus prompt library, the description is remarkably complete. It covers the main flow, one-off execution behavior, auth/payment fallbacks, permission requirements, and the distinction between permanent install and temporary invoke, even hinting at return values in the absence of an output schema.

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 the action enum semantics and the search/describe/invoke argument flow (mcp_id, tool_id). However, many of the 23 parameters (e.g., immediate, tier_slug, prompt_vars, report_context) are left undocumented, so the agent must infer their meaning from names and context.

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 that this is the 'official mcp.ai marketplace' and explains its dual role as catalog and execution engine. It explicitly distinguishes from siblings by covering capability requests and the core search/describe/invoke 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?

It offers explicit usage guidance, such as 'prefer invoke for a single/occasional use' versus 'use install only to make an MCP PERMANENT'. It also explains the credential/payment link flow with a retry instruction, and distinguishes list_tools, report_bug, request_mcp, and the prompt library actions.

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 indicate readOnlyHint=false, destructiveHint=false, and idempotentHint=true, covering some behavioral aspects. The description adds the instruction to include the conversation array, which is more about usage than behavior. It does not disclose what happens after reporting (e.g., where the data goes, persistence), but since annotations already reveal it is a non-read, non-destructive operation, the description does not need to repeat those. It adds minimal extra context, so a 3 is appropriate.

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 exceptionally concise—two sentences, each earning its place. The first states the purpose, and the second gives a critical usage instruction. There is no redundancy or filler, making it easy for an agent 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?

The tool is simple with no output schema, but the description still lacks information about expected outcomes or side effects. It does not mention what happens after reporting, any confirmation, or error conditions. Annotations provide some behavioral context but not completeness. The instruction to include the conversation array is useful, but for a tool that likely sends data externally, more context about the action's consequences would be 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?

Schema description coverage is 0%, so the description must compensate. The description explicitly mentions the 'conversation' parameter ('Include the conversation array with recent messages'), which adds meaning beyond the schema's default value. However, it does not explain 'message' or 'context' beyond the obvious. Given the low coverage and only partial elucidation, the description falls short of adequately documenting all 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 report a bug, missing feature, or send feedback. The verb 'Report' and resources ('bug, missing feature, feedback') are specific enough to distinguish it from sibling tools like 'authenticate' or 'sefaz_mg_simulacao_ipva_consultar'. However, it does not explicitly contrast with alternatives, so it falls short of a 5.

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 an operational guideline: 'Include the conversation array with recent messages for reproduction.' This tells the agent how to use the tool effectively but does not specify when to use this tool versus alternatives or under what circumstances it should be preferred. The usage context is implied rather than explicit.

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 valuable context: it is hosted by the platform, requires no platform credentials, is paid per query with prepaid credit, and clarifies data privacy (LGPD) responsibilities. This goes beyond annotations and provides useful behavioral 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 paragraph with several pieces of information, but it is somewhat dense and mixes purpose, hosting details, payment, and legal disclaimers. It is not front-loaded with the most critical usage info; the core purpose is stated first, but the additional details could be more concise. It earns a middle score for being informative but not optimally 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 has 4 parameters, no output schema, and no parameter descriptions, the description should provide more operational details (e.g., what inputs are needed, what the simulation returns). It covers the data source and legal aspects but lacks specifics on how to use the parameters or what the response contains. This is a moderate gap for a tool with such sparse schema information.

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 for parameter meaning. However, the description does not explain any of the four parameters (cpf, cnpj, renavam, parcelas). It only mentions the tool's purpose, leaving the agent to infer that renavam is required and parcelas relates to installment simulation. This is insufficient given the lack of schema descriptions.

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 'Simulação de Parcelamento IPVA' (IPVA installment simulation) for SEFAZ MG, using an official source. It distinguishes itself from generic tools by specifying the state (MG) and the specific tax (IPVA), though it doesn't explicitly contrast with sibling tools (which are mostly unrelated).

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 consulting official Brazilian sources and mentions payment via prepaid credits, but it does not explicitly state when to use this tool versus alternatives or provide exclusions. The context of 'consulta em fonte oficial' and 'pague por consulta' gives some guidance, but it lacks clear when-to-use/when-not-to-use instructions.

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 annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful scope ('platform and adapter versions') but does not describe the response structure, pagination implications, or other behavioral 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 a single, front-loaded sentence with no filler. Every word contributes to understanding the tool's purpose.

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 no-parameter, read-only, idempotent version-checking tool, the description is sufficient for an agent to decide to invoke it. The absence of an output schema is not a major issue here because the return concept is obvious, though a short note on the exact response shape could push it higher.

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 schema already fully captures everything needed. An explanation in the description would add little to no value.

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 clear verb ('Show') and a specific resource ('current MCP platform and adapter versions'), so the tool's purpose is unambiguous. It does not explicitly distinguish it from the sibling 'toolkit_info', so it falls short of full differentiation.

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?

Since this is a simple version-lookup tool, the usage is implied: call it when you need version information. However, there is no explicit guidance about when to prefer it over alternatives like 'toolkit_info' or what preconditions might exist.

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 idempotentHint=true, so the description does not need to restate these. However, it adds meaningful detail about what 'toolkit state' entails (MCPs, connection status, accounts, catalog counts), which provides value beyond the annotations. It could have mentioned that no side effects occur, but the readOnly hint covers that.

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 efficiently conveys the tool's purpose and return value with a colon-separated list. Every clause adds value, and there is no redundant or filler 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?

For a read-only informational tool with no parameters and no output schema, the description provides a complete and accurate summary of what the tool does and what it returns. Sibling tools are distinct, and the description leaves no critical gaps for an agent to resolve.

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 description coverage is vacuously 100% (no schema descriptions needed). The description fully compensates for the lack of parameters by explaining what the response will contain, which aligns with the baseline of 4 for parameterless 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 a specific verb ('Returns') and clearly identifies the resource ('current toolkit state'), then lists the exact components included (installed MCPs, connection status, accounts, catalog tool counts). This makes the tool's purpose unambiguous and distinguishes it from sibling tools like 'connect' or 'marketplace', which serve different functions.

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 obvious when to use this tool - whenever one needs to inspect the overall toolkit state. It doesn't explicitly mention when not to use it or name alternatives, but given the sibling tools are functionally distinct (e.g., 'authenticate', 'report_bug'), the usage context is clear without explicit exclusions.

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