SEFAZ MG: Consulta Parcelamento

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

Annotations indicate idempotent (true) and readOnlyHint (false). The description adds context about permanent vs. session-only connections and how the token is used. It does not elaborate on side effects, but the annotations already cover safety aspects. No contradictions found.

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 (two sentences) and well-structured: it states the purpose, gives the best practice, and explains the alternative. It avoids unnecessary detail and is efficiently front-loaded.

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 tool with a single optional parameter and no output schema, the description is complete: it covers both invocation modes, the token source, and the persistence model. No critical context is missing for an agent to correctly select and call this 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 schema has one optional 'token' parameter with no description (0% coverage). The description compensates fully by explaining that it expects a JWT parsed from the user's browser login, and that calling without arguments yields a login link. This adds significant semantic meaning beyond the 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 authentication for MCP.AI IDE agents, explaining the login process and two authentication methods. It is specific and distinguishes from siblings by focusing on token-based login, unlike 'connect' which likely serves a different 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?

It provides clear instructions on when to use the tool and the preferred method (adding to config for permanent access) versus session-specific login. It explains the call patterns but does not explicitly mention alternatives like 'connect' or why not to use them.

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 cover the read-only, idempotent, non-destructive nature of the operation. The description adds valuable conditional behavior: it states that authenticated:true with an empty pending array occurs when all providers are connected, and that missing credentials yield a connect_url and per-install URLs. This aligns with annotations and enriches the operational model.

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, and every sentence contributes useful conditional details. It avoids repetition, filler, or visual noise.

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?

With no parameters, a simple output model, and strong annotations, this description is complete enough for an agent to understand the tool. It explains both the success state and the missing-credentials state, which are the main scenarios an agent would need to anticipate.

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 no parameters, so parameter-level documentation is unnecessary. The description adequately focuses on behavior rather than parameters, and the zero-parameter nature of the tool makes this point moot.

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: returning connection status and URLs. It also distinguishes this tool from likely siblings by contrasting a state-checking tool (connect) against an auth-action tool (authenticate), especially through its conditional descriptions of successful and missing-credential states.

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 the tool by explaining what it returns in different connection states, but it does not explicitly say when to use connect versus an alternative like authenticate or marketplace. Clear context is provided, but there is no direct exclusion or comparison to sibling tools.

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 goes well beyond the boolean annotations by stating that invoke runs one-off even when the MCP is not installed, that auth failures produce connect links, that payment failures produce checkout/retry links, and that sensitive write actions require owner/admin. No contradiction with the provided annotations was found.

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 long but well organized: the core MCP flow is presented first, then install/permission logic, billing, auxiliary actions, and the separate prompt-library feature. The density is mostly justified, though a sentence is extremely dense because of the broad function surface.

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 such a large multi-action tool with no output schema and minimal structured annotations, this description is unusually complete. It covers the search-discover-invoke path, temporary vs permanent installation, authentication and payment edge cases, permissions, troubleshooting, and a secondary prompt library feature.

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 23 parameters and 0% schema description coverage, the description does a strong job at explaining action values, mcp_id vs tool_id workflows, arguments, prompt variables, and the prompt-library flow. A few optional parameters like immediate, tier_slug, conversation, and report_context remain under-documented, which prevents a perfect score.

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 defines marketplace as both the mcp.ai catalog and the execution layer for MCP tools. It gives a specific discovery flow from search to describe to invoke, and it enriches the noun-like tool name with concrete operational meaning.

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 explains when to prefer invoke over install, when to use subscribe/cancel, list_tools, report_bug, request_mcp, and the prompt-library actions. This makes choosing between actions inside the tool and avoiding a bloated toolkit highly actionable.

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 the tool is not read-only and not destructive. The description adds no further detail about side effects, authentication, or rate limits. It is minimal but consistent 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 concise and front-loaded, consisting of a single sentence that clearly communicates the action without unnecessary 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?

Given the tool's low complexity and lack of output schema, the description covers the main purpose adequately. However, it omits parameter details and does not address any potential side effects, making it minimally 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 schema provides no descriptions for parameters, so the description must compensate. It only hints at the 'conversation' parameter, leaving 'context' and 'message' unexplained. This is insufficient for 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: reporting bugs, missing features, or feedback. It is specific and distinct, using an explicit verb and object.

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 mention when to use this tool versus alternatives, nor does it provide any guidance on when not to use it. It simply states the action without 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?

Beyond the readOnly/idempotent annotations, the description discloses cost implications (pay per query), absence of platform credentials, data sensitivity (non-confidential), and LGPD compliance responsibilities. This provides a clear behavioral picture.

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 verbose and repetitive, containing redundant legal disclaimers (e.g., mentioning non-confidential data twice). While it conveys the core purpose, it could be streamlined to a more concise format without losing essential 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?

The description lacks critical usage details: it does not specify whether cpf or cnpj is required, the allowed combination, or any input format validation. It also fails to describe the expected output or error responses. Given the simple schema, this incompleteness hinders practical use.

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 lists cpf and cnpj but provides no descriptions. The description does not explain these parameters, their significance, or whether at least one is required. It relies entirely on implicit knowledge of Brazilian tax IDs, which is insufficient for a robust API description.

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: consulting installment (parcelamento) data from SEFAZ MG, a specific official Brazilian source. It distinguishes itself from the sibling tools (authenticate, connect, marketplace, etc.) by its precise resource and function.

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 usage context: it is a paid query (prepaid credits), does not require platform credentials, and accesses non-confidential official data. It implies when to use it (for checking installment status) but does not explicitly contrast with alternatives, which are unrelated in this case.

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 does not contradict these and adds no extra context, but the existing annotations are sufficient for transparency. The bar is lowered due to annotations, so a score of 4 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 a single, clear sentence with no unnecessary words. It is concise 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 simplicity of the tool (no parameters, no output schema), the description is complete. It explains what the tool does without additional detail being necessary. The absence of an output schema means no return value explanation 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 parameter semantics are not applicable. Per rubric, zero parameters receive a baseline score of 4.

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: displaying the current MCP platform and adapter versions. It is specific and unambiguous, and it distinguishes from sibling tools which handle different tasks (authentication, marketplace, etc.).

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 provide any guidance on when to use this tool versus alternatives. It only states what it does, without mentioning potential use cases, prerequisites, or situations where other tools might be more appropriate.

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 behavioral context by enumerating what the returned state includes, 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?

The description is a single, front-loaded sentence that lists the key output components with no filler or redundancy. Every phrase contributes meaningful 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 parameterless, read-only introspection tool, the description fully covers what the agent needs to know: what the tool returns and at what granularity. No output schema exists, so the description's enumeration of return contents 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?

The tool has zero parameters, so there is no parameter burden for the description to carry. The baseline of 4 applies because the description appropriately focuses entirely on the tool's output rather than 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 clearly identifies the resource ('current toolkit state') and the exact contents returned: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from sibling tools like show_version and 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 clearly implies when to use the tool: whenever the agent needs an overview of the toolkit's current state. It does not explicitly name alternatives or exclusions, but the context is clear enough for a read-only introspection tool.

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