SEFAZ CE: Certidao de Regularidade

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

Adds meaningful behavioral context beyond annotations: describes the browser login flow, permanent vs session-only behavior, and that no args returns a link. Annotations like idempotentHint are complemented rather than contradicted.

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 and front-loaded with the core action, but the phrasing is slightly run-on and mixes user instructions with tool behavior. Overall every sentence contributes useful 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 one-parameter authentication tool with no output schema, the description covers the main scenarios: browser login, permanent configuration, session-only token, and the no-args link flow. It does not describe response details or error cases, but those are less critical here.

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 the description carries the full burden for the single 'token' parameter. It explains that token is a JWT, that it can be omitted to request a login link, and how it is passed after the user pastes it—far exceeding the bare 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 an authentication mechanism for MCP.AI IDE agents, explaining the browser login/token workflow. It distinguishes itself from siblings by specifying the authentication/token purpose, though it does not explicitly contrast with the 'connect' sibling.

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 clear usage guidance: permanent config via Authorization header vs session-only login by pasting a token, and explains when to call with no args to get a login link. It gives practical alternatives but does not explicitly state when to avoid this tool in favor of a sibling.

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 (read-only, idempotent), the description discloses specific behavioral scenarios: what happens when all providers are connected (authenticated:true, empty pending[]) and when credentials are missing (returns connect_url for toolkit and per-install URLs). This adds transparency about conditional outputs, though it does not cover partial connectivity or error cases.

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, consisting of two clear sentences. It avoids unnecessary detail and is well-structured, presenting the main purpose first followed by conditional behaviors.

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 read-only status tool with no parameters, the description covers the primary output and key conditions. However, it does not address scenarios like partial provider connectivity or other potential edge cases, making it slightly incomplete but still adequate for typical 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 tool has no parameters, so there is nothing to explain. The description does not introduce any implicit parameters, and the schema coverage is complete (100%). Thus, parameter semantics are fully satisfied.

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 is specific and distinguishes it from other tools like 'authenticate' or 'marketplace' by focusing on connectivity and provider status.

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 conditional outcomes (all providers connected vs. missing credentials) but does not explicitly guide when to use this tool versus alternatives. It lacks direct statements like 'use this to check connectivity' or 'do not use if you need to authenticate'.

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 readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false. The description adds meaningful behavioral context: invoke runs tools without installing them or bloating the toolkit, install persists MCPs into the active toolkit, missing credentials yield a connect link, insufficient wallet balance yields a checkout link, and writes require workspace owner/admin. This substantially adds context beyond annotated flags, although it doesn't discuss rate limits or exact failure result shapes.

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 and information-dense, but every sentence earns its place by covering a distinct sub-area: discovery flow, invoke one-off semantics, credential/payment edge cases, install persistence, billing/support paths, workspace permissions, and prompt library. The structure is stream-of-consciousness rather than bullets or numbered flow, so it could be more scannable, but content is not redundant or padded.

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 the tool has an enormous 23-parameter schema with 0% coverage and no output schema, the description does an exceptional job of making the tool usable: it explains the search→describe→invoke core flow, the one-off vs permanent distinction, auth via connect links and payment via checkout links, admin ownership requirements, and prompt library flows. There are always more edge cases that could be enumerated, but this description is substantially complete for a variant-rich marketplace tool with no structured parameter documentation.

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% (the schema has 23 parameters but no per-parameter descriptions), so the description carries the full burden. The text names many parameters (action, limit, query, mcp_id, tool_id, arguments, prompt_* fields, cancel_reason, etc.) and relates them to sub-flows, but it does not explicitly map every named parameter to its type/default/meaning. It covers high-level semantics for important parameters (action=search/describe/install, mcp_id, tool_id, prompt_title/prompt_body/prompt_slug) and improves on an empty schema, earning a 3.

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 this is the official mcp.ai marketplace—the in-platform catalog of every MCP/tool AND the way to run them. It enumerates concrete capability queries (find an MCP that does X, consulta um CPF, is there a tool for Y) and explicitly distinguishes the tool's sub-actions (search/describe/invoke/install/list_tools/subscribe/cancel/report_bug/request_mcp) from sibling tools like authenticate and show_version. The verb-plus-resource structure makes the tool's purpose unmistakable.

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 explicit when-to-use guidance: use `invoke` for one-off/occasional runs even when MCP is not installed, use `install` only to make an MCP permanent, use `search` to discover by intent, `describe` to get a full profile, and `list_tools` to see what is callable right now. It also states credential/payment edge cases (invoke returns connect/checkout links) and warns that writes require workspace owner/admin, which effectively excludes non-admin usage.

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 establish that this is not read-only and not destructive, and the description adds the useful behavioral note to include the conversation array for reproduction. However, it does not disclose what happens after submission or any privacy/retention implications of sending recent messages.

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 concise sentences with no filler. The first states the purpose, the second gives the most important usage detail, so every sentence earns its place.

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 three-parameter tool with no output schema, the description covers purpose and the conversation parameter adequately. It could add what happens after submission, but that is not essential for correctly selecting and calling the 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 0% parameter-description coverage, so the free-text description must compensate. It helpsfully explains the 'conversation' parameter as recent messages for reproduction, but it does not clarify the 'context' parameter, and the required 'message' parameter is only implied by the overall purpose rather than explicitly defined.

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 explicitly states the tool's purpose: report a bug, request a missing feature, or send feedback. It clearly distinguishes itself from the listed sibling tools, none of which handle bug reporting or user feedback.

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 clear context for when to use the tool: when a user reports a bug, asks for a missing feature, or wants to provide feedback. It does not explicitly name alternatives or exclusions, but no competing sibling tool exists, so this is not a significant gap.

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 description does not need to repeat those. It adds valuable context beyond annotations: the payment mechanism (prepaid credit per consultation), the lack of platform credentials, and the LGPD compliance statement about data control. These explain the operational and legal behavior of the tool, complementing the annotations 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?

The description is composed of four sentences, each adding distinct information: purpose, hosting/payment, data source and privacy, and LGPD responsibility. It front-loads the main action (querying the certificate) and keeps additional details brief. No redundant or filler sentences are present, making it appropriately sized for a read-only query 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 simple tool with two parameters and no output schema, the description covers the core purpose, cost, and data governance but omits critical usage details like parameter semantics, response format, or any limitations (e.g., state scope). Since there is no output schema, it should describe what is returned, but it does not. The description is adequate for basic understanding but incomplete for agent guidance on 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 input schema lists only 'cpf' and 'cnpj' with no descriptions, and schema description coverage is 0%. The description does not explain what these parameters represent or how to use them (e.g., which one is needed, if both are acceptable, or if either is required). Since the description must compensate for the lack of schema documentation, this is a significant gap. The tool name and purpose hint at CPF/CNPJ identifiers but do not clarify 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 queries the 'Certidao de Regularidade' (Certificate of Regularity) from SEFAZ CE. It names the specific resource, the official source, and the action ('consulta em fonte oficial'). It distinguishes itself from sibling tools (which are platform-wide utilities like authenticate or connect) by being a domain-specific query.

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 context on usage constraints: it is 'hosted by the platform, without platform credentials', requires prepaid credit per query, and is for official data. However, it does not explicitly state when to use this tool over alternatives or when not to use it. It implies usage for legitimate LGPD-compliant purposes but lacks concrete exclusions or alternative tool references.

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, and the description is consistent with these. However, it adds no extra behavioral context beyond what the annotations provide, such as network implications or output shape.

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 zero filler or repetition. It is front-loaded and conveys the exact purpose without any 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?

This is a zero-parameter, read-only, idempotent information tool. The description fully covers its purpose, and with no parameters and no output schema, there are no additional contextual requirements.

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%, so there is nothing for the description to add. The baseline of 4 applies as no parameter clarification is needed.

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 ('Show') and precisely names the resources ('current MCP platform and adapter versions'). This clearly distinguishes it from sibling tools like authenticate, connect, and marketplace, which have entirely 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?

There is no explicit guidance on when to use this tool versus alternatives, but the straightforward purpose implies using it whenever version information is needed. No exclusions or alternative recommendations are provided, which is acceptable for such a simple utility.

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 value by specifying exactly what the returned state includes (installed MCPs, connection status, accounts, catalog tool counts), which is not present in the annotations or schema. 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 a single sentence that front-loads the primary action ('Returns the current toolkit state') and then enumerates the specific data points. Every word earns its place with no filler 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?

Despite having no output schema, the description sufficiently conveys the return value composition at a high level. It covers the key elements of toolkit state and is likely enough for an agent to decide whether to invoke this tool and interpret its result. Slight additional detail on format could improve it, but it is not necessary for this simple information 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 tool has zero parameters and the schema coverage is 100%, so there is no parameter ambiguity to resolve. The baseline of 4 for a parameterless tool is appropriate; the description does not need to explain parameter meaning.

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 resource ('current toolkit state') and enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly differentiates it from sibling tools like authenticate, connect, or show_version, 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 clearly frames when this tool is appropriate: whenever the agent needs an overview of the toolkit's state. It does not explicitly name alternatives or exclusions, but the context is unambiguous given the sibling tools operate in distinct domains (auth, connectivity, marketplace, bug reporting, version info).

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