SEFAZ: PR

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

The description adds context beyond annotations by explaining the two operation modes (permanent vs session-only) and the link retrieval behavior. It does not contradict the idempotentHint=true annotation, and while it doesn't discuss failure scenarios or token validity, the annotations already declare it non-destructive and safe.

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, front-loaded with the tool's core purpose, and efficiently covers all necessary usage details in a few sentences. No redundant information; every sentence serves a 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?

The tool is simple (one optional param, no output schema), and the description provides complete guidance for both invocation patterns, including the trade-off between permanent and session login. It covers everything an agent would need to select and use the tool 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?

With schema description coverage at 0% and only one optional parameter 'token', the description fully compensates by specifying that 'token' is a JWT and explaining when to provide it (after user pastes) versus when to omit it (to get the link). This adds meaningful 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 states the tool's purpose: authentication for MCP.AI IDE agents via browser login and token usage. It specifies the action (log in, copy token) and resource (access token), and distinguishes it from sibling tools by focusing on the authentication 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?

The description provides explicit usage guidance: for permanent connections it recommends configuring the token as a header, while for session-only it instructs to call with a token or with no arguments to get a link. It clearly explains when to use each method and the input for each scenario.

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. The description adds valuable behavioral detail about the two possible return states (authenticated:true with empty pending[] vs connect_url and per-install URLs), exceeding what annotations alone provide, though it does not cover error cases or rate limits.

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 every part contributes meaning. No wasted words or repetition.

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 fully explains the two possible outcomes and what fields/URLs to expect, making it complete for a simple zero-parameter status-checking 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 input schema is empty. Baseline for 0 params is 4; the description correctly avoids adding unnecessary parameter information.

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 and resource ('Returns connection status and URLs') and then clarifies two distinct outcomes, clearly distinguishing this tool from siblings like 'authenticate' or 'toolkit_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 provides clear context about the conditions under which different results are returned, implying it is for checking connection status, but it does not explicitly state when to use it versus alternatives, nor does it mention 'authenticate' or any exclusion 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?

The description goes well beyond the annotations by explaining that invoke runs tools even when not installed, does not bloat the toolkit, returns connect/checkout links for missing credentials or empty wallet, and flags installed_in_toolkit versus installed_in_workspace. It also calls out that writes require workspace owner/admin. This provides strong behavioral transparency with no contradictions against the raw 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 long, but it earns its length because the tool packages many actions and two workflows (MCP execution and prompt library). It is front-loaded with the core flow and uses whitespace-free but clearly segmented sentences; a few more line breaks or lists could improve readability, but there is little 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 23 parameters and 14+ enum actions, the description covers most major workflow branches: search, describe, invoke, install, list_tools, subscribe/cancel, report_bug, request_mcp, and all prompt library features. It omits explicit detail on 'resume', several individual parameters, and exact response shapes, but since there is no output schema, those omissions leave some ambiguity for an agent operating fully autonomously.

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 do the heavy lifting for parameter meaning. It does explain the core action-to-tool_id flow and implies usage of search, describe, invoke, install, and prompt parameters, but 23 parameters remain under-explained: fields like immediate, tier_slug, cancel_reason, conversation, and report_context receive no semantics. It is useful but not complete.

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 marketplace as the official mcp.ai catalog and execution layer for MCPs, with specific verbs for each phase of the flow: search discovers, describe profiles, invoke runs, install makes permanent. It is unambiguous about what the tool covers, but it is a multi-purpose umbrella rather than a single focused resource, and it does not explicitly differentiate itself from sibling tools like toolkit_info or report_bug.

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 runs, install only for permanent toolkit integration, and list_tools to see what is callable now. It also covers follow-up behavior after auth/checkout links and notes workspace owner/admin requirements for writes, giving the agent a clear decision path.

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=false, destructiveHint=false, idempotentHint=true, and openWorldHint=false. The description does not contradict these annotations. It adds minimal behavioral context: it implies a reporting action and suggests including conversation for reproduction, but does not disclose side effects, such as whether the report is stored or sent externally. Since annotations cover the safety profile, a score of 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 extremely concise: one sentence, no wasted words. It front-loads the purpose and provides a key usage instruction. It earns a perfect score for conciseness and structure.

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 there is no output schema and the description is the only source of context beyond annotations, it falls short for a tool with 3 parameters. It does not explain the return value, does not specify the format of 'conversation', and does not clarify the meaning of 'context'. The description provides a basic purpose but leaves significant gaps for an agent to use 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?

Schema description coverage is 0% – the description does not explain the 'message', 'conversation', or 'context' parameters. The required 'message' parameter is not described at all, and the 'conversation' parameter's format is only hinted via the description's instruction to 'include the conversation array'. With no parameter details in the description and no coverage in the schema, the description fails to compensate for the complete lack of parameter semantics.

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.' It uses specific verbs ('report', 'send') and identifies the resources (bug, feature, feedback). However, it doesn't explicitly differentiate from siblings, though sibling tools like 'marketplace' or 'show_version' are clearly different. The title 'Report Bug' aligns with the description.

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 context: it is for reporting issues and includes instructions to 'Include the conversation array with recent messages for reproduction.' However, it does not explicitly state when not to use this tool or mention alternatives among siblings. The guidance is clear but not comprehensive.

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 readOnly, idempotent, and non-destructive behavior. The description adds valuable context beyond that: prepaid per-query billing, no platform credentials required, the data is not confidential, and the client is the LGPD data controller. No contradiction with the annotations exists.

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 the core purpose but contains some redundancy, such as mentioning 'consulta em fonte oficial' and later 'consulta informação de fontes e órgãos oficiais brasileiros.' The LGPD sentence is relevant context but adds length; overall it is reasonably compact but not tightly edited.

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 covers billing, credentials, and data sensitivity, but it is incomplete for actual invocation: it does not explain what the response contains, whether one of 'ie'/'cnpj' is required, or how the parameters are meant to be used. With no output schema and minimal parameter information, the description leaves important operational gaps.

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 contains two parameters with no descriptions and 0% schema_description_coverage. The tool description does not compensate by explaining that 'ie' likely means Inscrição Estadual or how the parameters relate to each other. This is a significant gap for an agent trying to select and fill parameters correctly.

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 resource and action: consulting official SEFAZ PR sources. It distinguishes itself from generic sibling tools (authenticate, marketplace, etc.) by naming the specific government tax entity and official-source nature. However, it does not explicitly state what kind of data is returned (e.g., tax registration status), leaving slight ambiguity.

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 usage context: no platform credentials are needed, it is a prepaid per-query service, and the data is non-confidential public information with LGPD responsibilities. However, it gives no explicit guidance on when to use this tool versus alternatives, nor does it address the choice between the 'ie' and 'cnpj' parameters.

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 adds context by specifying that it returns platform and adapter version information, which goes beyond the annotations and clarifies what the readable result contains.

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 or redundancy. Every word adds meaning, clearly stating the tool's purpose and scope.

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, zero-parameter, read-only version inspection tool with comprehensive annotations, this description is complete. No output schema is present, but the description adequately conveys what the tool reports without needing to explain return structures.

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 completely covers parameter semantics. The description correctly adds no unnecessary parameter detail; baseline 4 applies 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 uses a specific verb ('Show') and clearly identifies the resource: current MCP platform and adapter versions. This distinguishes it from sibling tools like authenticate, connect, or toolkit_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 intended use is implied by the tool's name and description—call it when version information is needed—but no explicit guidance or alternatives are mentioned. It does not say when not to use it or compare it to related tools like toolkit_info.

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 indicate read-only, idempotent, and non-destructive behavior. The description adds minimal extra transparency, merely restating the read-like nature without going beyond the annotated traits.

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, compact sentence that conveys all necessary information without redundancy or fluff. It is well-structured and directly to the point.

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 no parameters and no output schema, the description fully specifies what the tool returns (installed MCPs, connection status, accounts, catalog tools). This is sufficient for an agent to understand the tool's purpose and expected output.

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?

There are zero parameters, so the baseline is 4. The description does not need to explain parameters, and it does not introduce any confusion about them.

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 the current toolkit state and enumerates the specific contents (installed MCPs, connection status, accounts, catalog tools). It uses a specific verb and resource, distinguishing it from sibling 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 does not provide explicit guidance on when to use this tool versus alternatives. No alternatives are mentioned, and there is no condition or context for invocation beyond its purpose.

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