SEFAZ PI: IPVA

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

The description discloses the outcome of the login (permanent versus session-only) and that a token is involved. It does not explicitly state side effects like state changes or failure behavior, but overall behavior is implied clearly enough. The idempotentHint is consistent with the description.

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 the 'Best:' and 'Or' structure, but it is still well-organized and free of unnecessary fluff. It effectively conveys both authentication methods without being overly 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?

Given the tool's purpose and lack of output schema, the description covers all necessary context: how to authenticate, the two modes, and what to do with the token. It is complete for an authentication 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 sole parameter 'token' is thoroughly explained: it is an optional JWT that can be passed for a session-only login, and when omitted, the tool provides the authentication link. This adds meaning beyond 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 states the tool's purpose: authenticating for MCP.AI in IDE agents. It explains the login process and distinguishes between permanent and session-based authentication, making it easy to understand what the tool 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?

The description explicitly explains when to use the tool—when needing to authenticate—and provides two clear usage paths: adding the token to config for permanent access, or passing the token for a session-only login. It also instructs to call with no args to get the link.

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, indicating safe, non-mutating behavior. The description adds value by specifying the actual response structure (authenticated flag, pending array, connect_urls) and differentiates between all-connected vs missing-credentials states. It does not add heavy behavioral warnings but supplements the annotation well.

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, only two sentences. It is well-structured, front-loading the primary purpose and then providing conditional details. Every sentence 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?

Given that this is a simple status-check tool with zero parameters and no output schema, the description is adequate. It explains the key states (authenticated and pending). It could theoretically explain the structure of connect_url or the 'pending' array in more detail, but the description is complete enough for an agent to know what to expect.

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 0 parameters, and schema coverage is 100% (meaning there are no parameters to document). The description explains what the response contains, which serves as the only necessary semantics. It doesn't need to explain parameters, and the description adds meaningful output context 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 returns connection status and URLs. It specifies the exact conditions for different states (authenticated:true when all providers connected, connect_url when credentials missing). It distinguishes itself from siblings like 'authenticate' by focusing on status inspection rather than authentication 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: use this tool to check connection status. It explains what to expect in different scenarios, which guides when to call it (e.g., to verify setup). However, it does not explicitly state when not to use it or mention alternatives, but the context is clear enough given the 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 discloses important behavioral details beyond annotations: invoke works even when the MCP is not installed (one-off execution without bloating the tool list), returns a connect link if credentials are needed, returns a checkout/top-up link if payment is required, and mentions that writes require owner/admin permissions. This adds rich context not present in the annotations, which merely indicate non-read-only, open-world behavior with no idempotency or destructive hints.

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 information-dense, covering a complex multi-action tool. It is front-loaded with the core purpose and flows logically through discovery, invocation, installation, permissions, and the prompt library. While it is a single paragraph and could be better structured with bullet points, every sentence provides useful detail and earns its place, so it is appropriately sized for the tool's complexity.

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 is highly comprehensive for a tool with 23 parameters and no output schema. It explains all major actions, edge cases (credentials, wallet, one-off execution), permission requirements, and the prompt library subsystem. It even hints at return behaviors (e.g., invoke returns a connect/checkout link, describe returns a profile). This level of detail makes the tool usable without additional 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?

With 23 parameters and 0% schema description coverage, the description must compensate. It does so by explaining the 'action' parameter in depth (search, describe, invoke, install, etc.) and providing context for mcp_id, tool_id, arguments, and prompt-related parameters through the flow descriptions. However, it does not explain all parameters such as limit, query, conversation, prompt_vars, etc. individually, leaving some semantics to be inferred from the schema. It adds significant value but stops short of full coverage.

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 'the official mcp.ai marketplace' and explains it is the catalog of MCPs/tools and the way to run them, covering capability requests. It distinguishes itself from siblings by detailing its multi-action nature (search, describe, invoke, install, prompt library) and explicitly mentioning alternatives like report_bug and request_mcp, which are also siblings.

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: it outlines the core flow (search → describe → invoke), recommends invoking for one-off use versus installing for permanent use, and explains when to use subscribe/cancel, report_bug, request_mcp, and the prompt library actions. It also notes that writes require workspace owner/admin, and explains the difference between installed_in_toolkit vs installed_in_workspace.

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 idempotentHint=true, readOnlyHint=false, and destructiveHint=false, indicating a safe, non-destructive operation that can be retried. The description adds the instruction to include the conversation array, which is more of a parameter guidance than a behavioral trait. It does not contradict annotations, and while it doesn't reveal side effects (e.g., where the report goes), the annotations cover the safety profile adequately.

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: the first states the purpose, the second gives the key usage instruction. It is front-loaded, efficient, and every word earns its place. 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?

For a simple tool with three straightforward parameters, no output schema, and no nested objects, the description covers the essential points: what it does and what to include (conversation array). The 'context' parameter remains unexplained, but it has a default value and is optional, so the overall completeness is good but not perfect.

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. It explains the 'conversation' parameter ('Include the conversation array'), and 'message' is self-explanatory, but the 'context' parameter is not described at all. The instruction about conversation adds value beyond the schema's default value, but the lack of context meaning leaves a 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 the tool's purpose: 'Report a bug, missing feature, or send feedback.' The verb 'Report' combined with the resource 'bug/feature/feedback' is specific and unambiguous, and none of the sibling tools (authenticate, connect, marketplace, etc.) overlap with this function, so differentiation is natural.

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 it: whenever a bug, missing feature, or feedback needs to be submitted. It does not explicitly mention alternatives or when not to use, but given the sibling tools are clearly unrelated, the context is sufficient. It also gives a concrete instruction to 'Include the conversation array with recent messages for reproduction,' which aids 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful context by stating that platform credentials are not needed, each query consumes prepaid credit, and the returned data is non-confidential official information subject to LGPD compliance. This enriches the agent's understanding without contradicting any annotation.

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 logically structured: the core purpose is stated first, followed by details about hosting, payment, data nature, and legal responsibility. Although it omits parameter descriptions, that is more a completeness gap than a conciseness issue; the text itself is tightly written.

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 output schema and no explanation of inputs, the description leaves the agent without essential invocation details. It covers legal and payment context, but lacks parameter semantics and response expectations, so the tool is not fully usable based on this description alone.

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 defines five properties (cpf, cnpj, chassi, renavam, tipo_cotas) with zero schema descriptions, and the description provides no explanation of their meanings or usage. The agent cannot determine what 'tipo_cotas' represents or which identifier to supply, making correct parameter selection nearly impossible.

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 'SEFAZ PI: IPVA, consulta em fonte oficial' – a specific query operation for IPVA data from the Piauí state tax authority. This clearly distinguishes it from sibling platform tools like authenticate, connect, and marketplace, 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 mentions that the tool is hosted by the platform, requires no platform credentials, and is paid per query with prepaid credit, implying use when official IPVA data is needed and credits are available. However, it does not explicitly state when not to use the tool or name alternative query methods, so the guidance remains 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, fully covering the safety profile. The description adds no additional behavioral context, which is acceptable for a trivial read-only operation. The bar is lower with annotations present, and the tool has no side effects to disclose.

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 wasted words. It front-loads the primary action and subject, achieving maximum conciseness.

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 simple, dependency-free tool with no output schema. The description fully captures the tool's purpose and scope. There are no complex behaviors, parameters, or return values to elaborate on, so the description is complete for the 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?

The tool has zero parameters, and schema coverage is 100% (vacuously). Per the rubric, a zero-parameter tool receives a baseline of 4. The description does not need to add parameter semantics, and it does not try to.

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 'Show the current MCP platform and adapter versions' uses a specific verb ('Show') and a specific resource ('current MCP platform and adapter versions'). It clearly distinguishes itself from siblings like authenticate or connect, which are action-oriented, and from toolkit_info, which likely provides broader tooling details.

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 effectively states when to use the tool: when you need to check the current platform and adapter versions. It doesn't explicitly mention when not to use it, but given the tool's simplicity and clear purpose, no exclusion is necessary. The context is unambiguous.

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 supply readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is established. The description adds the output scope (MCPs, connections, accounts, counts), but it does not disclose additional behavioral traits such as data freshness, potential sensitive-info exposure, or lack of authentication requirements.

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 all returned information without any filler. Every element contributes to understanding the tool's output, making it both concise and 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?

For a zero-parameter, read-only info tool, the description adequately specifies the returned content, even without an output schema. It could add a small note about why this information matters or how it fits with related tools, but the current level is sufficient given the simplicity.

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 does not need to explain any. Per the baseline rule for zero-parameter tools, a score of 4 is appropriate.

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 begins with 'Returns the current toolkit state', specifying a clear verb and resource. It then enumerates the precise data points (installed MCPs, connection status, accounts, catalog tool count), which unambiguously distinguishes it from siblings 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 tool's purpose strongly implies when it should be used (to inspect toolkit state), but there is no explicit statement of when to use it over alternatives or any exclusions. Guidance is inferred from the described output rather than directly provided.

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