SEFAZ PB: IPVA

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

The description explains the behavior of returning a login link when called with no args and accepting a token for authentication. It doesn't detail side effects, but since there are annotations (idempotentHint=true, readOnlyHint=false), it adds useful context on persistence options that the annotations don't cover.

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 well-structured: it starts with the tool's purpose, then provides clear instructions for setup and usage. Every sentence adds value, and it's compact despite covering a complex authentication flow.

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 complexity (authentication flow with optional token and config setup), the description covers the key aspects: how to log in, what the token is, and how to use it for both permanent and session-only connections. The absence of an output schema is compensated by the description's thoroughness.

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 only defines 'token' as a string with no description. The description adds significant meaning: token is a JWT that the user pastes, and calling without args gives the link. It doesn't list all parameter purposes, but for a single optional parameter it provides enough guidance.

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 an authentication tool for IDE agents, explaining how to log in and use tokens. It distinguishes itself from siblings like 'connect' by focusing on browser-based login and token exchange.

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 use it: first-time setup vs. session-only login, and how to use the optional token parameter. It also provides clear alternatives like adding the token to the server config, making it a strong guideline example.

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 cover readOnly, idempotent, and non-destructive behavior. The description adds value by explaining conditional output fields (authenticated:true, pending[], connect_url) and per-install URLs, providing insight beyond 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?

The description is three concise sentences that front-load the primary purpose and then provide conditional details. No redundancy or 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?

With no parameters, no output schema, and adequate annotations, the description fully covers the tool's behavior for its simplicity. It explains the two primary output states and is sufficient for an agent to understand 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 zero parameters, so there is nothing to explain. The description correctly focuses on behavior and outputs, making parameter semantics irrelevant. Baseline of 4 applies due to no 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?

Clearly states the tool returns connection status and URLs, and elaborates on the two main output scenarios (all connected vs. missing credentials). This distinguishes it from siblings like authenticate or show_version by focusing on status retrieval.

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 use cases (check connection status) through its behavior explanation, but does not explicitly contrast with alternatives like authenticate. It gives clear context for when the tool would be relevant.

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. It discloses that invoke runs a one-off tool without adding it to the toolkit, that writes require owner/admin, that auth failures return connect links, and that payment issues return top-up links. This gives substantial behavioral context beyond the schema and 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 dense but generally earns its length; it front-loads the core flow and adds key permissions and nested feature coverage. However, it reads as one long paragraph and would be more scannable with bullets or action-grouping.

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?

Considering the very high complexity (23 params, 14+ actions, multi-part catalog, prompt library), the description is unusually complete. It covers main flows, permissions, physical side-effects, auth/payment outcomes, and fallback links. It omits some niche actions and parameters like `resume`, `immediate`, and cancellation detail, but still gives a strong model for deciding when and how to use the marketplace.

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 carry heavy weight. It usefully explains the action flow and connects some parameters to behavior (action, mcp_id, tool_id, prompt variables), but it leaves many parameters such as arguments, immediate, resume, cancel_reason, and tier_slug without any semantic clarification.

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 starts with a clear definition: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It then explains the core flow and distinct capability areas, which makes the tool's purpose and scope unambiguous and separates 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 provides explicit when-to-use guidance: search to discover, describe to inspect, invoke to run, install only for permanent use, and list_tools for callable tools. It also calls out alternatives and special cases like 'prefer invoke' over install and separates prompt-library actions from MCP 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 already indicate non-readonly, non-destructive, and idempotent behavior. The description adds only the 'conversation array for reproduction' detail, not additional behavioral consequences like data transmission, storage, or external effects of submitting a report.

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 short sentences, front-loaded with purpose followed by one actionable usage detail. Every sentence contributes value 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?

For a simple 3-parameter reporting tool, the description provides core purpose and a key usage note. However, it leaves the 'context' parameter unexplored and does not explain the submission side effects, so it is minimally complete but not comprehensive.

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% and the description only explains the 'conversation' parameter, clarifying it should contain recent messages for reproduction. 'message' and 'context' remain unexplained, leaving most parameters ambiguous despite the low schema 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 uses an explicit verb ('Report') and identifies specific purposes: bugs, missing features, or feedback. This clearly distinguishes it from the unrelated sibling tools like authenticate, show_version, and sefaz_pb_ipva_consultar.

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 first sentence clearly states when to use the tool: when reporting a bug, missing feature, or sending feedback. It instructs to include the conversation array for reproduction, but it does not explicitly name alternatives or state exclusions.

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 readOnly, non-destructive, idempotent. The description adds valuable context: hosting, payment model, official source, non-confidential data, and LGPD responsibilities. This goes beyond the annotations by explaining the operational and legal boundaries.

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 with the core purpose. It includes extra context (payment, legal) without excessive verbosity. Could be slightly tighter but overall efficient.

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?

Tool has no output schema distance, so description should explain expected return values. It mentions it consults official sources but not what data is returned (e.g., IPVA amount, status, etc.). Also lacks parameter guidance footnote. Still, the basic context of 'IPVA consultation' is present, making it partially 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?

Schema has 4 parameters (cpf, cnpj, placa, renavam) with zero description coverage. The description does not mention any parameters or their meaning, leaving the agent to infer. While placa and renavam are somewhat self-explanatory in the IPVA context, the optional cpf/cnpj filters are unexplained.

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's a consultation (consulta) of IPVA data from SEFAZ PB, a specific official source. It also distinguishes from sibling tools by naming the exact resource and scope, making the purpose unambiguous.

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 context that the tool uses official sources and requires prepaid credits, which implies when to use it (paid data queries). It doesn't explicitly contrast with alternatives, but sibling tools are generic platform functions, so the context is clear. No misleading guidance.

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, covering the safety profile. The description adds the context that it reports platform and adapter versions, but doesn't disclose return format, whether connectivity is required, or any other runtime behavior. It's consistent but not richly informative.

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?

A single, front-loaded sentence with no filler. Every word contributes to the meaning, and the structure is ideal for quick agent comprehension.

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-argument, no-output-schema tool, the description is appropriately complete. It names the exact subject (platform and adapter versions), and the annotations cover safety aspects. No additional context is needed for correct 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 schema has zero parameters, so schema description coverage is trivially 100%. Per the baseline for 0-parameter tools, the description need not add parameter semantics; it simply describes the action clearly without needing to explain inputs.

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 action ('Show') and the specific resource (current MCP platform and adapter versions), making it instantly distinguishable from sibling tools like authenticate, connect, and marketplace. The verb+resource combination is specific and unambiguous.

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 no guidance on when to use this tool versus alternatives, no exclusions, and no mention of prerequisites. While the purpose implies usage scenarios, there is no explicit 'use when...' or comparison with 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds valuable context by enumerating what the state includes (installed MCPs, connection statuses, accounts, catalog tool counts), making the behavior transparent without contradicting 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?

A single sentence that fully explains the purpose and the specific data returned, with no redundant words. Perfectly front-loaded and efficient.

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, this description provides complete context—it enumerates the four key aspects of the state returned. With annotations confirming safety and no output schema, the description suffices for the 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 zero parameters, so the description need not explain parameter semantics. The baseline for 0 params is 4, and the description correctly focuses on the output rather than inputs.

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, specifying the exact components: installed MCPs, connection status, connected accounts, and catalog tool counts. It uses a specific verb ('Returns') with a concrete resource ('toolkit state') and details that distinguish it from sibling tools like authenticate or connect.

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 checking the toolkit state but does not explicitly state when to use versus alternatives. Given it's a read-only informational tool with no side effects, the context is clear enough, but it lacks explicit exclusions or mention of alternative tools for related actions.

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