SEFAZ MA: NFC-e

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

It discloses the session/permanent distinction, the optional token parameter, and the expected flow (no args returns link, token authenticates session). Annotations only provide hints; the description adds meaningful behavioral context beyond those.

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 packs useful information but is somewhat dense and includes audience-specific framing ('MCP.AI for IDE agents') that could be separate. All sentences earn their place, but it could be tightened without losing clarity.

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 there is no output schema, the description does enough by explaining the link-generation behavior and token-input flow. It does not specify the exact response structure or failure cases, but for a one-parameter authentication tool this is reasonably 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 only declares a generic optional string token with zero description coverage. The description adds the crucial semantics that the token is a JWT and demonstrates exactly when to pass it versus omit it.

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 flow for MCP.AI in IDE agents, describing login via browser and token handling. It does not explicitly contrast with sibling tools but the distinctive auth scope is evident.

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 actionable guidance: use the permanent config header for long-lived access, or call the tool with no arguments to get a login link, or call with a JWT for session-only login. It implies when each mode is appropriate but does not mention alternative authentication 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 annotations establish read-only, idempotent, non-destructive behavior, and the description adds valuable conditional details: the exact authenticated state, pending array behavior, and returned URLs when credentials are missing. This gives agents enough context to interpret results without over-describing.

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 brief and front-loaded with the core purpose, followed by two compact conditional sentences. Every sentence contributes concrete information and there is no filler or repetition of annotation values.

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 trivial input schema, strong annotations, and simple conceptual scope, the description is sufficient. It explains both relevant outcomes and the key fields in the response even though no output schema is provided, leaving little meaningful ambiguity.

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 already covers this fully, so the description does not need to explain inputs. It instead adds appropriate meaning by describing what the connection-status output represents, which is more useful than 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 clearly states the tool's verb and resource: it 'Returns connection status and URLs.' It distinguishes itself from sibling tools by focusing on status reporting rather than initiating authentication or showing version/toolkit info, and it explicitly describes the success 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 provides clear conditional context: when all providers are connected versus when credentials are missing, it shows what the caller should expect. It does not explicitly name alternative tools like authenticate as the better choice for initiating connections, but it clearly implies this tool is for inspection rather than setup.

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 traits beyond annotations: writes require workspace owner/admin, invoke runs uninstalled MCPs one-off without bloating tool lists, paid MCPs may return a checkout/top-up link requiring retry, and install changes future availability. It covers edge cases around auth and billing even though annotations only give readOnlyHint, idempotentHint, and openWorldHint.

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 rich with information but is a very long, single run-on paragraph with frequent semicolons, making it hard to quickly parse. It is detailed and front-loaded with the central flow, but a listing structure would have improved readability and 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?

Given the large parameter space, the missing output schema, and the broad multi-action nature of the tool, the description covers a lot of ground: the core process, the difference between integrate and invoke, permission requirements, prompt-library workflows, and key response behavior. It is mostly complete for initial orientation, though per-action details like parameter mapping and return types are not explicit.

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 23 parameters with zero descriptions, so the description must compensate. It explains core fields like action, search, describe, tool_id, and arguments, but many parameters remain implicit (e.g., immediate, tier_slug, cancel_reason, conversation, prompt_targets) and require inference or are not described at all.

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 is the official mcp.ai marketplace and explains its two primary roles: catalog discovery and running MCPs. It gives specific actions like search, describe, invoke, install, and prompt-library functions, and differentiates it from sibling tools such as authenticate, connect, and sefaz_ma_nfce_consultar by focusing on catalog and execution flows.

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 search for discovery, describe to inspect, invoke for one-off execution, install only for permanent toolkits, and list_tools to see callable options. It explains the resolution for missing credentials and empty wallets, and contrasts the prompt library workways with MCP-specific 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 cover read-only, destructive, and idempotence hints, and the description adds useful context by advising the inclusion of a conversation array for reproduction. However, it does not disclose what happens after reporting, whether confirmation is returned, or any privacy/implications of sending conversation data.

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 that are efficient and front-loaded: the first gives the purpose, the second gives a key operational instruction. No 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?

For a simple feedback/report tool with no output schema, the description covers the basic purpose and one important usage detail. However, it leaves parameter semantics incomplete and does not state expected outcomes, so it is minimally adequate rather than fully 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 description coverage is 0%, so the description must compensate, but it only mentions the conversation data. The required 'message' field is not explicitly described, 'context' is not explained, and 'conversation' is described as an array while the schema defines it as a string, creating potential confusion.

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 a specific purpose: 'Report a bug, missing feature, or send feedback.' This is a direct verb+resource statement and is well distinguished from sibling tools like authenticate, show_version, or sefaz_ma_nfce_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 description gives clear context for when to use the tool: for bugs, missing features, or feedback. It does not explicitly name alternatives or exclusions, but the purpose statement is specific enough to guide selection.

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 safety characteristics such as readOnly, idempotent, and non-destructive. The description adds meaningful behavioral context: paid per query, no credential requirement, same public data available to citizens, and LGPD-related data responsibilities. No contradiction with 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 compact and front-loaded with the main purpose. It includes some dense clauses about hosting, prepaid credits, and LGPD, but each adds context and does not waste 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?

For a tool with one parameter and no output schema, the description covers the essential aspects enough: purpose, official source, payment mechanism, credential needs, and public data scope. It could still be stronger by describing the return value or invalid-input behavior, but the low complexity keeps the gap minor.

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 description coverage, and the description does not explain the expected format or meaning of the `nfce` parameter. It only restates the domain concept without clarifying whether it is a numeric key, full access key, or another identifier.

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 a query operation for NFC-e data from the official SEFAZ-MA source. It distinguishes the tool from the generic sibling tools by naming the specific resource and source.

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 use: it is an official-source consultation tool, hosted by the platform, requiring prepaid credits and no platform credentials. It does not explicitly mention when not to use it compared to alternatives, but that is less critical given the unrelated 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 and idempotentHint=true. The description adds useful context that both platform and adapter versions are shown, going slightly beyond the annotations. No side effects or further behavioral details are needed for a trivial read operation.

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, focused sentence that directly states what the tool does without any fluff. Every word earns its place, making it a model of 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?

For a tool with no parameters and no output schema, the description sufficiently covers what the tool does. It could mention the exact return format, but that is not necessary for a simple version check, and the tool's simplicity reduces the burden on the description.

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 0 parameters, schema coverage is 100% by default, and the rubric gives a baseline of 4 for 0-param tools. The description adds no parameter info, which is appropriate since there are none to describe.

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 clearly identifies the resource (MCP platform and adapter versions). It is unambiguous and distinguishes itself from sibling tools like 'toolkit_info' by focusing solely on version display.

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 purpose is self-evident and contextually clear for checking versions, but it does not explicitly mention when not to use it or name alternatives. It earns a 4 because the use case is obvious without exclusions or alternatives being necessary.

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, destructiveHint=false, and idempotentHint=true. The description adds value by detailing what the returned state contains (installed MCPs, status, accounts, tool counts), going beyond the annotations. It provides useful context without contradicting the 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 a single, well-structured sentence that front-loads the action ('Returns') and then lists the key components of the state. No filler words, every element contributes to the meaning.

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 no parameters, no output schema, and clear annotations, the description fully explains what the tool provides. It covers the essential information an agent needs to decide to call it and interpret the result.

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 0 parameters, the tool requires no schema explanation. The description doesn't need to add parameter info, and the schema coverage is effectively 100% since there are no params. Baseline 4 applies.

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 exactly what that includes: installed MCPs, connection status, connected accounts, and catalog tool counts. This is a specific verb+resource statement that distinguishes it from sibling tools like authenticate or connect, which are action-oriented.

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 the tool is for reading state but does not explicitly state when to use it versus alternatives (e.g., 'Use this to get an overview' or 'Do not use for actions'). There are no exclusions or mentions of alternative tools, though the read-only nature is clear from context and annotations.

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