SEFAZ MS: NFC-e

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

Annotation says idempotentHint=true and destructiveHint=false. The description adds context about non-expiring vs session-only login, and explains the token flow. It does not contradict annotations and gives useful behavioral details beyond what annotations provide.

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?

One dense sentence delivers all necessary information. It is slightly convoluted with the opening 'MCP.AI for IDE agents' but every clause adds value and it is not redundant.

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?

Covers the two authentication methods, the token parameter, and the link-generating behavior. Since there is no output schema, the description could clarify what the tool returns, but for a simple auth flow the usage is sufficiently 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 zero description coverage, but the description explains the 'token' parameter: what it is (JWT from browser) and that it's optional (omit to get link). It gives an example call, adding 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 to the MCP.AI server for IDE agents. It describes the browser login flow and token submission, and it is distinct from siblings like 'connect' by explicitly focusing on token-based authentication and session/permanent options.

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 explicit usage guidance: recommends adding the token to the server config for a permanent connection, or pasting it for session-only login. Also explains two invocation modes (with/without token). Does not mention alternative sibling tools, but the instructions are clear and actionable.

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, and the description aligns with those. The description adds useful behavioral detail beyond annotations by explaining the two conditional response states around authentication and missing credentials. It does not contradict 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 concise and front-loaded with the core action and output: 'Returns connection status and URLs.' The second sentence adds the conditional behavior without padding, making both sentences earn their 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, parameter-free connector status tool, the description conveys the main output states needed by the agent. It covers the connected case and the missing-credential case, and with no return schema present, still communicates key response semantics. A small improvement would be defining what 'per-install URLs' means, but overall it is adequate.

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 an empty properties object, so schema coverage is 100% by definition. There is no parameter semantic burden for the description to carry, so a baseline 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?

Description states a specific action and result: 'Returns connection status and URLs.' It also distinguishes itself from siblings like `authenticate` by framing this as a status-reporting tool rather than a mutating/auth action, while describing conditional outputs.

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 conditions for the tool's outputs: when all providers are connected it returns authenticated:true and empty pending[], and when credentials are missing it returns connect_url and per-install URLs. This effectively implies when to call it, though it does not explicitly state do not use this when the goal is to perform authentication rather than check status.

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 reveals many non-obvious behaviors beyond the annotations: invoke runs tools without installing or bloating the tool list, returns connect links when credentials are needed and checkout links when wallet balance is empty, and requires owner/admin for writes. It also notes that search/describe flag installed_in_toolkit vs installed_in_workspace. No contradiction with the annotations was 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 long but reasonably front-loaded with a crisp statement and a 'core flow' explanation. It uses clear signposts like 'KEY', 'Use install only...', and 'list_tools lists...' so each segment serves a purpose, though it is still one dense paragraph and would benefit from bullet-like separation of the many modes.

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 complex multi-behavior marketplace tool, the description covers the main categories: discovery, profile inspection, one-off execution, install/uninstall, billing, capabilities like report_bug/request_mcp, and the separate prompt library. It is missing explicit details on a few actions such as resume and does not describe return formats for all actions, but it is reasonably complete for high-level usage.

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 does some high-level compensation: it explains action, tool_id selection, and the general search/describe/invoke flow. However, many parameters such as cancel_reason, conversation, immediate, tier_slug, prompt_vars, and prompt_targets are not described in the prose and cannot be inferred without significant guesswork.

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 that this is the official mcp.ai marketplace: the in-platform catalog of MCPs/tools and the mechanism to run them. It specifies the core flow (search → describe → invoke), distinguishes marketplace actions from list_tools, report_bug, and request_mcp, and even separates MCP-related actions from the prompt library.

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 explicit usage guidance: use search to discover, describe to inspect, and invoke for one-off runs. It says 'use install only to make an MCP PERMANENT' and 'prefer invoke for a single/occasional use', and it names alternatives like list_tools, subscribe, cancel, report_bug, request_mcp, and search_prompts with clear intent.

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 indicate idempotent behavior and non-destructive nature, but the description does not elaborate on side effects (e.g., creating a ticket, sending a notification). It mentions including conversation for reproduction, which hints at the submission process, but lacks explicit detail about what happens after the 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 a single, concise sentence that directly conveys the tool's purpose. It is well-structured and free of fluff 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 the lack of output schema and minimal parameter documentation, the description is incomplete. It does not explain how to use the parameters beyond mentioning the conversation array, and it fails to provide comprehensive usage context.

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 three parameters (context, message, conversation) with no descriptions in the schema itself. The tool description only references the conversation parameter, leaving message and context unexplained. This fails to provide necessary semantic information for the 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?

The description clearly states the tool's purpose: reporting a bug, missing feature, or sending feedback. It is specific and unambiguous, leaving no doubt about the action performed.

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 any guidance on when to use this tool versus alternatives. It lacks context about scenarios where reporting a bug is appropriate or how it differs from other 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?

Beyond the annotations (readOnly, idempotent, non-destructive), the description adds important behavior: it is a paid query, requires no platform credentials, provides the same data available to citizens, and clarifies the LGPD privacy responsibility. These extra details significantly expand the agent's understanding.

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 and keeps additional sentences relevant, such as payment and LGPD terms. A few phrases could be tightened, but overall every sentence contributes meaningful context.

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 single-parameter read-only tool with no output schema, the description covers the key contextual dimensions: official source, credential requirements, payment model, data sensitivity, and legal responsibility. It does not describe the response format, but that is not critical for a simple NFC-e lookup.

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 only parameter 'nfce' has 0% schema description coverage, and the description never specifies the expected format or meaning (e.g., whether it is the 44-digit access key). The acronym in the tool name helps, but the description does not compensate for the missing parameter documentation.

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 opens with 'SEFAZ MS: NFC-e, consulta em fonte oficial,' using the specific verb 'consulta' and the exact resource 'NFC-e' from the official SEFAZ source. This clearly distinguishes the tool from the listed siblings (authenticate, marketplace, etc.), which are platform-level utilities.

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 practical context: it is hosted by the platform, requires no platform credentials, and is paid via prepaid credit. This sets expectations for when to call the tool. However, it does not explicitly state alternatives or when not to use it, hence not a full 5.

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 is consistent with read-only, idempotent annotations; no additional behavioral details are needed.

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 unnecessary 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?

Given the simplicity and lack of parameters, the description is sufficient and 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?

No parameters exist, so no explanation is required.

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 displays MCP platform and adapter versions, distinguishing it from other tools in the list.

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 when version information is needed, though it does not explicitly state when to use versus alternatives; alternatives are not obvious.

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 and idempotentHint, so the agent knows this is a safe read. The description goes beyond by detailing exactly what state is exposed (MCPs, statuses, accounts, tool counts), providing valuable behavioral context about the return payload.

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, well-structured sentence with a clear verb ('Returns'), a direct object, and a colon-led list of included elements. No wasted words; every phrase adds value.

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 and no output schema, the description fully covers what the tool does and what information it provides. There are no gaps that would confuse an agent.

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 and 100% schema coverage (vacuously). Per the rubric, a baseline of 4 applies for 0-parameter tools, and the description is not required to add parameter detail.

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 'Returns the current toolkit state' and enumerates specific components (installed MCPs, connection status, accounts, catalog tool counts). This specific verb+resource combination distinguishes it from siblings like connect or authenticate, which imply different 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 a read-only inspection use case but does not explicitly state when to use it versus alternatives. While the sibling names (connect, authenticate, show_version) hint at different purposes, there is no explicit when/when-not guidance.

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