SEFAZ CE: NFE

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

Annotations declare idempotentHint=true and destructiveHint=false, and the description does not contradict these. It adds useful behavioral context: calling without args returns a link, and passing a token enables a session-only login. It also mentions the permanent vs. session distinction, which is beyond the annotations. Slightly lacks explicit detail on side effects (e.g., whether it stores the token), but overall transparency is strong.

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 yet informative, front-loading the purpose and then branching into configuration vs. session usage. Every sentence adds value; no filler or repetition. It is well-structured and easy for an agent to parse.

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 sufficiently explains what happens: it either returns a link (when called with no args) or processes a token. It also covers the two usage modes (permanent config vs. session-only). The tool is simple, and the description covers all necessary aspects for an agent to invoke 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?

The schema only defines 'token' as a string with no description (0% coverage). The description compensates by explaining when to provide the token (after the user pastes) and its format ('<jwt>'), and that omitting it returns the login link. This fully adds meaning beyond the raw 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 is for authentication, specifying the exact flow: log in in the browser, copy the access token, and either add it to the server config or pass it as a parameter. It distinguishes itself from siblings by being the dedicated auth tool for IDE agents (e.g., Cursor).

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?

Explicit usage guidance is provided: it recommends adding the token as a header for a permanent connection, or pasting the token for a session-only login. It also tells the caller when to pass a token (with the user's pasted JWT) and when to call with no args (to get the link). This fully clarifies when and how to use the tool.

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 agent knows this is a safe, non-mutating operation. The description adds details about the return values in different states, which is useful context beyond the annotations. However, it doesn't mention any side effects (though likely none) or edge cases, but given the annotations, the extra info about URLs is sufficient for a 3.

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, concise and to the point. It front-loads the primary purpose and then provides state examples. It is appropriately sized for a no-parameter tool, with every sentence adding 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?

Given no parameters and no output schema, the description adequately explains the tool's behavior in different scenarios (all connected vs. missing credentials). It provides enough information for an agent to know what to expect. It could mention example URL formats, but that is not essential for a status-check tool. The annotations cover safety, so the completeness is good.

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, so the description has little to add. However, the description clarifies what the output contains (e.g., connect_url when not authenticated), which indirectly explains how to interpret the response. Since there are no params, a baseline of 4 might be considered, but the description's clarity about return states is sufficient; no parameter-specific info is needed.

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 it returns connection status and URLs, with specific details about different states (authenticated:true, empty pending[], connect_url, per-install URLs). This distinguishes it from siblings like authenticate and marketplace, as it is a read-only status inspection tool.

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: when the agent needs to check connection status, especially to see if providers are connected or if credentials are missing. It doesn't explicitly exclude alternatives, but the context is clear given the sibling names (e.g., authenticate for initiating auth, connect for checking 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?

Annotations only give generic flags (readOnlyHint=false, openWorldHint=true), so the description carries the safety and side-effect burden — and it delivers richly: invoke performs a one-off install without bloating the toolkit; credential/paid cases return connect or checkout/top-up links, then "the user opens it, then you retry"; "Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin". It even documents that publish_prompt returns a shareable link that opens without login. Far exceeds what the annotations convey.

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 ~250-word description is a single dense paragraph with no visual hierarchy — no sentence breaks for stages like FLOW / MODES / PROMPT LIBRARY / PERMISSIONS, no bullets, no front-loaded summary line stripped from the flow. Every sentence carries information (low waste), but for a tool with 14 actions and two feature domains, the wall-of-text format makes rapid parsing difficult. This is not conciseness; it's under-structuring a legitimately large tool.

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 extreme complexity (23 params, 14 actions, no output schema, minimal annotations), the description covers an enormous surface: the full search→describe→invoke flow, the not-installed execution path, credential and payment retry loops, the install-vs-invoke decision, permission requirements, installed_in_toolkit vs installed_in_workspace flags, and the entire prompt-library domain. Gaps remain — 'resume' is never explained, and params like 'immediate', 'conversation', and 'tier_slug' are unaddressed — which costs it the 5, but the completeness for the primary user journey is exceptional.

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 — and it does for the critical dispatch parameter: every action enum value except 'resume' is behaviorally defined (search/describe/invoke/install/list_tools/report_bug/request_mcp/search_prompts/get_prompt/publish_prompt/subscribe/cancel). It also ties the key params to their roles (describe uses mcp_id, invoke uses tool_id + arguments). However, with 23 parameters there are gaps: 'limit', 'immediate', 'conversation', 'tier_slug', and 'message' get no explicit explanation, and 'resume' is only implied by the subscribe/cancel grouping. Strong compensation, 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 opening line — "The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them" — precisely names the resource, the action (marketplace operations), and its scope (catalog plus execution). It immediately distinguishes from siblings like authenticate, connect, and the SEFAZ tool by stating it's the discovery + invocation layer, and even carves out a second domain (prompt library) explicitly. The verb/scope contract is 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?

Explicit when-to/which-action guidance throughout: "prefer invoke for a single/occasional use", "Use install only to make an MCP PERMANENT in the active toolkit", "subscribe/cancel handle per-MCP billing", and "request_mcp asks us to build a NEW MCP when nothing fits". The core flow (search → describe → invoke) is spelled out with a concrete condition — "invoke works even when the MCP is NOT installed" — plus retry instructions for credential and payment cases. This is direct, actionable routing for the agent.

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 (readOnlyHint=false, destructiveHint=false, idempotentHint=true), so the bar is lower. The description adds that the conversation array is included for reproduction, implying the data is transmitted. It does not disclose side effects beyond submission, but is not misleading and adds some behavioral context.

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 with the main purpose front-loaded. It wastes no words and is appropriately sized for the tool's simplicity.

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 tool with no output schema and no nested objects, the description is adequate but incomplete. It provides the core purpose and a hint for one parameter, but fails to describe the required message field or any expected response. It is a minimum viable description with clear 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?

Schema description coverage is 0%, so the description must compensate. It only explains the purpose of the 'conversation' parameter (recent messages for reproduction) but does not clarify the required 'message' parameter or the optional 'context' parameter. This leaves significant semantic gaps.

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 with a specific verb and resource: 'Report a bug, missing feature, or send feedback.' This distinguishes it from the unrelated sibling tools (authenticate, marketplace, sefaz_ce_nfe_consultar, etc.).

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 on when to use the tool (for bugs, missing features, feedback) and even gives a usage hint ('Include the conversation array with recent messages for reproduction'). It does not explicitly discuss alternatives or when not to use it, but the context is sufficient given the sibling tools are unrelated.

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 annotations, it discloses that no platform credentials are required, it is a paid consultation, and it deals with non-confidential data, with the client responsible for LGPD compliance. This adds behavioral transparency.

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 sentence, but contains legal and procedural details that could be separated. It is not overly long, but the structure is a run-on.

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 provides purpose and some behavioral constraints, but lacks parameter details, return format, and usage scenarios. It is somewhat incomplete for a tool with a single parameter.

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 single required parameter 'nfe' is not explained in either the schema or description. There is no indication of its format (e.g., access key, number) or any constraints.

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 consults NF-e in official sources, making its purpose evident. It distinguishes itself as a consultation tool, not a modification, though it could specify what details it returns.

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?

No guidance on when to use this tool over alternatives, nor any prerequisites or scenarios. It only mentions payment and data responsibility, not usage conditions.

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 useful context about what the tool returns—current MCP platform and adapter versions—beyond the bare 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 a single, front-loaded sentence that conveys the purpose with no wasted words. It is appropriately concise for a zero-parameter, read-only version-inspection tool.

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 simplicity, the rich annotations, and the zero-parameter schema, the description provides sufficient context for an agent to select and invoke the tool correctly. No output schema exists, but the returned information is straightforwardly described by the tool name and 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?

The tool has zero parameters, so parameter semantics are trivial. The schema coverage is effectively complete, and the description adds no misleading or 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 ('Show') and a clear resource ('current MCP platform and adapter versions'), making the tool's purpose immediately obvious. It is also clearly distinct from the sibling tools, which involve authentication, connectivity, marketplace, bug reporting, or SEFAZ consultation.

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 explicitly state when to use this tool versus alternatives, but the usage context is strongly implied: call this tool to check which MCP platform and adapter versions are currently running. No exclusions or alternative references are provided.

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 the tool read-only and idempotent, so the description's job is to add behavioral detail. It does this by specifying the exact fields returned (installed MCPs, connection status, accounts, catalog tool counts). While it does not dive into potential caveats like response size or caching, the provided detail goes meaningfully beyond the annotations and gives the agent a realistic picture of what to expect.

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 one compact sentence that front-loads the core action and then lists the four concrete return aspects separated by commas. It is concise without being terse, and every word adds meaning. There is no redundancy or 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 the tool's simplicity—no parameters, no output schema, and a read-only nature already annotated—the description covers every essential aspect an agent needs. It details the return content thoroughly enough to set expectations and does not omit any crucial behavioral aspect. The description is complete for its intended 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 input schema is an empty object with 100% schema description coverage (vacuously), and there are zero parameters. The description does not waste characters on params, which is appropriate. Per calibration, zero-parameter tools earn a baseline of 4, and the description adds value by detailing the output instead of the (nonexistent) 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 begins with a specific verb, 'Returns,' and clearly identifies the resource as 'the current toolkit state.' It enumerates exactly what that state includes: installed MCPs, their connection status, associated accounts, and catalog tool counts. This fully differentiates it from sibling tools like show_version or connect, which address different concerns.

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 the tool—whenever an agent needs a status overview—but it never explicitly states this or contrasts it with alternatives. There is no mention of sibling tools or conditions like 'Use this before connecting' or 'For version details, see show_version.' It provides a clear purpose but leaves the 'when vs. when not' to be inferred.

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