SEFAZ TO: NFC-e

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

Annotations already indicate idempotent, non-destructive, and not read-only. The description adds behavioral context such as the browser login flow, the ability to paste a JWT for session-only login, and the fact that no args returns a link. It also contrasts permanent vs session connections, which goes 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 a single paragraph with multiple instructions and some redundancy (e.g., login and copy token, then paste). It is information-dense but somewhat verbose, and could benefit from clearer structure separating the two usage modes. Still, it is not excessively 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?

For a simple auth tool with no output schema, the description covers the main aspects: how to initiate login, both permanent and session options, and what to expect (a link). It stops short of detailing the exact return format or error cases, but these are not essential given the tool's simplicity and annotations.

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 only an optional 'token' property with no description, so the description fully compensates by explaining the token is a JWT for session-only login and that calling with no args returns the login link. This gives clear meaning to the parameter and the no-argument case.

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 authenticates for MCP.AI used by IDE agents like Cursor, with explicit modes: getting a login link or accepting a token. It distinguishes this from siblings by scoping to IDE agents, though it does not explicitly contrast with '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 provides usage context: recommending a permanent config header vs a session-only token paste, and explaining the no-args call for a link. However, it does not explicitly state when to use this tool instead of alternatives like 'connect', nor when not to use it.

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 establish that the tool is read-only and idempotent. The description adds meaningful behavioral detail beyond the annotations, including the conditional response shape: authenticated:true with empty pending[] when connected, versus connect_url and per-install URLs when credentials are missing. No contradiction exists.

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 effectively front-loaded, with the core purpose in the first sentence and a concise conditional breakdown in the second. Every sentence earns its 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 zero-parameter status tool with no output schema, this description covers the main success and missing-credential branches clearly. It leaves minor ambiguities such as behavior when only some providers are connected or the exact response field shapes, but overall it is complete enough for a typical agent to choose and invoke it.

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 accepts zero parameters, so the input schema leaves no semantic gap to fill. The description adds no unnecessary parameter text, and no false parameter expectations are created.

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 a clear verb and object: 'Returns connection status and URLs.' It then gives concrete expected outputs for both connected and missing-credential states, making the tool's purpose unambiguous and distinguishable from action-oriented siblings like 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 intended use is implied: call this zero-argument tool to inspect connection status. However, the description never explicitly states when to prefer this over alternatives such as authenticate or toolkit_info, nor does it mention exclusions like 'use authenticate to initiate a connection.'

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?

No annotation contradiction exists — the description agrees with readOnlyHint=false, openWorldHint=true, destructiveHint=false. It adds deep context beyond the annotations: invoke runs one-off even when the MCP isn't installed, returns connect/checkout links, the install vs. invoke side-effect distinction (doesn't bloat the tool list), and the prompt library's login-free /p/ slug behavior. For a tool whose annotation block conveys almost nothing, the description carries the full burden and succeeds.

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 dense 450-word single paragraph with no section breaks, subheadings, or bullets. Every sentence contributes value and nothing is wasted, but the critical invoke-vs-install rule is buried in the middle rather than front-loaded, the prompt-library content is awkwardly appended with 'It also carries...', and there's a Portuguese typo ('pontualmente'). For an agent parsing a wall of text at runtime, better structure would meaningfully improve it.

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 enormous complexity — 14 actions, 23 optional params, two subsystems (marketplace + prompt library) — the description covers nearly all the important behaviors: full flow, permissions, auth/payment link handling, billing, and sharing semantics. Minor gaps (e.g., what happens on a resume action, what 'message' is for, error/empty-result behavior) keep it from a 5, but no output schema exists and the description already goes far beyond the schema.

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% schema description coverage and 23 params, the description carries the full burden for parameter meaning. It explains the core semantics well: the action enum values (search/describe/install/invoke/subscribe/cancel/list_tools/report_bug/request_mcp and the prompt_* family), the tool_id selection, mcp_id/dependency on describe, and arguments for invoke. However, some params (limit, tier_slug, immediate, conversation, message) remain unexplained despite the rich action context; the description covers the most important dozen of 23 params but not 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 identifies the tool as the mcp.ai marketplace and execution engine, with a specific verb-noun structure: lists what it catalogs, gives concrete example intents ('find an MCP that does X', 'consulta um CPF'), and outlines the search→describe→invoke flow that distinguishes it from the sibling tools like authenticate or report_bug. Although the surface area is large, the phrase 'Covers capability requests like...' plus the explicit flow makes it 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 directly answers when to use which action: 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use'; it explains what list_tools returns vs. search, how connect/checkout links work, when to retry, and that writes require owner/admin. This is explicit when/when-not guidance with named alternatives, and it even covers the requery-after-link pattern.

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 provide idempotentHint=true, readOnlyHint=false, and destructiveHint=false, covering safety and repeatability traits. The description adds that the conversation array should be included for reproduction, but it does not disclose what happens after reporting, such as whether feedback is persisted or what the response contains. No contradiction with 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?

Description is one concise sentence with front-loaded purpose and a practical instruction. Every clause contributes value, with no redundant or filler content.

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 low-complexity tool with three simple string parameters and helpful annotations. The description covers purpose, core usage, and the reproduction instruction. Minor gaps remain around the meaning of 'context' and the expected return, but overall the tool is sufficiently described for an agent to use 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?

Schema description coverage is 0%, so the description must compensate for documenting parameters. It only clarifies the 'conversation' parameter's role, while the required 'message' parameter and the 'context' parameter remain unexplained. This is partial guidance at best for a 3-parameter tool.

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 uses a specific verb ('Report') and clearly identifies the target resources: bug, missing feature, and feedback. It is also distinguishable from sibling tools such as authenticate, connect, and sefaz_to_nfce_consultar, none of which handle bug reporting or feedback.

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?

Description explicitly lists when to use the tool (bug, missing feature, feedback) and provides an actionable instruction to include the conversation array for reproduction. It does not mention alternatives or exclusions, but no near sibling exists, so the context is sufficiently clear.

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. The description adds useful behavioral context beyond those hints: no platform credentials are required, each query consumes prepaid credit, the data is non-confidential official information, and the client is the LGPD data controller. It does not cover errors or output format, but the annotation baseline lowers the burden.

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 purpose is front-loaded in the first sentence, and the description is compact. However, the phrase about consulting official sources and agencies largely repeats the 'fonte oficial' point from the first sentence, and the legal/payment context adds necessary information but could be tightened.

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 one-parameter, read-only tool with no output schema, the description covers purpose, hosting, credentials, payment, data sensitivity, and LGPD responsibility. Still, it omits the expected `nfce` input format and gives no indication of what the consultation result contains, leaving a notable completeness gap.

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 one string parameter `nfce` with 0% description coverage. The tool description only mentions NFC-e generically and never explains what value to pass, such as the access key, format, or length. This does not compensate for the lack of schema-level 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 clearly identifies the verb 'consulta' and the resource 'NFC-e' from 'SEFAZ TO', making the purpose understandable. It is specific about the official source but does not explicitly differentiate this tool from sibling alternatives, though no directly competing query sibling appears.

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 operational context (prepaid credit, no platform credentials) but does not state when to use this tool versus alternatives, nor any exclusions or prerequisites beyond payment. There is no explicit when/when-not guidance, so the agent must infer 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, which the description does not contradict. The description adds that it reports both platform and adapter versions, offering a bit more specificity about the output, but it does not detail potential side effects, error cases, or performance characteristics. This aligns with the baseline expectation but doesn't go further.

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 exactly one sentence, using the imperative 'Show' followed by the direct object. It is concise, front-loaded, and contains no filler or redundant phrasing.

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 version-information tool with no parameters and comprehensive annotations, the description is complete. It clearly states what the tool does without unnecessary elaboration. The lack of an output schema is mitigated by the tool's trivial nature; a user can reasonably expect a version string or similar.

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 schema coverage is 100% trivially. According to the rubric, a 0-param tool receives a baseline of 4, and the description does not need to elaborate on parameter meanings. No additional semantic information is necessary here.

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 the specific verb 'Show' and clearly identifies the resource as 'the current MCP platform and adapter versions.' This single-sentence explanation is unambiguous and differentiates the tool from its siblings (e.g., 'connect', 'marketplace'), which have distinct 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 provides no explicit guidance on when to use this tool instead of an alternative, but the intended usage is strongly implied by the name and description. It is straightforward to infer that this tool is for retrieving version information, which is a simple and obvious case, yet it stops short of naming alternatives or exceptions.

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 the exact content of the returned state beyond the readOnlyHint annotation, providing clear expectations of what the user will receive without any hidden side effects.

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 efficiently conveys all necessary information without redundancy or filler.

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 simple read-only nature and absence of an output schema, the description is complete. It fully explains what the tool returns, which is sufficient for the user to understand its function.

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 no parameters in the schema, so no explanation is needed. The baseline for zero parameters is 4, and the description adds no conflicting 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 clearly states that the tool returns the current toolkit state including installed MCPs, connection status, accounts, and catalog counts. It is specific and distinct 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 when to use it (to inspect toolkit state) and the nature of the returned info, but does not explicitly contrast with alternatives such as show_version. Still, the purpose is self-evident.

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