SEFAZ SP: Cupom Fiscal Eletrônico (SAT) - Detalhado

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

The description discloses that the tool can return a login link (when called with no args), and explains the difference between permanent (config header) and session-only authentication, which goes beyond the annotations. It does not conflict with the idempotentHint=true annotation; repeated calls with the same token should be safe. It also implies state change (authentication) consistent with readOnlyHint=false.

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 functional but slightly wordy, providing context about IDE agents (Cursor, etc.) that may not be essential. It could be more concise, but all sentences serve a purpose in explaining the 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?

For a simple one-parameter tool with no output schema, the description covers the key aspects: how to obtain the token, the two authentication modes, and the parameter usage. It does not describe the return value, but that is less critical here. The guidance is sufficient for an agent to invoke the tool 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 input schema defines a single optional 'token' string with no description, but the description compensates by explaining what the token is ('<jwt>') and how to use it, as well as the behavior when omitted (returns a link). This adds sufficient meaning beyond the 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 with MCP.AI by either returning a browser login link (no args) or accepting a JWT token for session login. It also mentions the alternative of adding the token to server config for a permanent connection. While it doesn't explicitly contrast with sibling 'connect', the verb 'authenticate' and the login context make the purpose clear.

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 instructions: call with no args to get a login link, or with a token for session-only login, and recommends adding the token to the server config as an Authorization header for a permanent connection. It thus provides clear when-to-use guidance for the different invocation modes, though it doesn't discuss alternatives among 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, idempotentHint, and non-destructive behavior. The description adds value by specifying the response states: authenticated:true with empty pending[], or connect_url plus per-install URLs when credentials are missing. This provides useful behavioral context beyond the annotations without contradicting them.

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, front-loaded with the core purpose, and contains no filler or redundant restating of the tool name or annotations. Every clause contributes meaningful behavioral detail.

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, the description provides enough about both success and missing-credential states, including key output fields. It does not fully enumerate an output schema, but no output schema is present, and the behavior is simple enough that the description is largely 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 tool has zero parameters and schema coverage is effectively complete, so the description cannot add parameter-level meaning. The baseline for zero parameters is 4, and the description appropriately focuses on 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 uses the specific verb 'Returns' and clearly identifies the resource: connection status and URLs. It differentiates from siblings like authenticate by focusing on status reporting rather than performing authentication.

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 by describing its output in different connection states, but it never explicitly states 'use this when you need to check whether providers are connected' or explains when not to use it in favor of authenticate. Guidance is inferred rather than explicit.

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 are minimal (readOnlyHint=false, no idempotent/destructive hints), so the description carries the full burden and delivers richly. It discloses that invoke runs a tool one-off without installing it ('without adding the MCP to the toolkit and without bloating the tool list'), that credential/payment gaps return connect/checkout links requiring user action then retry, that install is permanent, and that write operations need workspace owner/admin. This significantly extends behavioral knowledge beyond the structured fields. 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?

This is a dense ~450-word single paragraph with no bullets, line breaks, or sectioning, making it hard to scan. It front-loads the core purpose and flow well, but the invoke explanation is redundant ('runs it pontualmente (one-off)' repeated with 'without adding... without bloating'), and the PROMPT LIBRARY section is appended as a trailing clause. Every sentence carries some information, but the wall-of-text format undermines usability for an agent parsing on the fly.

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 of this complexity (23 params, 14 actions, no output schema, sparse annotations), the description covers the workflow thoroughly: the search→describe→invoke pipeline, install vs invoke tradeoffs, billing/auth links, and the prompt-library sub-flow. However, it omits parameter semantics (limit, tier_slug, prompt_targets, cancel_reason, etc.) and never explains the return value shape — with no output schema, the agent cannot know what invoke or describe returns on success beyond the connect/checkout link mentions. Adequate for workflow, incomplete on data contract.

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 fully, but it does not. It thoroughly explains the action enum (all 14 values are described in prose) and implies mcp_id/tool_id/arguments through the flow narrative, but the remaining ~17 parameters (limit, message, immediate, tier_slug, conversation, cancel_reason, cancel_comment, prompt_body, prompt_slug, prompt_tool, prompt_title, request_name, prompt_targets, report_context, request_details, prompt_description, prompt_category) are completely unexplained in both schema and description. The action field is well-served, but the bulk of parameters are opaque.

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 establishes this as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' with a defined core flow (search → describe → invoke). It names specific capability intents ('find an MCP that does X', 'consulta um CPF') which makes the purpose concrete. However, the tool spans 14 actions plus a prompt library, so the purpose is somewhat diffuse rather than a single verb+resource; the description handles this well overall but doesn't crisply state 'this tool performs one job'.

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?

Exceptionally explicit guidance is provided: the core flow is spelled out step-by-step ('action=search discovers MCPs by intent → describe returns one MCP's full profile... → invoke RUNS that tool'). It gives a clear decision rule for invoke vs install ('Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use'), states auth requirements ('Writes... require workspace owner/admin'), and covers the retry flow when credentials or payment are needed. It also tells when to use list_tools, subscribe/cancel, report_bug, and request_mcp, including the fallback 'request_mcp asks us to build a NEW MCP when nothing fits.'

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 the basic behavioral markers: not read-only, idempotent, and not destructive. The description adds that the conversation is included with the report, which is useful context, but it does not mention authentication requirements, response behavior, or other 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 short and front-loaded: purpose first, then one relevant usage note. Every sentence contributes information without repetition 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?

The tool is simple and has annotations, but the complete lack of parameter documentation in the schema demands more from the description. It covers the reproduction aspect but leaves the required message and optional context underspecified, and the conversation format is ambiguous.

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, the tool description must compensate for all parameters. It only hints at the conversation parameter, and does so in a misleading way by calling it an array when the schema defines a string defaulting to '[]'. It does not explain the required message or the context parameter.

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 names concrete actions: report a bug, request a missing feature, or send feedback. This goes beyond the tool name and clearly distinguishes it from sibling tools like show_version and marketplace.

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 gives clear reporting context and instructs the caller to include recent conversation messages for reproduction. It does not explicitly compare against alternative tools, but no sibling appears to serve the same bug/feedback purpose.

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, destructiveHint=false, so the safety profile is clear. The description adds valuable context: it's hosted by the platform, requires no platform credentials, is pay-per-query with prepaid credits, and clarifies data is not confidential. It also addresses LGPD compliance, which is useful behavioral context beyond 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 but packs essential information: what it does, source, hosting, credentials, pricing, data nature, and LGPD. It's somewhat dense but not verbose. Could be slightly more structured, but it's 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?

Given the tool's simplicity (1 param, no output schema), the description covers the key aspects: purpose, data source, access method, and legal context. It doesn't describe return format, but with no output schema, that's a minor gap. The description is adequate for an agent to understand what this tool does and its constraints.

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 coverage is 0% and there's only one parameter 'chave' (key). The description doesn't explain what 'chave' means (likely the CF-e access key), but with a single parameter and the tool name indicating CF-e consultation, the meaning is fairly inferable. However, the description could have explicitly stated that 'chave' is the CF-e access key.

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 queries official SEFAZ SP source for detailed Electronic Fiscal Receipt (SAT) information. It distinguishes itself by specifying 'Detalhado' (detailed) and 'consulta em fonte oficial', though it doesn't explicitly contrast with sibling tools (which are mostly unrelated).

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 querying official Brazilian tax data, and mentions it's the same data available to citizens, but doesn't explicitly state when to use this vs alternatives or when not to use it. Sibling tools are unrelated, so no direct comparison is 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?

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, establishing this is a safe, read-only operation. The description reinforces that by saying 'Show' (not 'change' or 'modify'). It adds no contradictory information and is fully aligned with annotations, which is sufficient for a simple version query.

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 superfluous words. It front-loads the action ('Show') and specifies the exact scope of information, making it extremely concise and structured appropriately.

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 has no parameters, no output schema, and is a simple informational read, the description is complete. It states what versions are returned, and the annotations cover safety. There is no missing information that would hinder correct 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?

The tool has zero parameters, so the baseline is 4 per the rubric. The description doesn't need to elaborate on parameters, as there are none to explain. It adds value by stating what the output covers (platform and adapter versions), which helps the agent know what to expect.

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 function: showing the current MCP platform and adapter versions. It uses a specific verb ('Show') and identifies the resource (versions), which is distinct from siblings like authenticate or connect. It could be slightly more specific about what 'adapter' refers to, but the purpose is clear.

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 checking the environment/version), but it doesn't explicitly state exclusions or alternatives among siblings. Given no parameters and a simple informational purpose, the context is clear enough, though it could benefit from an explicit note like 'use when you need to verify compatibility or version details.'

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 destructiveHint=false, so safety is clear. The description adds valuable context about the content of the response, specifying what aspects of toolkit state are returned. This goes beyond the annotations, though it doesn't discuss side effects or auth requirements (which are irrelevant for a read-only tool).

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, tightly written sentence that front-loads the core action and lists all relevant output details. No unnecessary words 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?

For a zero-parameter read-only tool with no output schema, the description fully specifies what the agent can expect to receive. It covers installed MCPs, connection status, accounts, and catalog tool counts—everything needed to understand the tool's return value and purpose.

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 baseline is 4. The description correctly implies that no parameters are needed, and there's nothing more to explain about 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 uses a specific verb 'Returns' with a clear resource 'current toolkit state' and enumerates the exact components (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from sibling tools like authenticate, connect, or show_version, which have different 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 implicitly communicates when to use this tool: whenever the agent needs to inspect the toolkit's state. However, it does not explicitly mention when not to use it or suggest alternatives, but that's acceptable given the simplicity of the tool and clear context from the description.

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