SEFAZ CE: Cupom Fiscal Eletrônico (SAT)

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

The description adds useful behavioral context beyond annotations: it explains the permanent-vs-session distinction, the need to paste a JWT, and the no-args behavior of returning a link. It does not contradict the idempotentHint or destructiveHint annotations, though it could more explicitly disclose state changes when a token is supplied.

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 long and front-loads the core action, with additional detail about the recommended permanent header configuration and the session-only fallback. Each sentence contributes useful operational information, though the lead-in 'MCP.AI for IDE agents (Cursor, etc.)' is slightly verbose.

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 input schema, no output schema, and one optional parameter, the description gives enough operational context to invoke the tool: how to get the link, how to pass a token, and how to configure a permanent connection. It lacks explicit return-value details for the token-provided call, but the tool is simple enough that this is a minor 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?

With 0% schema description coverage, the description carries the full burden for the single 'token' parameter. It explains that token is a JWT pasted from the browser and that omitting it will trigger the login-link flow. This compensates well for the lack of schema descriptions, though it does not detail the token's exact format or expected expiry behavior.

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's purpose: authenticating IDE agents to the MCP server by logging in through the browser and obtaining an access token. It is specific about the resource (this server's auth) and the action, though it does not explicitly distinguish itself from the sibling tool '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?

It provides explicit usage alternatives: permanent configuration via header vs. session-only login by pasting a token, and explains that calling with no args returns the login link. While it does not explicitly state when not to use this tool, the two-path guidance is strong enough to guide agent decision-making.

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 indicate read-only, idempotent, non-destructive, but description adds valuable context about the exact response states: authenticated:true with empty pending[] vs. connect_url and per-install URLs. This goes beyond annotation coverage.

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?

Two concise sentences, front-loaded with the primary purpose and then expanding on behavior. No redundant information or unnecessary 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?

Description covers the two main states (all connected vs. missing credentials) and clarifies return values. Lacks explicit mention of partial connection states, but for a simple no-parameter status tool, this 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?

Tool has zero parameters, so schema coverage is 100% and there is nothing to document. Baseline of 4 applies, and description does not need to add parameter info.

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 clearly states the tool's purpose: returns connection status and URLs, with specific behavior for different states. Distinguishes from siblings like 'authenticate' by focusing on status rather than authentication 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?

Provides clear context on what the tool returns and when (all connected vs. missing credentials), implying use for checking connection status. Does not explicitly mention alternatives or when not to use, but sibling names like 'authenticate' suggest distinct purposes.

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 say readOnlyHint=false and destructiveHint=false, so the description carries the behavioral burden. It discloses writes require workspace owner/admin, invoke works without installing, returns connect/checkout links, and avoids bloating the tool list. This meaningfully 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 long and dense, but it earns its length given the tool's action-dispatch complexity and 23 parameters. The core flow and exception behaviors are front-loaded, and there is almost no filler; the odd 'pontualmente' phrase and heavy use of CAPS add slight noise.

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 high complexity (23 params, 14+ actions, no output schema), the description explains the overall architecture well: search/describe/invoke lifecycle, install permissions, billing/payment flows, and the prompt-library subsystem. Minor gaps remain: the 'resume' action is undocumented, 'connect' is only implied via links, and several params are contextually orphaned.

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 core params like action, query, mcp_id, tool_id, arguments, and prompt_* fields. However, 23 parameters are left largely unmentioned (limit, immediate, conversation, report_context, request_details, cancel_reason), so many parameter semantics remain under-specified.

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 is explicit: 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them' with a clear core flow. It identifies what the tool does, its scope, and its relationship to capability searches.

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 strong when-to-use guidance: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', plus distinctions for subscribe/cancel, report_bug, and request_mcp. It also explains what to do when credentials or payment are required.

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 idempotentHint=true and destructiveHint=false. The description adds that the conversation array is for 'reproduction,' giving context that the data is sent for debugging. It doesn't contradict annotations and provides some added context about expected use, though it doesn't detail side effects or data handling. This is an adequate but not exceptional addition 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?

Two sentences: the first states the purpose, the second gives a critical usage instruction. Every word is purposeful, and the description is front-loaded with the action verb. No 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?

For a tool with 3 simple parameters, the description covers the core action and the most important parameter (conversation) with context for reproduction. It doesn't explain return values, but there's no output schema and the annotations cover idempotency and safety. A minor gap is not explaining the 'context' parameter, but the tool is simple enough that the description is nearly 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 coverage is 0%, so the description must compensate for missing parameter details. It does explain that 'conversation' should be an array of recent messages for reproduction, which adds meaning. However, it doesn't clarify the 'context' parameter or the format of 'message' beyond the general purpose. The description partially bridges the gap but leaves some 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: 'Report a bug, missing feature, or send feedback.' This is a specific verb+resource combination that distinguishes it from siblings like 'show_version' or 'authenticate', which have different functions. Even without knowing sibling names, the purpose is immediately 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 the tool ('Report a bug, missing feature, or send feedback') and provides a specific instruction ('Include the conversation array...'). It doesn't mention exclusions or alternatives, but none of the sibling tools appear to serve a similar purpose, so context is clear. A full 5 would require explicit when-not-to-use or alternative naming.

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 destructiveHint false. The description adds meaningful behavioral context beyond those: prepaid per-query cost, no platform credentials needed, official-source nature, and LGPD controller responsibility. This is valuable additional disclosure.

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 purpose, followed by payment, access, and legal context. Every sentence adds relevant information without filler or repetition.

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 query tool, the description covers the source, access model, cost, and data classification. However, it omits the expected format of 'chave' and any indication of response contents, which is more impactful given there is no output 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?

The schema has one required string parameter 'chave' with 0% description coverage. The description never explains what 'chave' is, its expected format, or how to obtain it. Since schema coverage is low, the description should compensate, but it does not.

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 CE: Cupom Fiscal Eletrônico (SAT), consulta em fonte oficial', giving a specific verb (consulta) and resource (CF-e from SEFAZ CE). This clearly distinguishes it from the generic sibling tools like authenticate, marketplace, and show_version.

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 useful context: it queries an official Brazilian source, requires no platform credentials, uses prepaid credit, and deals with non-confidential data. It does not explicitly state when to use it versus alternatives, but no similar sibling exists, so the context is sufficient.

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 the tool as read-only and non-destructive, and the description's 'Show' verb aligns with that. The description adds useful specificity by naming exactly what is shown (MCP platform and adapter versions), which goes slightly beyond the annotation framework.

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 with no filler or redundant information. Every word contributes to the meaning, and it is fully front-loaded.

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 low complexity (no parameters, no output schema), the description is sufficiently complete. It states the exact purpose and leaves no ambiguous operational questions for this straightforward version query.

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 is an empty object, so there is no parameter burden for the description to carry. Per the rubric, a baseline of 4 is appropriate when no parameters need explanation.

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 function immediately obvious. This also distinguishes it from sibling tools like authenticate, connect, and toolkit_info.

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 should be used when the agent needs to know the current platform and adapter versions, but it provides no explicit context about when to prefer this over alternatives or any exclusions. For a simple information-only tool, this implied usage is acceptable but not fully 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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by specifying exactly what state is returned, going 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 a single, well-structured sentence that front-loads the core purpose and then lists the specific data points returned. Every word earns its place, with no 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?

For a zero-parameter, read-only informational tool with strong annotations, the description is complete. It fully explains what the return value contains, which is especially important given there is no output 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?

The tool has zero parameters, so the baseline is 4. The description adds no parameter-specific meaning because none is needed; the schema already confirms an empty parameter object.

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') and clearly identifies the resource ('current toolkit state') with a detailed enumeration of contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from siblings like show_version, which presumably reports version info rather than overall state.

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 clearly implies when to use this tool: whenever the agent needs an overview of the toolkit's installed MCPs, connections, and accounts. It does not explicitly name alternatives or exclusions, but the context is unambiguous enough for a simple informational tool.

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