SEFAZ RS: Certidão Negativa de Débitos

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

It discloses relevant behavior beyond the annotations: calling with no args produces a login link, calling with a token activates a session, and the described permanent mode uses a config header. It aligns with the idempotent and non-destructive hints, adding meaningful workflow 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 appropriately concise and covers all essential information in three sentences. The structure is a bit dense and slightly overlong in the last sentence, but no words are wasted.

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 (one optional parameter) and the description covers the two call modes and expected inputs. It does not explain what happens after successful authentication via the token path, but the overall context is sufficient for an agent to use 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 only parameter `token` is explicitly described as the pasted JWT, with an example call and clear statement that omitting it returns the login link. This fully compensates for the lack of parameter description in 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 identifies the tool as an authentication helper for MCP.AI in IDE agents, explaining it logs in via browser/copy-token or by providing a JWT. It specifies the resource (MCP.AI) and the scope (IDE agents such as Cursor), and the flow is distinct from siblings like 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 explains when to use the tool and the main alternative: adding an Authorization header to the server config for persistent access versus pasting a token for session-only. It gives clear contexts but does not explicitly contrast with sibling tools like connect.

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. The description adds valuable context by specifying the two response states (authenticated:true with empty pending[] vs connect_url when credentials are missing), going beyond the structured hints.

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 with front-loaded purpose and concise conditional details. Every word earns its place; no filler 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 status tool with no output schema, the description covers the primary return states (all connected vs missing credentials). A slight gap exists for partial connectivity, but it is adequate for the tool's simplicity.

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 schema trivially covers everything. The description correctly focuses on behavior rather than parameters, and the baseline of 4 applies.

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 ('connection status and URLs'), and the conditional behavior distinguishes it from sibling 'authenticate' by clarifying it reports status 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 usage is implied: call this to check connection status. However, it does not explicitly state when to use this tool versus alternatives like 'authenticate', nor does it provide any exclusions or alternative guidance.

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 rich in behavior beyond the shallow annotation set: it states invoke executes MCPs not installed, does not bloat the tool list, returns login/checkout links when credentials or wallet funds are missing, requires workspace owner/admin for writes, and lists installed state flags in search/describe. None of this contradicts the annotations, so the description fully carries the transparency 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 description is a single dense block that spends every sentence on substantive behavior and front-loads the core definition. However, the long run-on structure, commas, and boly semicolon usage deter quick scanning; a bulleted flow of actions and short paragraphs would have been clearer while retaining all the key information.

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 complexity (23 parameters, 12+ actions, no output schema), the description covers the canonical paths—discover, describe, invoke, install, billing, prompt library, and permissions. Yet it misses the meaning of several actions/parameters, most notably the `resume` action, the `arguments` JSON format, and the `conversation` parameter, leaving some real gaps for correct invocation.

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 must compensate for parameter meaning. It energetically defines action names and implied parameters (query, mcp_id, tool_id), but many remain completely unexplained: arguments as a JSON string, limit, conversation, immediate, tier_slug, cancel_reason, cancel_comment, report_context, and several prompt_* parameters. This leaves significant ambiguity for an agent trying to construct a request.

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 immediately defines the marketplace as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them' and then enumerates the exact capabilities: search, describe, invoke, install, subscribe/cancel, report_bug, request_mcp, and the prompt library. It strongly distinguishes this tool from simple sibling tools by presenting a clear content-specific purpose, despite the large breadth of 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 gives explicit when-to-use guidance and alternatives: a complete flow of 'action=search discovers MCPs → describe returns one MCP's full profile → invoke RUNS that tool', plus a direct recommendation that install is for permanent addition and invoke is preferred for single/occasional use. It additionally specifies list_tools for what is callable, subscribe/cancel for billing, and request_mcp for building new MCPs, providing clear selection criteria.

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, so the description isn't required to restate these. It adds value by instructing users to include the conversation array for reproduction, but it doesn't disclose side effects (e.g., sending data externally, creating a ticket) or what happens after submission. This is moderate transparency 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 sentence that immediately states the tool's purpose and includes one critical usage note. Every word earns its place; there is no fluff 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?

The description offers a general purpose and one usage hint, but with three parameters and no output schema, it lacks detail on parameter roles and expected behavior. It is sufficient for a simple tool, yet gaps remain, particularly around the 'context' parameter and what constitutes a valid 'message'.

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 0% description coverage, so the description must compensate for parameter meanings. It explicitly mentions 'conversation array' and 'message' but does not clarify the 'context' parameter or the expected format of 'message.' The description fails to fully explain all three parameters, leaving significant ambiguity.

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 plus resource: 'Report a bug, missing feature, or send feedback.' This distinguishes it from sibling tools like authenticate, connect, or marketplace, which serve entirely different functions.

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 usage context by telling the user to include the conversation array with recent messages for reproduction. While it doesn't explicitly name alternatives or exclusions, sibling tools are sufficiently different that no ambiguity exists. It effectively communicates the intended use case.

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 readOnly, idempotent, and destructive hints. The description adds meaningful behavioral context beyond those: payment per query, no platform credentials, non-confidential data, and the client's role as data controller under LGPD. It does not contradict 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 focused sentence that front-loads the core purpose and packs relevant operational and legal context efficiently. It is somewhat dense, but every clause adds meaningful information.

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 consultation tool, the description covers purpose, official source, pricing, and data governance. However, it omits how to use the CPF/CNPJ parameters, mutual exclusivity if applicable, and what the returned certificate looks like. The absence of an output schema makes this gap more noticeable.

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%, and the description does not mention cpf or cnpj at all. It fails to explain that these are Brazilian tax identifiers, whether one is required, or any formatting/validation rules. The description provides no compensation 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 clearly identifies the resource (SEFAZ RS Certidão Negativa de Débitos) and the action (consultar/consulta em fonte oficial). It is specific enough to distinguish it from the unrelated sibling tools like authenticate, connect, 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 for use: it is an official Brazilian source, hosted by the platform, requires prepaid credit, and involves LGPD responsibilities. It does not explicitly state when to use it versus alternatives, but no directly competing sibling tool 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, which fully cover the safety profile. The description adds only the detail about showing versions, which is more about purpose than behavior. It does not contradict annotations, and the annotations carry the transparency burden effectively.

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 of 11 words, front-loaded with the action ('Show') and specific object ('current MCP platform and adapter versions'). Every word earns its place, with no unnecessary details.

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 (zero parameters, rich annotations, no output schema), the description fully covers the essentials: what it does and what it returns (versions). It does not need additional context about outputs or side effects because annotations already cover safety and idempotency.

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 description coverage is 100% by default. Per the rubric, a zero-parameter tool gets a baseline of 4 for parameter semantics, and the description adds nothing extra (there is nothing to add). The score reflects the baseline.

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 shows current MCP platform and adapter versions. It uses a specific verb ('show') and resource ('versions'), which distinguishes it from siblings like toolkit_info, though it does not explicitly differentiate from similar informational tools.

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 is provided on when to use this tool versus alternatives. While it is a simple read-only info tool, it does not mention any context or contrast with siblings such as toolkit_info or marketplace, leaving the agent without explicit usage direction.

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 tool's safety is clear. The description adds value by detailing exactly what state information is returned (MCPs, connection status, accounts, tool counts), which goes beyond the annotation's binary flags. No contradictions 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 a single, well-formed sentence that efficiently enumerates the returned content. Every clause adds concrete detail without redundancy, and the most important element (state return) is front-loaded. No filler or unnecessary information.

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 informational tool with no parameters and no output schema, but the description fully specifies what the user will receive. It covers all relevant aspects of the tool's behavior and output, making it complete for the agent to decide whether to 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 has zero parameters, and schema coverage is 100% (trivially). With no parameters to document, the description is not expected to elaborate on inputs. The baseline for zero-param tools is 4, and the description appropriately focuses on the output rather than 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') and a precise resource ('current toolkit state'), then enumerates the exact contents (installed MCPs, connection status, associated accounts, and catalog tool counts). This clearly distinguishes it from siblings like show_version (version only) and connect/authenticate (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 an informational use case but does not explicitly state when to prefer this tool over siblings, nor does it mention prerequisites or complementary usage (e.g., checking state before connecting). The purpose is clear, but no direct guidance or exclusions are provided.

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