SEFAZ ES: Certidão Negativa de Débitos

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

It discloses behavior beyond annotations, such as the distinction between permanent non-expiring config-based bearer tokens and session-only pasted JWTs. It also implies a browser-login flow without contradicting idempotentHint or any other annotation.

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 front-loaded, with two sentences covering auth flow, best practices, and invocation patterns. Slightly conversational phrasing adds minor noise but every sentence offers actionable 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?

For an authentication tool with one optional token parameter, no path schema, and idempotentHint true, the description is largely sufficient and explains how to obtain and use the token. It does not mention response shapes or errors, but these are not critical for this use case.

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?

Even though the schema only defines an optional 'token' string with no description, the description compensates by explaining that token should be the JWT pasted by the user and that omitting it returns the login link. This adds meaningful semantic context for the single 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 clearly states the tool's purpose: authenticate an MCP.AI connection by obtaining a login link or accepting a pasted JWT. It names specific actions and resources, though it does not explicitly compare itself with sibling tools 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 provides concrete when-to-use guidance: call with no arguments to get the login link, call with { token: '<jwt>' } for session-only auth, or use the server config for a permanent bearer token. It lacks explicit sibling-tool alternatives, but the usage context is 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, so the safety profile is clear. The description adds behavioral context about the response structure (authenticated:true and empty pending[] vs. connect_url and per-install URLs), which is useful beyond the annotations. However, it doesn't disclose details like rate limits or auth requirements, but given the annotations cover the main safety aspects, a 3 is appropriate.

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 every sentence adds value. It efficiently covers the two possible states without 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?

Given the tool has no parameters, no output schema, and simple annotations, the description is complete enough. It explains the two states and what URLs are returned, which is sufficient for an agent to understand the tool's behavior. The only minor gap is not specifying the exact format of the URLs, but that is not critical.

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 provides no parameter information. The description compensates by explaining what the tool returns and under what conditions, which is the relevant semantic content. Since there are no parameters to document, a baseline of 4 is justified.

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 returns connection status and URLs, and explains the two possible states (all providers connected vs. missing credentials). It distinguishes from siblings like authenticate and toolkit_info by focusing on status/URLs rather than performing authentication or showing version 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 when to use it (to check connection status and get URLs when credentials are missing) but does not explicitly state when not to use it or mention alternatives. It provides context about the two states, which helps the agent decide, but lacks explicit exclusions.

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 the annotations, the description richly discloses behavioral traits: invoke runs tools one-off without installing or bloating the tool list, auth and payment failures return actionable links, and writes require workspace owner/admin. It also contrasts search/describe flags for installed state and explains that prompt links open without login. No contradiction with the annotations; the description adds substantial context they do not provide.

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 but unusually dense and well organized: core flow first, then the invoke nuance, install vs invoke, permissions, and prompt library. Almost every sentence earns its place. Minor points like the localized example 'consulta um CPF' and the awkward 'pontualmente' add slight noise, but they do not undermine overall structure.

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 complexity (14 actions, 23 params, no output schema), the description covers most key behaviors: discovery, invocation, installation, billing/subscription, permissions, and prompt-library operations. It leaves some output expectations unstated for actions like report_bug, request_mcp, subscribe, and cancel, but for an agent selecting and invoking the tool, the critical paths are sufficiently 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?

With 23 parameters and 0% schema description coverage, the description carries a heavy burden and does add meaning for many action values and prompt-related parameters (e.g., action=invoke, prompt_vars filling, publish_prompt returning a slug link). However, several non-obvious parameters remain unexplained, such as limit, query, immediate, tier_slug, and conversation, so an agent still has to guess or infer their formats and relevance.

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 official mcp.ai marketplace and runtime, with a specific verb+resource framing ('catalog of every MCP/tool, AND the way to run them'). It also lays out the core search→describe→invoke flow, making the main purpose unambiguous. It does not explicitly compare itself to sibling tools like authenticate or connect, and the added prompt-library scope makes it multi-purpose, so it falls just short of a perfect 5.

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 for the major actions: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', 'list_tools lists what is callable right now', and 'request_mcp asks us to build a NEW MCP when nothing fits'. It also explains the auth/billing edge cases (connect link, checkout link) and when to retry. This is model behavior for guiding tool selection.

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 (readOnlyHint: false, destructiveHint: false, idempotentHint: true) already indicate it's a non-destructive, idempotent write operation. The description adds the reproduction requirement but does not describe effects (e.g., whether a ticket is created) or authentication needs. 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?

The description is two sentences, direct, and front-loaded with the purpose. Every sentence adds value—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?

The tool is simple (3 parameters, no output schema), but the description lacks information about return values (e.g., success message) and does not explain the 'context' parameter. While it covers the essential purpose and one usage hint, gaps remain for a fully self-sufficient 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?

Schema description coverage is 0%, so the description must compensate. It explains the 'conversation' parameter ('Include the conversation array with recent messages for reproduction') but provides no guidance for 'context' or elaborates on 'message' beyond being the core content. This is insufficient for full parameter understanding.

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 action ('Report a bug, missing feature, or send feedback') and identifies the resource (bug/feature/feedback). It distinguishes itself from unrelated siblings like authenticate, connect, and show_version by specifying a distinct purpose.

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 explicitly indicates when to use the tool (reporting bugs, missing features, feedback) and gives a specific usage instruction (include the conversation array for reproduction). It does not mention exclusions, but no sibling alternatives are available, so the guidance is adequate.

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 readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context beyond these: the tool requires prepaid credit (costs money), involves no platform credentials, and the client is the data controller under LGPD. This enriches the agent's understanding of side effects and responsibilities, which is not covered by 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 short paragraph of four concise sentences, front-loaded with the core purpose. It includes necessary practical details (payment, legal note) without excessive verbosity. Each sentence contributes value, though the legal and payment info could be seen as peripheral. Overall, it is efficient and well-structured.

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 output schema and low schema coverage, the description should compensate by explaining parameters and expected output. It clarifies purpose, source, and costs, but omits what the query returns (e.g., a certificate document) and how to correctly use cpf vs. cnpj. For a moderately complex query tool, this is a notable gap, so it is minimally 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 input schema has two parameters (cpf, cnpj) with 0% schema description coverage. The description does not explicitly explain that cpf is for individuals and cnpj for companies, nor does it clarify their optionality or format. It only implicitly suggests tax debt lookup but offers no parameter-specific guidance, leaving the agent uncertain about how to fill these fields.

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: 'SEFAZ ES: Certidão Negativa de Débitos, consulta em fonte oficial.' It specifies the verb (consulta) and the resource (certidão negativa de débitos from SEFAZ ES). It distinguishes itself from sibling tools (authenticate, marketplace, etc.) which are unrelated, leaving no ambiguity about its function.

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?

While there is no explicit 'use when' or 'do not use when' statement, the description provides clear context: it queries official Brazilian sources, is not confidential, and involves prepaid credit. This implicitly tells the agent when to use it (for official tax debt queries) and that it's not for confidential data. However, it lacks explicit alternatives or exclusions, so I score it 4.

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 consistent with the annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false). It adds no behavioral details beyond what annotations already declare, such as output format or whether any side effects occur. Since annotations cover the safety profile, the description meets the minimum bar but does not enrich behavioral understanding.

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 delivers the complete purpose without any fluff. Every word contributes to clarity, and it is perfectly sized for a simple 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 (no parameters, no output schema, clear read-only metadata), the description is adequate for an agent to understand its function. However, it does not specify the format of the returned version information (e.g., string, object, individual fields), which could be useful if the agent needs to parse the output. This minor omission prevents a perfect score.

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 according to the rubric, the baseline is 4. The description correctly implies no inputs are needed. No additional parameter semantics are required because there are none.

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: to show current MCP platform and adapter versions. It uses a specific verb ('show') and resource ('versions'), which is unambiguous. However, it does not explicitly differentiate from sibling tools like toolkit_info, which might provide similar information, though the description's specificity reduces confusion.

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 guidance on when to use this tool versus alternatives. It simply states what it does, leaving the agent to infer usage context. There is no mention of exclusions or comparisons to sibling tools, which is a clear gap for a tool that could potentially overlap with toolkit_info.

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, destructiveHint=false, and idempotentHint=true, which the description aligns with ('Returns'). The description adds context about the specific content returned (installed MCPs, connection status, accounts, tool counts) but does not disclose any additional behavioral caveats (e.g., auth requirements, rate limits, side effects). This is adequate given the 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?

The description is a single, tightly packed sentence that front-loads the purpose ('Returns the current toolkit state') and lists precise contents without any filler or repetition. Every clause adds 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?

For a zero-parameter, read-only informational tool with annotations covering safety, the description fully specifies what the tool returns. There is no output schema, but the description enumerates all relevant data points, making it complete for its simple 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, and the schema is trivially 100% covered. The description adds no parameter information because none is needed. Per the rubric, 0 parameters warrants a baseline of 4.

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 names the resource 'current toolkit state' followed by a precise enumerations of contents (installed MCPs, connection status, accounts, tool counts). This clearly differentiates it from sibling tools like 'authenticate' (an action) and 'show_version' (which likely focuses on version details).

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 inspecting overall toolkit health and configuration but does not explicitly state when to use it over alternatives or when not to use it. There is clear context (it's a state reporter) but no exclusions or named alternative tools, so it falls into 'implied usage'.

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