SEFAZ MS: Certidão Negativa de Débitos

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

Beyond the annotations (idempotent, non-destructive), the description discloses real behavioral detail: what happens with no args, what happens when a token is pasted, and how to achieve a non-expiring connection via config. There is 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 compact, front-loaded with the purpose, and every sentence conveys a distinct actionable detail (browser flow, permanent config, session token flow). Formatting with colons and inline code keeps the optional paths easy to parse.

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 one-optional-param tool with no output schema, the description covers all call variants and their outcomes (link, session token, permanent header). It does not specify the exact return payload for successful token authentication or error behavior, but the core user/agent workflow is 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 schema only defines token as an optional string with no description (0% coverage). The description compensates by explaining that token is an optional JWT to be passed after the user pastes it, and that omitting it returns the login link. It does not provide validation constraints, but it gives enough semantics 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 identifies an authentication action for the MCP.AI server: it explains that calling with no args returns a browser login link and calling with a token completes a session-only login. It distinguishes use cases within the tool, but it does not name or contrast sibling tools such as connect, so sibling differentiation is absent.

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 explicit invocation guidance: the recommended permanent approach is to add the Authorization header to server config, while passing a pasted JWT provides session-only auth, and no arguments yields the login link. This is strong 'when/how' guidance, but there is no explicit when-not-to-use instruction or alternative-tool comparison.

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 behavioral outcomes based on connection state, including the return of 'authenticated:true' and 'empty pending[]' when all providers are connected, and 'connect_url' when credentials are missing. This goes well beyond the read-only and idempotent hints, providing rich context on what the tool returns.

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 well-structured, using two sentences to convey the main purpose and then the conditional behaviors. It avoids redundant words and is easy to parse.

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 covers the two primary scenarios (all connected vs missing credentials) but does not elaborate on potential error cases or edge conditions. Given the tool's simplicity and lack of parameters or output schema, this is sufficiently complete for a status check.

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 no parameters, so the description adds no parameter-specific information. Since the schema fully covers this aspect (zero parameters), the baseline score of 4 is appropriate as there is nothing to add.

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: it returns connection status and URLs. It provides specific details about two possible outcomes, which makes its function unambiguous and distinct from sibling tools like 'authenticate' or '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 describes what the tool does but does not explicitly guide when to use it versus alternatives. It lacks a clear usage directive, such as 'use this to check if all providers are connected' or 'use this to determine if authentication is needed before proceeding.'

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 indicate readOnlyHint=false and destructiveHint=false, and the description adds context by explaining that writes require owner/admin, that invoke may return connect or checkout links, and that invoke runs one-off without installation. It does not contradict annotations and covers key side effects without being exhaustive.

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 highly structured and information-dense. It front-loads the core purpose and flow, then covers key behaviors, permissions, and the separate prompt library. Each sentence adds value, and the length is justified given the tool's broad scope.

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 23 parameters, no output schema, and many actions, the description covers the essential context: search/describe/invoke flow, installation vs. one-off, auth and payment handling, permission requirements, and the prompt library. It does not exhaustively detail every action's return format, but it provides a solid framework for 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?

Schema description coverage is 0%, but the description compensates by explaining the core 'action' enum values (search, describe, invoke, install, etc.) and their roles in the flow. It also references parameters like mcp_id, tool_id, arguments, and prompt_slug, giving enough context to use the tool, though not every one of the 23 parameters is elaborated.

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 executes a wide range of actions (search, describe, invoke, install, prompt library). It explicitly distinguishes it from sibling tools by outlining its unique role as a catalog and execution engine, and it details the core flow from search to invoke.

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 extensive usage guidance: it explains when to use invoke vs install ('prefer invoke for a single/occasional use'), explicitly names alternatives like search_prompts for prompt text, and notes the permission requirements for writes (owner/admin). It also flags the key behavior of invoke working without installation.

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 convey that the tool is not read-only, is not destructive, and is flagged idempotent. The description adds useful context about including recent conversation messages for reproduction, but does not disclose side effects such as where the report goes or what response to expect. No annotation contradiction is present.

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 states the tool's purpose and the key caller requirement. 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?

For a simple reporting tool, the description gives enough to understand the basic call, especially with annotations covering safety traits. However, no output schema exists, and the description leaves the return/feedback behavior and the 'context' parameter ambiguous, so it is only 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?

Schema description coverage is 0%, so the description must compensate. It only clarifies the 'conversation' parameter as containing recent messages for reproduction, and even calls it an 'array' while the schema types it as a string. The required 'message' parameter and the 'context' parameter are not meaningfully explained.

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 specific action verbs ('report', 'send') and names the resources (bug, missing feature, feedback), making the tool's purpose immediately clear. It also distinguishes itself from sibling tools like connect and show_version by emphasizing reproduction of issues.

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 states clear use cases ('a bug, missing feature, or send feedback') and advises including the conversation array for reproduction. However, it does not explicitly say when not to use this tool or name alternatives, though none of the sibling tools appear to overlap.

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 readOnly and idempotent annotations, the description discloses several behavioral aspects: it is hosted by the platform, requires no credentials, operates on a prepaid credit system, and clarifies data sensitivity (non-confidential) and LGPD compliance responsibilities. This adds significant transparency about pricing, authentication needs, and data governance, exceeding the annotation-only baseline.

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 contains redundancy, e.g., repeating 'consulta em fonte oficial' and 'consulta informação de fontes e órgãos oficiais'. It also includes legal jargon (LGPD) that could be condensed. While not excessively long, it is wordier than necessary and could be streamlined for clarity.

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 covers many important contextual aspects: official source, payment model, credential requirements, data sensitivity, and LGPD responsibility. It does not describe the return format, but since the tool is clearly for obtaining a certificate, the output is implied. Given the tool's simplicity, this level of detail is largely complete, though it could be enhanced by specifying expected output or any prerequisites.

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 description gives no explanation of the parameters (ie, cpf, cnpj). Schema coverage for parameter descriptions is 0%, so the description was expected to compensate. It does not mention what each identifier stands for or when to use which. The only hint is the tool name itself, which implies tax-related identifiers, but no explicit mapping is provided. This leaves the agent without guidance on parameter selection.

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: it queries an official source for a negative debt certificate (Certidão Negativa de Débitos) from SEFAZ MS. This is a specific verb ('consulta') and resource, and it distinguishes itself from sibling tools like 'authenticate' or 'connect' which serve 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 useful usage context: it is a paid service (requires prepaid credits), requires no platform credentials, and is used for querying official Brazilian sources. While it does not explicitly mention alternatives (none exist among siblings), it implies the appropriate scenario—when a user needs official tax certificate data without additional authentication. This is more informative than the mid-example but lacks explicit 'when to use' or 'when not to use' 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, and the description adds 'current' to clarify the temporal scope. However, it does not disclose any additional behavioral traits such as output format or potential side effects, though none are expected for a read-only 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 sentence, front-loaded with the action, and contains no unnecessary words. It is maximally concise while still being informative.

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 a trivial purpose, the description is complete. It tells exactly what the tool does, leaving no ambiguity. The companion annotations further clarify its non-destructive, read-only nature.

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% (vacuously). The baseline for 0 parameters is 4, and the description does not need to explain parameter semantics since 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 uses a specific verb 'Show' and a clear resource 'current MCP platform and adapter versions', making the tool's purpose immediately obvious. It clearly distinguishes itself from sibling tools like authenticate or connect, as it is purely informational.

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 its usage: when you need to know the current MCP platform and adapter versions. No explicit alternatives or exclusions are given, but for a simple version-check tool, the context is clear and no exclusions are necessary.

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 covered. The description adds value by detailing the exact content returned (installed MCPs, statuses, accounts, tool counts), which is beyond what annotations provide. No contradictions.

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 purpose ('Returns the current toolkit state') and lists specifics without any filler. Every word 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 simple read-only tool with no output schema, the description adequately lists the return contents. It could mention the output format, but the substance is sufficient for an agent to know what to expect. A score of 4 reflects solid completeness without unnecessary verbosity.

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 zero parameters, the schema trivially covers 100%. The description does not need to explain parameters. Baseline for zero params is 4, and the description adds no misleading 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?

The description clearly states the tool 'Returns the current toolkit state' with specific details: installed MCPs, connection status, accounts, and catalog tool counts. This verb+resource+scope is precise and distinguishes it from siblings like 'connect' or '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 implies this tool is for querying status, but it does not explicitly state when to use it versus alternatives, nor mention any exclusions or prerequisites. For a read-only info tool, the purpose is clear, but there is no explicit usage guidance.

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