Procuradoria Geral do Estado SP: Certidão Negativa de Débitos Tributários

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

Annotations already declare readOnly=false, idempotent=true, destructive=false. The description adds context about the login flow and token type, but doesn't go into potential side effects or state changes. It does not contradict 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 dense sentence containing all necessary usage scenarios. It could be better structured, but it's not overly verbose and each clause serves a purpose.

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 tool with one optional param, the description covers both invocation patterns and the alternative config method. It doesn't specify the exact return value, but mentions receiving a link, which is sufficient 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?

The schema only defines 'token' as an optional string with no description. The description compensates by explaining that the token is a JWT and when to include it, and that omitting it returns a login link.

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 role in authenticating MCP.AI for IDE agents, describing the login flow and token exchange. It specifies both invocation modes (with or without token) but doesn't explicitly distinguish it from 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?

It provides clear instructions on when to call with a token (after user pastes) and when to call without args (to get the link), and also mentions the alternative of configuring the server permanently. However, it doesn't explicitly contrast with alternative tools, only with the config approach.

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 readOnly, idempotent, and non-destructive behavior; the description adds concrete behavioral details about the response shape, including authenticated, pending[], connect_url, and per-install URLs under missing credentials. 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?

The description is two sentences with no filler. The key action and primary outputs are front-loaded, and the conditional details are compactly presented.

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 covers normal and missing-credential cases and describes the main return fields. With annotations indicating safe read-only behavior and no output schema, this is sufficient context for an agent to invoke 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 tool has zero parameters, so the input schema fully covers any parameter concerns. The description correctly avoids inventing parameters and instead describes the tool's output 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 uses the specific verb 'Returns' with a clear resource: connection status and URLs. It explicitly distinguishes itself from sibling tools 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?

It provides clear situational guidance: when all providers are connected vs when credentials are missing, and what response to expect. It doesn't explicitly name alternatives, but the context strongly implies this is for checking status rather than initiating auth.

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 goes far beyond the annotations, disclosing that invoke runs without installing, requires owner/admin for writes, and returns authentication or payment links when needed. It details side effects (e.g., 'without bloating the tool list') and permission requirements, which are not present in 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, dense paragraph containing a wealth of information, but it lacks structure (no bullet points or headings) and includes a non-English word ('pontualmente'), which slightly hampers readability. While every sentence carries value, it could be better organized for an AI to parse quickly.

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 and the absence of an output schema, the description covers core workflows, permission requirements, billing edge cases, and the prompt library in depth. It anticipates common failure points (e.g., missing credentials, empty wallet) and explains how to handle them, making it highly complete for an agent needing to use 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?

With 0% schema coverage, the description compensates by explaining the meaning of key actions (search, describe, invoke) and the workflow, including tool_id and arguments implicitly. It also explains prompt-related actions (search_prompts, get_prompt, publish_prompt) and variable substitution. However, it does not enumerate all 23 parameters, leaving some (e.g., limit, query, cancel_reason) to be inferred.

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 — the in-platform catalog of every MCP/tool, AND the way to run them', specifying both a concrete resource (MCPs and prompt library) and its role as an execution engine. It distinguishes itself from sibling tools (authenticate, connect, etc.) by focusing on discovery and invocation, using specific action verbs like 'search', 'describe', and '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?

It provides explicit when-to-use guidance: prefer 'invoke' for one-off use vs 'install' for permanent additions, and covers alternatives like 'report_bug' and 'request_mcp'. It also explains the conditions under which connect/checkout links are returned, giving clear decision criteria for selecting this tool over others.

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 that the tool requires no credentials and is a paid query service, which are behavioral aspects beyond the readOnly and idempotent annotations. It also confirms that the data consulted is not confidential and clarifies data controller responsibilities, aligning with the non-destructive nature.

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 verbose, containing multiple legal disclaimers about LGPD and data control that are likely unnecessary for basic tool usage. While it is not extremely long, the extra boilerplate detracts from conciseness and could be trimmed to focus on essential operational 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 lack of parameter explanations and no output schema, the description is incomplete for practical use. It provides some context about the source and payment model, but missing parameter semantics and output expectations prevent a user from effectively invoking the tool.

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 includes six parameters (cpf, cnpj, login_cpf, login_senha, pkcs12_cert, pkcs12_pass) but the description provides no explanation for any of them. Users are left to guess which parameters are required, their formats, or their purposes, making this a critical gap.

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: consulting a negative tax debt certificate from the São Paulo State Attorney General's Office. It specifies the official source and includes relevant disclaimers about data handling, distinguishing it from sibling tools like authentication or reporting.

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 mentions that the service is paid with prepaid credits and is hosted on the platform, but it does not provide guidance on when to use this tool versus alternatives. There is no explicit comparison or situational advice, leaving usage context ambiguous.

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 safety hints (readOnlyHint false, idempotentHint true, destructiveHint false). The description adds the instruction to include a conversation array for reproduction, which is a useful behavioral note but does not go into depth about side effects or output. No contradiction.

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: first declares purpose, second provides a key usage instruction. No unnecessary words.

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 tool with 3 parameters and no output schema, the description provides enough to understand what to do, though it could clarify the 'context' parameter and expected behavior.

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 has 0% description coverage, so the description must clarify parameters. It explains the purpose of 'conversation' ('Include the conversation array with recent messages for reproduction') but leaves 'context' undefined. The 'message' parameter is self-evident from the tool's purpose.

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: 'Report a bug, missing feature, or send feedback.' This specific verb+resource distinguishes it 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?

It gives clear context for use (reporting bugs/feedback) but does not explicitly state when not to use it or name alternatives. Since sibling tools are unrelated, this is acceptable but not 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 specify readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is clear. The description adds the specific content: it returns MCP platform and adapter versions. This adds context beyond annotations, though the lack of output format details (e.g., structured vs plain text) is a minor gap, but for a simple version tool it's sufficient.

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, concise sentence that conveys the essential information with no unnecessary words. It is front-loaded, clear, and to the point. This is ideal for a tool of this simplicity.

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 with no parameters, no output schema, and clear annotations. The description fully covers what the tool does. The only minor omission is specifying the format or structure of the returned version info, but that's not critical. The tool is complete enough for an agent to use 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 tool has no parameters, and the schema has zero properties. The description doesn't need to explain parameters since there are none. The description correctly focuses on the output, which is the main value. With no parameters, a baseline of 4 is appropriate because the description fully addresses what the tool does without requiring param 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 clearly states the tool's function: showing version information for the MCP platform and adapters. It uses specific terms ('current MCP platform and adapter versions') and distinguishes itself from sibling tools like authenticate, connect, or marketplace, 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 implies that this tool is used to check version info, but it doesn't explicitly state when to use it or contrast with alternatives. However, given the simplicity of the tool and its clear purpose, the usage context is obvious enough. The absence of exclusions or alternatives is acceptable here because the tool is self-contained and unique among siblings.

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 readOnly and idempotent, and the description adds transparency about the returned data (state details). However, it does not mention any potential side effects, errors, or assumptions beyond what is stated. Since annotations cover the basic safety profile, the description adds some value but not extensive additional transparency.

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, concise sentence that directly conveys the tool's function without unnecessary words. It is well-structured and front-loaded with the key action and resource, making it easy to scan.

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 that there is no output schema, the description provides a sufficiently detailed breakdown of what the tool returns (installed MCPs, connection status, accounts, and catalog tool counts). This gives the agent a clear expectation of the response content, making the description complete for its 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 no parameters, as indicated by the empty schema and the absence of any parameter descriptions. There is no ambiguity or need for further clarification; the absence of parameters is clear from the schema, so the description need not address them.

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 ('Returns') and a precise resource ('current toolkit state'), detailing the exact information provided (installed MCPs, connection status, accounts, and catalog tool counts). This distinguishes it from sibling tools focused on authentication, connection, or reporting bugs, though it does not explicitly name them.

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 does not provide any explicit guidance on when to use this tool versus alternatives. It only describes what the tool returns, without mentioning typical scenarios or cases where it should be preferred over sibling tools. There is no reference to 'use this when' or 'instead of'.

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