SEFAZ DF: Certidão de Dívida Ativa

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

It discloses important behavior beyond the annotations: permanent config vs session-only token, and the no-argument behavior of returning a login link. There is no contradiction with the annotations, though it does not describe what happens on invalid tokens or how the tool reports success/failure.

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 compact and front-loaded: it states the purpose, then the permanent setup, then the session-only invocation options. The phrasing is slightly awkward in places, but every clause adds meaningful guidance.

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-parameter authentication tool with sparse annotations and no output schema, the description provides enough context to use the tool for permanent configuration, session-based login, and link retrieval. It could be more explicit about exact response behavior and error cases, but it is largely 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 only defines 'token' as a string with no description, but this description adds key semantics: the token is an access JWT, it is optional, it is used for session-only login, and omitting it returns a login link. This is strong compensation for the 0% schema description coverage.

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 flow for MCP.AI in IDE agents: the user logs in through the browser, obtains an access token, and either configures it permanently or passes it to the tool. It does not explicitly contrast itself with the sibling tool 'connect', so it narrowly misses full differentiation.

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 clear usage branches: use the config header for a permanent connection or call the tool with a token for session-only login, and call with no arguments to receive the login link. It does not explicitly address when not to use the tool or name alternatives.

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 mark it as read-only, idempotent, and non-destructive. The description adds valuable context by detailing the output shape under different conditions (authenticated:true with empty pending[] vs connect_url), which helps the agent predict results. 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 concise sentences, front-loaded with the primary purpose, and then explains conditional outputs. Every sentence adds value 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 simple status-check tool with no parameters and no output schema, the description covers the essential possible outcomes. It doesn't mention error cases or integration with siblings, but given its simplicity, the provided details are sufficient for an agent to understand what to expect.

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 coverage is effectively 100%. The description doesn't need to explain parameters and correctly focuses on behavior. The baseline for zero parameters is 4, and the description meets that standard without unnecessary elaboration.

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, which is a specific verb-resource pair. It distinguishes itself from siblings like 'authenticate' by focusing on checking status rather than initiating authentication, though it doesn't explicitly contrast. the conditional outputs (authenticated:true vs connect_url) add specificity.

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 the tool's behavior in different scenarios (all providers connected vs missing credentials), implying it's for checking status. However, it doesn't explicitly state when to prefer this over 'authenticate' or mention any exclusions, leaving some ambiguity about its role relative to the authentication flow.

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 major safety and side-effect context: writes require workspace owner/admin, invoke runs tools without installing them, credential-less scenarios return connect links, and unpaid paid tools return checkout links. None of this contradicts the annotations, which are sparse, so the description carries the burden well.

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 does not waste words: almost every sentence adds a distinct capability or decision rule. The main downside is its dense one-paragraph-format which makes the action-specific semantics harder for an agent to scan 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?

The description covers nearly all actions in the action enum and gives core workflows, side effects, and fallback links. It is not quite complete because the resume action is never mentioned, parameter details are uneven, and there is no output-shape guidance—though no output schema exists either.

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 does heavy lifting by explaining action, mcp_id, tool_id, arguments, and prompt-related variables/variables/links. However, many parameters remain unexplained—such as immediate, tier_slug, conversation, cancel_reason, report_context, request_details, and prompt_title—so the agent would still need to infer their meaning from names alone.

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 mcp.ai marketplace catalog and execution engine, and distinguishes it from the sibling tools (authenticate/connect/etc.) by framing search → describe → invoke as its core flow. It names concrete actions and resources, making the purpose unambiguous.

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 decision guidance: prefer invoke for one-off use and install only to make an MCP permanent, list_tools shows what is callable now, and request_mcp is for cases where nothing fits. It also clarifies prompt-library actions separately, so the agent knows when to use this tool versus alternatives.

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: false, destructiveHint: false, and idempotentHint: true. The description adds the behavioral note to include the conversation array for reproduction, which gives some insight into expected input. However, it doesn't disclose outcomes, side effects, or error handling, so it only partially enhances 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 two sentences long, front-loads the core purpose, and provides a specific instruction (include conversation array) without any fluff. Every word adds value, making it highly efficient.

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 bug-reporting tool, the description is adequate but not thorough. It lacks details on response format, whether a report is created immediately, or any validation rules. Since there's no output schema and the operation is side-effectful, a bit more context (e.g., what happens after submission) could improve completeness, but it's not critically deficient.

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, but it only addresses one parameter ('conversation') by mentioning the array for reproduction. The 'message' and 'context' parameters are not explained, and there is no clarification on their purpose or format. This leaves the agent with incomplete semantic 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 tool's purpose: 'Report a bug, missing feature, or send feedback.' This is a specific verb+resource combination that is unambiguous. It also distinguishes itself from sibling tools like 'authenticate' or 'marketplace' by focusing on feedback/discrepancy reporting, making its role obvious.

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 (for bugs or feedback) but provides no explicit guidance on when not to use it or alternatives. It doesn't mention any exclusions or compare itself to other tools, leaving usage context implied rather than 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. The description adds valuable context: it is hosted by the platform, requires no platform credentials, incurs prepaid per-query costs, queries non-confidential official data, and holds the client responsible under LGPD. This goes beyond the annotations and sets clear expectations for side effects and compliance, though it could detail data handling or failure modes.

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 paragraph of four sentences. It is relatively concise but bundles core purpose with billing, hosting, and legal disclaimers in a way that buries the lede. While not overly long, the structure could be improved by front-loading the tool's function before discussing payment and LGPD, making it slightly less scannable.

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 query tool with two optional parameters and no output schema, the description covers non-functional aspects (payment, LGPD) but omits crucial functional details: it never clarifies that users should provide a CPF or CNPJ, nor what kind of result to expect. It does not mention any constraints, validations, or error conditions, leaving an agent with insufficient information 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?

Schema description coverage is 0%, so the description must explain the parameters. It does not mention 'cpf' or 'cnpj' at all. The tool has two optional parameters with no required fields, but the description gives zero indication of how to use them, whether one is needed, or what input format is expected. This is a critical failure given the absence of schema descriptions.

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 a query for 'Certidão de Dívida Ativa' from SEFAZ DF via 'consulta em fonte oficial'. The verb+resource structure is explicit, and the specific government source differentiates it from generic siblings. However, it does not state what the return value looks like (e.g., certificate content vs. status), and the purpose is slightly muddled by billing/LGPD 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 gives no direct guidance on when to use this tool versus alternatives. It implies usage for querying official Brazilian tax debt data but does not state prerequisites (e.g., needing CPF or CNPJ), exclusions, or when a different tool would be more appropriate. The mention of 'pay per query' is contextual but not a usage guideline.

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?

Behavioral transparency is already provided by annotations (readOnly, idempotent, non-destructive). The description adds no further behavioral details, such as side effects or limitations, but it does not contradict the annotations either.

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 states the tool's purpose with no unnecessary detail 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?

Given the tool's simplicity (no parameters, no output schema), the description is complete. It fully conveys what the tool does, and there is no missing information that would hinder 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?

The tool has no parameters, and the description accurately reflects this. No additional parameter explanation is needed.

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 MCP platform and adapter versions. The verb 'Show' is specific and the resource is well-defined, distinguishing it from sibling tools like 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 does not mention when to use this tool versus alternatives. It simply states the action without providing context or explicit guidance, such as when version information is needed or how it compares to similar tools.

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 this as read-only, idempotent, and non-destructive, so the description only needs to add content-level context. It does this well by specifying exactly what the returned state includes, providing value beyond the structured 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 front-loads the primary action and then efficiently packs the key output dimensions. No filler, redundant phrasing, 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?

For a zero-parameter, read-only status tool with no output schema, the description provides a sufficiently complete picture of what the caller will receive. It covers the main categories of returned information without requiring an output schema to be useful.

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 is trivially complete. With no parameters to document, the description appropriately focuses on the output contents instead, matching the baseline for a no-parameter tool.

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 names a concrete, bounded resource: the current toolkit state. It enumerates distinct content categories (installed MCPs, connection status, connected accounts, catalog tool counts), making it clearly distinguishable from siblings like show_version or authenticate.

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 phrase 'current toolkit state' clearly implies this is the inspection/status tool for the overall toolkit setup. It doesn't explicitly name alternatives or exclusion cases, but the context and sibling list make the intended use evident.

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