IBAMA: Certidão de Débitos

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

The description adds useful behavioral context beyond the annotations: permanent vs session-only auth, no-args returning the login link, and the use of a JWT. However, it does not describe failure behavior, what the response payload looks like, or edge cases such as already-authenticated sessions, so it is only moderately transparent.

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, covering the auth flow, the permanent-config option, and the session-only path in a few sentences. Some phrasing is slightly instructions-like rather than a clean tool specification, but no sentence is 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?

For such a small 1-parameter tool, the description is fairly complete: it tells the agent how to invoke the tool and what to expect in the main happy paths. It is incomplete regarding errors, response structure, and session expiry behavior, and it has no output schema to make up for that.

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 has one optional string token with zero description coverage, so the description must explain the parameter. It does: token is the JWT pasted by the user, and omitting it returns the login link. This is helpful and largely compensates for the schema's lack of 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 states this is the MCP.AI authentication/login tool: it returns a browser login link when called with no args and accepts a pasted JWT token to complete a session login. This is specific enough to distinguish it from sibling tools such as connect, marketplace, or report_bug.

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 instructions for two usage paths: a permanent connection via a server config Authorization header and a session-only login via a pasted token or no-args link. The main gap is that it does not explicitly contrast this tool with the 'connect' sibling or say when to favor tool-based authentication over config-based authentication.

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 it as read-only and idempotent. The description adds valuable context about output variations (authenticated:true with empty pending vs. connect_url for missing credentials), which goes beyond the annotations and helps the agent understand expected responses.

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—two sentences that front-load the core purpose and then detail the two possible outcomes. Every sentence adds value, with no redundancy or fluff.

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 no-parameter tool with no output schema, the description covers the main outcomes (all connected vs. missing credentials) and explains the returned URLs. It's sufficient for the agent to understand what to expect, though it doesn't elaborate on other edge cases (e.g., partial connections).

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 shows an empty properties object. The description doesn't need to explain parameters since none exist; the baseline of 4 applies as there's nothing to compensate for.

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, with a specific verb ('returns') and resource (connection status). It distinguishes itself from siblings like 'authenticate' by focusing on status checking, though it doesn't explicitly contrast with 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 implies this is for checking connection status, and given sibling 'authenticate' exists, it's implied to be used for querying rather than initiating auth. However, it doesn't explicitly state when to use this tool or mention alternatives, so guidance is only implied.

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 tell the agent this is read-only, idempotent, and non-destructive. The description adds meaningful context beyond that: the operation is metered/prepaid, the tool uses official public sources, no platform credentials are needed, and LGPD data controller responsibilities apply. This is useful behavioral and compliance disclosure.

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 compact Portuguese paragraph that front-loads the purpose and then adds necessary operational and legal caveats. It is slightly heavy on compliance language, but each sentence contributes relevant information and it avoids unnecessary 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?

The description covers intent, source officiality, payment, credentials, and privacy obligations, but it does not describe what the response contains, whether a CPF, CNPJ, or name is required, or how to format identifiers. Given the dependency on the schema is high — and the schema is sparse — the description leaves relevant operational gaps.

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 provides no guidance about the parameters cpf, cnpj, or nome. Schema description coverage is 0%, and there are no format hints, required-parameter instructions, or combination rules in the description, which is risky because an agent cannot tell whether one of the three identifiers must always be supplied.

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 (IBAMA Certidão de Débitos) and the action (consulta em fonte oficial). It also differentiates itself from the sibling tools, which are generic platform tools like authenticate or marketplace, by specifying a concrete domain query 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 gives useful usage context: the data is public, non-confidential, available to citizens, and the query is paid via prepaid credit, with no platform credentials required. It does not explicitly name an alternative or say when not to use it, but it gives clear conditions for legitimate use.

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?

With annotations only indicating openWorldHint and readOnlyHint, the description adds substantial behavioral context: invoke runs uninstalled MCPs one-off, returns a connect link when credentials are needed, returns checkout/top-up when payment is required, and requires workspace owner/admin for writes. It also explains the prompt library's login-free share links, going well beyond 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 lengthy but earns its length: it front-loads the core flow, uses clear separators (core flow, KEY, install vs invoke, prompt library), and every clause adds a meaningful distinction. The structure helps navigate the large action space without wasted 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?

For a 23-param, 14-action multiplexer with no output schema, the description covers the main workflow, auth, billing, installation, and prompt library very thoroughly. Minor gaps remain: the 'resume' action is not mentioned, and params such as immediate, tier_slug, and request_details receive no explanation.

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% across 23 parameters, and the description compensates by explaining the semantic roles of key fields: action values, mcp_id, tool_id, prompt_slug, and the invoke/install distinction. However, it does not clarify individual params such as limit, immediate, tier_slug, cancel_reason, or prompt_vars, leaving some burden on 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 states this is the official mcp.ai marketplace: a catalog of MCPs/tools and the way to run them. It lays out the core search → describe → invoke flow and enumerates secondary capabilities (install, billing, report_bug, request_mcp, prompt library), so the agent understands exactly what the tool is for.

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: prefer invoke for one-off use, use install to make an MCP permanent, use list_tools to see what is callable now, use request_mcp when nothing fits, and use subscribe/cancel for billing. It also names alternatives and workflow exclusions, which is model behavior for this dimension.

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, destructiveHint=false, and readOnlyHint=false, so the safety profile is covered. The description adds the instruction to include the conversation array, which is usage guidance rather than behavioral disclosure. No contradictions exist, but it doesn't add extra context about side effects or return behavior.

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: the first states the purpose, the second provides a usage tip. It is front-loaded and every sentence serves a purpose. No fluff.

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 a description in the schema and no output schema, the description should elaborate on parameters and expected behavior. It only mentions the conversation array, leaving 'message' and 'context' unexplained, and does not describe what happens after reporting. The tool is simple, but the description is minimal and leaves gaps.

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 that 'conversation' should contain recent messages for reproduction, but it does not explain 'message' (the required field) or 'context'. This is insufficient given the low 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 states the purpose: 'Report a bug, missing feature, or send feedback.' This uses a specific verb (report) and resource (bug/feedback), and it distinguishes from sibling tools (authenticate, connect, etc.) which have unrelated purposes. No ambiguity.

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 context for when to use the tool (to report issues or feedback) and even includes a usage hint ('Include the conversation array with recent messages for reproduction'). However, it does not explicitly mention when not to use it or suggest alternatives, so it fails to meet the highest bar.

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 cover the safety profile. The description adds the specific scope of versions reported (MCP platform and adapter versions), but does not disclose additional behavioral details such as whether the call hits a network endpoint or returns cached values.

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 with no filler or redundant content. It earns its place by clearly stating the tool's purpose in the fewest possible 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?

This is a simple, zero-parameter, read-only version query with strong annotations, so the description need not be elaborate. It conveys both the MCP platform and adapter version aspects, though it does not specify the exact return shape; the absence of an output schema makes a slightly more explicit response format potentially valuable.

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 coverage is effectively 100%, so the description has no parameter semantics burden. The baseline of 4 applies because no parameters exist and nothing needs 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 uses a specific verb ('Show') and names the exact resource ('current MCP platform and adapter versions'), making the tool's purpose clear. It does not explicitly distinguish itself from the sibling tool 'toolkit_info', though the focus on version information is reasonably unique.

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 or any exclusions. With siblings like 'toolkit_info', some indication of when to prefer 'show_version' would have been helpful.

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 aligns with annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false) by stating it 'Returns' state rather than mutating anything. It adds value beyond annotations by detailing exactly what state is exposed (installed MCPs, connection status, connected accounts, catalog tool counts), which is useful for the agent to predict the response shape.

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-structured sentence that front-loads the main action ('Returns the current toolkit state') and then lists the specific data elements. Every clause contributes meaning with 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 simple, parameterless read-only tool with no output schema, the description covers the main return categories (installed MCPs, connection status, accounts, catalog counts) adequately. It could specify value formats or edge cases, but such depth is not necessary for an informational snapshot tool given the annotations.

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 is trivially complete (100% coverage) and no parameter documentation is needed. The baseline for 0-parameter tools is 4, and the description correctly omits any unnecessary param details.

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 the exact resource ('current toolkit state'), then enumerates the contents (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from 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 makes the use case obvious: call this when you need an overview of the toolkit's installed components, their connection status, and associated accounts. It doesn't explicitly name alternatives or exclusions, but as a read-only status tool the context is clear, and no when-not guidance is needed given the sibling set.

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