ANTT SIFAMA: Download de Auto de Infração

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

Annotations already indicate read-only, idempotent, non-destructive. The description adds that it queries official Brazilian sources, is not confidential, and involves LGPD compliance for the client, which are valuable behavioral disclosures 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 concise, using three sentences to convey purpose, payment, and legal context without unnecessary padding.

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 five parameters and no output schema, the description is insufficient: it doesn't cover parameter meanings or expected outcomes, making it incomplete for an agent to use effectively.

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 does not explain any of the five parameters, despite 0% schema coverage. It fails to add meaning to login_senha, cnpj_representado, auto_infracao, etc., leaving the agent to infer their 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 downloads an infraction notice (Auto de Infração) from ANTT SIFAMA, an official source, which distinguishes it from generic sibling tools.

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 explains the tool is hosted by the platform, requires no platform credentials, and uses prepaid credit, giving context for when to use it. However, it does not explicitly mention alternatives or scenarios to avoid, but the 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 mark the operation as idempotent and non-destructive, and the description adds meaningful context: browser interaction, token copying, permanent vs session scope, and the no-args behavior of returning a login link. 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 somewhat dense but well structured: it states the audience, gives the recommended approach, then the alternative. Every sentence adds operational value, though it could be tightened slightly.

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 single-optional-parameter tool with no output schema, the description covers the complete authentication flow including permanent and session-based options. It does not describe the exact response format, but this is less critical given the simple interface.

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 zero description coverage and merely defines an optional string 'token'. The description compensates by explaining that the token is a JWT, how to pass it, and that omitting it returns the 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 explicitly states this is an authentication flow for MCP.AI IDE agents, covering browser login, token retrieval, and two usage modes. This clearly distinguishes it from sibling tools like connect 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 provides clear alternative usage paths: permanent config header vs session-only token paste, and explains when to call with no args. It does not explicitly exclude other tools, but the guidance is sufficient for selecting the right invocation.

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 the tool as read-only, idempotent, and non-destructive. The description adds meaningful behavioral detail beyond annotations by explaining the conditional response shape: authenticated:true with empty pending[] on full connection, and connect_url plus per-install URLs when credentials are missing. This is transparent about the tool's output behavior for a zero-parameter read-only status check.

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, front-loaded with the primary action and then conditionals. Every sentence provides useful information without filler. The structure is highly efficient for a tool with no parameters.

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 zero parameters, no output schema, and strong annotations, the description is complete enough. It describes the main return values and the conditional cases that matter for a status-checking tool. The description fully compensates for the lack of an output schema by explaining what the response contains.

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 is empty with 0 parameters, so there is no parameter documentation burden. The baseline of 4 applies because no parameters need semantic explanation. The description effectively focuses on the tool's behavior rather than parameter details, which is appropriate here.

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?

Description clearly states the tool returns connection status and URLs, with specific conditionals like authenticated:true and empty pending[] when all providers are connected. It distinguishes itself from the sibling authenticate tool by focusing on status inspection rather than initiating authentication. Slight ambiguity remains because it does not explicitly contrast itself with 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 description provides clear context on when results differ: when all providers are connected versus when credentials are missing, including what URLs are returned. It does not explicitly name the authenticate sibling as the alternative for initiating connections, but the usage context is clearly inferred from the status-oriented language. No exclusions or when-not-to-use guidance is provided.

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 only indicate openWorldHint and non-read-only. The description goes far beyond by explaining that invoke runs tools even if the MCP is not installed (one-off, no toolkit bloat), that writes require owner/admin, that invoke returns connect/checkout links when needed, and that installed status is flagged in search/describe. No contradiction with annotations; the description adds critical operational context.

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 well-organized, starting with the overall purpose, then the core flow, then special behaviors for invoke, then permission notes, and finally the prompt library. Each sentence adds meaningful detail, but the density could be overwhelming. It is front-loaded with the most critical info. Slightly wordy but not redundant.

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 params and multiple operational modes, the description covers the main workflows (search/describe/invoke/install), permission requirements, and the prompt library. It does not explain return formats (no output schema), nor delve into every action like report_bug or subscribe/cancel specifics. However, given the complexity, it provides a strong high-level picture and enough to guide an agent through typical use cases.

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 carries the full burden. It explains the meaning of the action enum, mcp_id, and tool_id in the flow, and touches on prompt-related params (prompt_body, prompt_slug, etc.). However, 23 parameters exist, and many like cancel_reason, report_context, request_details, immediate, tier_slug are not explained at all. The description covers the main params but leaves numerous others opaque, failing to fully compensate for the lack 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 states it is the official mcp.ai marketplace, combining a catalog of MCPs/tools and the runtime to execute them. It mentions specific actions like search, describe, install, invoke, and a separate prompt library, distinguishing it from the sibling tools (which are more focused like authenticate/report_bug). The purpose is unambiguous and high-level yet specific.

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?

Extensive guidance is provided: the core search→describe→invoke flow, when to prefer invoke over install (one-off vs permanent), permission requirements for writes (owner/admin), and how to handle missing credentials or empty wallets (connect/checkout links). It also differentiates the prompt library actions (search_prompts, get_prompt, publish_prompt) and suggests request_mcp when nothing fits. This is exemplary usage 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=false, destructiveHint=false, and idempotentHint=true. The description adds context about including the conversation array for reproduction, which is a useful behavioral hint. However, it does not disclose side effects or error behavior beyond what annotations imply, so it adds limited 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?

Two sentences total. The first sentence states the purpose clearly, and the second provides essential guidance. No wasted 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?

With 3 parameters, 0% schema coverage, and no output schema, the description must do more to explain usage. It only hints at the 'conversation' parameter, while 'message' is required but undescribed. Annotations mitigate some safety concerns, but usability suffers from missing parameter semantics.

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 parameters. It mentions the 'conversation' array for reproduction, giving some meaning, but does not explain 'message' (required) or 'context' at all. This partial coverage is insufficient for correct invocations.

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.' It uses specific verbs and resources, distinguishing it from sibling tools like 'show_version' or 'marketplace' which imply different actions.

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 clear context on when to use the tool (reporting bugs, missing features, feedback) but does not explicitly mention alternatives or exclusion criteria. It says 'send feedback' which covers a broad scope, but no 'when not to use' or alternatives are listed.

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 fully covered. The description adds marginal scoping context (that it reports BOTH platform and adapter versions) but discloses nothing about return format, which is relevant given the absence of an output schema. 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?

A single, front-loaded sentence of nine words. Every word earns its place — it states the subject, verb, and scope without fluff or redundant restatement of the tool name.

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 parameterless, read-only version tool with strong annotations, the description is nearly complete. It could optionally describe what the returned version output looks like since no output schema exists, but the trivial nature of the tool keeps this gap minor.

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 per the rubric the baseline is 4. There is no parameter information the description would need to add since the input schema is empty.

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+resource construction: 'Show the current MCP platform and adapter versions.' It clearly identifies what the tool does and distinguishes it from sibling tools like authenticate, connect, and marketplace. Even the similar toolkit_info is differentiated since this tool targets version details specifically.

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?

No explicit when-to-use or when-not-to-use guidance is provided, nor are alternatives named. Usage is only implied by the verb 'Show' — an agent can reasonably infer this tool is for retrieving version info, but the description never states when to prefer it over siblings like 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, idempotentHint=true, and destructiveHint=false, so the safe read-only behavior is established. The description adds value by detailing the exact contents of the returned state, giving the agent a richer expectation of the tool's output beyond just 'returns state'.

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 primary action and result ('Returns the current toolkit state') before enumerating the key details. Every clause adds meaningful information, with no filler or 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?

This is a simple, zero-parameter read-only tool, and the description names the main return contents (installed MCPs, connection status, accounts, catalog tool counts). Since there is no output schema, the description carries the responsibility of indicating what the result contains, and it does so adequately, though it does not specify the exact data shape or formatting.

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 empty with 100% coverage by virtue of having no properties to document. The description doesn't need to explain parameters; the baseline of 4 applies because there is nothing ambiguous 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 uses a specific verb ('Returns') and explicitly names the resource ('current toolkit state') plus the exact information included, such as installed MCPs, connection status, accounts, and catalog tool counts. This clearly distinguishes it from sibling tools like show_version or connect, which serve 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 makes the use case clear: when an agent needs an overview of installed MCPs, their status, and connected accounts, this tool provides it. It does not explicitly state when not to use it or name alternatives, but the context is sufficiently clear given its informational nature and the absence of similar sibling tools.

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