SENATRAN: Penalidade de Advertência por Escrito

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

Annotations indicate a write operation (readOnlyHint=false) and idempotency (idempotentHint=true). The description adds behavioral nuance: permanent vs session-only login, and the distinction between passing a token and calling with no args. 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 verbose and run-on, especially the second sentence. It front-loads the main purpose but could be tightened without losing meaning.

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 no output schema, the description should indicate what the tool returns or confirms success. It only mentions getting a link but does not describe the response after token submission or potential errors. Adequate but incomplete for a complex auth flow.

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 only one parameter 'token' with no description (coverage 0%). The description explicitly explains the token's purpose (session-only login) and that calling with no args returns the link, fully compensating for schema gaps.

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 tool authenticates the MCP.AI server for IDE agents, specifying the actions (log in via browser, paste token) and distinguishes from sibling tools by focusing on authentication flow.

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: use for IDE agents (Cursor, etc.), with two distinct usage modes (permanent config vs session-only token). It doesn't explicitly exclude alternatives but makes the authentication purpose unambiguous.

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 and idempotentHint. The description adds valuable context about authenticated:true, pending[], and connect_url behavior, including the case when credentials are missing, which goes 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?

Two concise sentences front-load the primary purpose and then detail conditional behavior. Every word earns its place with no 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?

Given the tool has no parameters, no output schema, and clear annotations, the description fully explains the tool's behavior, including edge cases like missing credentials. It is complete for its simplicity.

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 100% by default. The description does not need to explain parameters, and the baseline of 4 is appropriate.

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 'Returns connection status and URLs' with a specific verb and resource, and elaborates on conditional return values. It is unambiguous and distinct from the 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?

The description implies the tool is for checking connection status but does not explicitly state when to use it instead of alternatives like 'authenticate' or 'toolkit_info'. The conditional behavior is described but not framed as 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?

Beyond annotations, the description discloses key behavioral traits: invoke runs even when the MCP is not installed, returns credential/checkout links, and performs a one-off install behind the scenes. It also explains auth/permission requirements for writes, the permanent nature of install, and that prompt share links open without login. No contradiction with annotations (readOnlyHint=false, openWorldHint=true, etc.).

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 dense but well-structured, with a logical flow (core flow arrow chain, semicolon-separated action summaries, prompt library section). Every sentence carries information needed for a complex 14-action tool. It is longer than average, but appropriate for the complexity; a bit more formatting (bullets) would improve skimmability.

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 an output schema and the high tool complexity, the description is remarkably complete. It covers the full search→describe→invoke lifecycle, the one-off vs. permanent installation distinction, auth and billing failure modes (connect/link/checkout), write permission requirements, and the separate prompt library feature. No significant behavior is left unexplained.

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 0% description coverage across 23 parameters, so the description must compensate. It does explain the action enum values and the role of central params like mcp_id, tool_id, and arguments. However, many action-specific parameters (prompt_*, cancel_*, request_*, tier_slug, immediate, conversation, etc.) receive no explanation in the description, leaving the agent 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 states the tool is 'the official mcp.ai marketplace' that serves both as a catalog and a runner for MCPs/tools. It explicitly covers capability requests and walks through the core flow (search → describe → invoke), making it unmistakably distinct from sibling tools like authenticate, 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?

Usage guidance is explicit and actionable: prefer invoke for one-off/occasional use, install for permanent toolkit membership; list_tools for currently callable tools; subscribe/cancel for per-MCP billing; request_mcp for building new MCPs. It also clearly states that writes require workspace owner/admin, and explains the conditions under which invoke returns connect or checkout links.

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 cover idempotency and non-destructiveness, but the description adds no behavioral context such as authentication needs, rate limits, or side effects. It only instructs on input format, not the implications of reporting.

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, front-loads the purpose, and contains no fluff. Each word contributes to the tool's understanding.

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 mutation tool with three parameters and no output schema, this description is too sparse. It omits prerequisites, success behavior, and format details for the conversation field, leaving ambiguity for an agent.

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 tool description must explain parameters. It mentions the conversation array for reproduction but does not clarify 'message' or 'context' roles, and fails to note the conversation field is a JSON string despite being called an 'array'.

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: reporting bugs, missing features, or feedback. It uses a specific verb ('report') with distinct targets, and the conversation array instruction differentiates it from sibling tools like authenticate or 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?

The description implies usage for issue reporting but does not explicitly state when to use it versus alternatives. It advises including the conversation array for reproduction, yet lacks explicit exclusions or references to other 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 readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable context: payment per query with prepaid credit, no platform credentials needed, data is not confidential, and LGPD responsibilities. This goes beyond the annotations without contradicting them.

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 (three sentences), front-loaded with purpose, and each sentence contributes meaningful information about hosting, payment, data source, and legal compliance. No fluff 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?

Given 7 parameters, no output schema, and no parameter explanations, the description is incomplete. It does not clarify the role of optional credentials, what the query returns, or how payment is processed beyond 'prepaid credit'. An agent would struggle to correctly invoke this tool without additional info.

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%, and the description provides no explanation of any of the 7 parameters. It does not mention chave_infracao, placa, or the credential fields (login_cpf, pkcs12_cert, etc.), leaving the agent without guidance on how to populate them correctly.

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 queries 'Penalidade de Advertência por Escrito' (written warning penalty) from SENATRAN official sources. The verb 'consulta' and specific resource distinguish it from the generic sibling tools like authenticate 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?

Usage context is implied by the name and description (query official SENATRAN penalty data), but there is no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. The description mentions 'sem credenciais da plataforma' but does not clarify when to provide the optional credential parameters.

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 communicate the read-only, idempotent, and non-destructive nature. The description adds the specific scope of what is shown ('platform and adapter' versions) but not details about formatting or environment behavior. This meets the annotation-augmented bar without exceeding it.

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 wasted words. It could not be more concise while remaining 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?

For a simple version-query tool with no output schema and no parameters, the description plus annotations are nearly complete. Slightly more detail about the return format or where the versions appear would push this to a 5.

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 and 100% schema coverage, the baseline of 4 applies. The description doesn't need to explain parameter semantics here; nothing is missing.

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 verb 'Show' and the resource 'MCP platform and adapter versions'. None of the sibling tools (authenticate, connect, marketplace, report_bug, toolkit_info) overlap with a version-query purpose, making it distinct.

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?

Usage context is implied—an agent would naturally call this when version information is needed—but the description never explicitly states when to use it versus alternatives, nor does it mention sysinfo-like exclusions. For a trivial parameterless tool this is adequate but not exemplary.

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 covered. The description adds value beyond annotations by detailing exactly what data is returned (installed MCPs, connection status, accounts, catalog tool counts), giving the agent a clear behavioral model without overstating side effects.

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 immediately states the verb and object, then lists the specific information returned. Every phrase earns its place, with no fluff, redundancy, or vague wording.

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?

Even though there is no output schema, the description effectively explains what the tool will return by enumerating the state categories. Given the tool's low complexity, zero parameters, and strong read-only annotations, the description is complete enough for an agent to select and invoke it 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 baseline is 4. There are no parameter meanings to clarify, and the description instead clarifies the output semantics, which is appropriate for this schema. Nothing is missing in terms of parameter guidance.

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 a precise resource ('current toolkit state'), then enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly identifies the tool's purpose and distinguishes it 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 description implies when this tool should be used—whenever an agent needs to inspect installed MCPs, connection status, or exposed tool counts—but it does not explicitly state when to use it versus alternatives or mention any exclusions. It is adequate but leaves the usage guidance implicit rather than explicit.

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