ANTT: Calcular Piso Mínimo de Frete

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

Annotations already declare the tool as readOnlyHint and idempotentHint, but the description adds significant context: 'Hospedado pela plataforma, sem credenciais da plataforma, pague por consulta com crédito pré-pago' (hosted by platform, no credentials, pay-per-query) and clarifies data is non-confidential with LGPD compliance. This exceeds the annotations by covering billing and data privacy. It does not describe return format, but the annotated safety profile lowers the burden.

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 brief and front-loads the core function, then adds context. The second sentence is a bit of a run-on with legal/billing details, but it remains under 50 words and contains no fluff. It could be split into bullet points, but it's efficient overall.

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 six parameters, zero parameter descriptions, and no output schema, the description leaves critical gaps. While it covers the tool's data source and legal framework, it omits essential operational details like parameter formats, units, and any error/return behavior. A tool with this complexity requires much more contextual guidance.

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 carries full responsibility to explain the six string parameters (e.g., 'eixos', 'distancia'). It completely fails to do so. The parameter names are only mildly self-evident, and no units, formats, or examples are given, leaving the agent guessing.

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 opens with 'ANTT: Calcular Piso Mínimo de Frete' which is a specific action (calculate) and resource (minimum freight floor), immediately clear and distinct from siblings like 'authenticate' or 'connect'. It clearly indicates a read-only consultation, fully aligning with the tool's 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 implies usage by stating the tool calculates the freight floor from official sources, and mentions payment and LGPD compliance. However, it offers no explicit guidance on when to choose this tool over alternatives, no exclusions, and no alternatives are named. Usage is inferred from the purpose rather than stated.

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 well beyond annotations by detailing behavior: no args returns a link, token arg authenticates for the session, and config header creates a permanent non-expiring connection. This adds meaningful context about session persistence and user action, complementing the idempotentHint.

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 slightly wordy, starting with 'MCP.AI for IDE agents (Cursor, etc.)' which is context but not core to the tool's action. However, it is logically structured with 'Best' and 'Or', and all sentences provide functional value.

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 one optional parameter and no output schema, the description covers both invocation styles, the configuration alternative, and expected results (link or login). It provides sufficient context for an agent to select and invoke 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?

The input schema provides no description for the optional 'token' parameter (0% coverage). The description fully compensates by explaining the token is a JWT to paste after user login, and that omitting it produces an auth link. This is essential for correct invocation.

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 authenticates via browser login and token exchange, specifying two distinct modes (config header vs session token). This is a specific verb+resource and distinguishes from the general 'connect' sibling by focusing solely on 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?

Explicit guidance is given: use config header for permanent connection, pass a token for session-only login, or call with no args to get the link. It explains the trade-offs between modes but does not explicitly mention alternatives to the tool itself.

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 read-only and non-destructive behavior. The description adds details about the response content, providing sufficient transparency without contradicting 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 concise, two sentences, and directly conveys all necessary information without extra verbiage.

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 both possible states (all connected vs. missing credentials) and explains the return behavior, making it complete for the tool's simple scope with no output schema.

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?

There are no parameters, so schema coverage is trivially complete. The description adds no parameter-specific information, matching the baseline for zero-parameter tools.

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: returning connection status and URLs, with conditions for different states, distinguishing it from sibling tools like '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 indicates the tool's purpose but does not explicitly state when to use it versus alternatives. The usage is implied for checking connection status, but no explicit 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?

Beyond annotations (readOnlyHint=false, openWorldHint=true), the description discloses side effects and permissions: writes require workspace owner/admin, invoke runs one-off without permanent installation, and failure paths (connect link, checkout link). This is rich and non-contradictory.

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 without line breaks or bullet points, making it hard to scan. While every sentence adds value, the lack of structure hurts readability, so it earns a 3 rather than higher.

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 (23 params, multiple actions, no output schema), the description is thorough: it covers core flows, permission and billing behavior, the prompt library, and return-value hints (connect/checkout links). It is complete for a meta-tool with this scope.

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 carry parameter meaning. It explains key parameters like action, mcp_id, tool_id, arguments, and prompt_* in context. It does not exhaustively cover every one of the 23 params (e.g., cancel_reason enum details), but it meaningfully guides on the most critical ones, earning a 4.

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 the tool is the official mcp.ai marketplace, covering discovery and execution of MCPs. It clearly differentiates from sibling tools by being a meta-catalog, and names specific capabilities 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?

Provides a clear core flow (search→describe→invoke) and explicit guidance on when to use invoke vs install, and how to handle billing/auth link scenarios. It also clarifies when to use other actions like list_tools, subscribe, and the prompt library, completely fulfilling when/to-use-and-when-not-to.

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 adds the useful behavioral detail to include conversation history for reproduction, but it does not explain what happens after reporting (e.g., submission, side effects). Annotations provide idempotentHint=true and destructiveHint=false, which are not contradicted. The added context is minimal 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?

A single, front-loaded sentence that communicates the core purpose and a key usage instruction. 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?

For a simple three-parameter tool with no output schema, the description covers the purpose and the most important parameter (conversation). It lacks details on the 'context' parameter and the meaning of idempotent behavior, but overall it is reasonably complete for this simplicity level.

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 explicitly explains the 'conversation' parameter as a reproduction aid, but does not clarify the 'context' parameter. The required 'message' is implied by the purpose, but not fully defined. Partial compensation for missing 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 'Report a bug, missing feature, or send feedback' with a specific verb and resource. It fully distinguishes the tool from the unrelated sibling tools (freight inquiry, authentication, etc.).

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 when-to-use guidance for reporting bugs/feedback and explicitly instructs to include the conversation array for reproduction. It does not mention exclusions or alternatives, but none are needed given the unrelated 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety expectations. The description adds no additional behavioral context (e.g., rate limits or response format), but for a read-only version tool this is acceptable. 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, efficient sentence that conveys the entire purpose. There is zero wasted wording, and it is front-loaded with the verb 'Show' followed by the specific subject matter.

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 trivial complexity (no parameters, no output schema), the description is fully sufficient. It clearly states what the tool returns (version information) without needing to elaborate further.

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 remaining at 100% schema coverage, the baseline for parameter semantics is 4. The description correctly omits parameter details since there are none, and the empty schema requires no compensation.

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 resource ('current MCP platform and adapter versions'), making the tool's purpose unambiguous. It also implicitly differentiates from siblings like 'toolkit_info' by focusing specifically on version 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 implies usage as a simple informational query with no preconditions or side effects. However, it does not explicitly state when to prefer this over alternatives or when not to use it, though the simplicity of the tool makes this less critical.

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 safety is covered. The description adds value by detailing what the read-only operation returns, including connection status and per-MCP account/tool counts, which goes beyond the bare 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, front-loaded sentence that lists the key returned information without filler. Every phrase contributes meaningful detail about the tool's output.

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 adequately explains what the tool returns: installed MCPs, connection statuses, connected accounts, and catalog tool counts. No critical gaps are apparent.

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 has zero parameters and 100% schema description coverage, so there is no parameter burden. As a no-parameter tool, the description appropriately avoids inventing unnecessary parameter 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 the specific verb 'Returns' and clearly identifies the resource as 'current toolkit state', listing concrete details (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from siblings like show_version 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 provides clear context: use this tool to inspect the current toolkit state and its components. It does not explicitly name alternatives or exclusions, but the intent is unambiguous given the tool's scope.

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