PIS (Ministério do Trabalho)

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

The description covers behavioral traits beyond annotations: permanent versus session-only login, browser flow, and configuration options. It adds context about token expiration and non-expiring connections. Annotations indicate idempotent and non-destructive, and the description does not contradict these; it enhances understanding.

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 three sentences and front-loaded with the primary action. It includes extra context like 'MCP.AI for IDE agents' and parentheticals, which are useful but slightly verbose. Overall, it is efficient and each sentence contributes.

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 tool with one optional parameter and no output schema, the description covers use cases, persistence, and session behavior. It does not state what the tool returns, but that is a minor omission given the tool's 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 input schema lists a single optional string 'token' with no description (0% coverage). The description adds meaning by explaining the token is a JWT copied from the browser, and how to use it (paste for session login, omit to get link). This compensates well for the schema's lack of detail.

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 authenticates the user for IDE agents, using specific actions like 'log in' and 'copy the access token'. It implies the tool's purpose is authentication, but it does not explicitly contrast with sibling 'connect', so it lacks full sibling 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 provides explicit usage guidelines for two modes: adding a permanent config header versus pasting a session token. It explains when to call with a token and when to call with no args. However, it does not mention when to use this tool over alternatives like 'connect'.

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, non-destructive, and idempotent behavior. The description adds informative conditional outcomes (authenticated:true vs. connect_url for missing credentials), enriching behavioral understanding 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, front-loaded with the primary purpose and then explaining conditional behavior. Every word 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?

The description covers the two main states (all connected vs. missing credentials) but does not mention partial connection states or error scenarios. Given the tool's simplicity and strong annotations, this is a minor gap, so a 4 is warranted.

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 zero parameters, so schema coverage is 100% trivially. The description correctly introduces no parameter details, and with no params to explain, a 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 the tool 'Returns connection status and URLs' with specific conditional outcomes. This distinguishes it from siblings like 'authenticate' and 'marketplace' by focusing on status retrieval rather than 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 implies usage by describing what the tool returns, and the sibling tool 'authenticate' naturally indicates when not to use this tool. However, no explicit alternatives or exclusion criteria are provided, only implicit context.

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 behaviors: invoke runs tools without installing them, writes require workspace owner/admin, auth/payment scenarios produce connect/checkout links, and search/describe flag installation status. This adds significant context about side effects and prerequisites that annotations alone do not provide. No contradiction found.

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 appropriately so for a tool with 23 parameters and 14 actions. It is front-loaded with the core purpose, then organizes the flow with 'Core flow', 'KEY', and clear distinctions. Every sentence adds useful information, and the density is justified by the tool's complexity.

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 and lack of output schema, the description is remarkably complete. It covers all major functional areas: discovery, execution, installation, billing, feedback, requests, and the prompt library, including authentication and payment behaviors. Minor omissions like resume are negligible given the breadth covered.

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 0% schema description coverage, the description compensates substantially by explaining the meaning of the action enum values (search, describe, invoke, install, subscribe, etc.) and the roles of core parameters like mcp_id, tool_id, and prompt-related fields. It adds meaning beyond the bare input schema even though not every parameter is individually addressed.

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 that this is 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It specifies the resource (MCPs and prompt library) and distinct actions (search, describe, invoke, install), differentiating it from sibling tools by emphasizing it is both catalog and execution engine.

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 explicit when-to-use guidance: 'prefer invoke for a single/occasional use' vs 'install only to make an MCP PERMANENT.' It explains the core flow (search → describe → invoke), when to use list_tools, and how to handle authentication and payment via connect/checkout links. This clearly distinguishes between 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=true and idempotentHint=true, so the safety profile is known. The description adds valuable context beyond the annotations: the query is hosted without credentials, requires prepaid credits, accesses public data, and places LGPD responsibility on the client. This enriches the agent's understanding of operational and legal 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 reasonably concise for the amount of context it provides. It starts with the core purpose, then details payment, credentials, data nature, and LGPD. While it could be trimmed, each sentence adds meaningful operational or legal context, and the structure is logical.

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 tool with no output schema, the description covers the main purpose, payment model, and legal framing. However, it omits explanation of the 'completo' parameter and doesn't mention the response format or error behavior, leaving some important gaps for an agent deciding how to invoke the tool.

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 0% schema description coverage, the description must compensate. It explains that the query is based on CPF, which covers the 'Cpf' parameter, but it does not explain the 'completo' boolean parameter at all. The phrase 'dados associados' is vague and doesn't clarify what 'completo' changes, leaving a significant gap.

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 states a specific action ('Consulta o número do PIS e dados associados de uma pessoa a partir do CPF') with a clear resource (PIS data from CPF) and source (Ministério do Trabalho). It distinguishes itself from sibling tools, which are unrelated (authenticate, connect, marketplace, 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 context for when to use the tool: prepaid credit, no credentials required, and it queries public-access information. It doesn't explicitly mention alternatives or exclusions, but the context is sufficient to infer appropriate usage.

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 reveal non-read-only, idempotent, non-destructive behavior. The description adds the useful detail that the conversation array should be included for reproduction, but it doesn't disclose other behavioral aspects such as whether a confirmation is returned or how the report is processed. This is moderate added value 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 purpose, and ends with a specific, necessary instruction about the conversation array. There is no extraneous text, making it both concise and effectively structured.

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 reporting tool with three string parameters and no output schema, the description is mostly adequate. However, it omits the 'context' parameter entirely, doesn't mention any response or post-submission behavior, and leans on annotations for safety. This is a moderate gap given zero schema coverage.

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 descriptions cover 0% of parameters, so the description must compensate. It only explains the 'conversation' parameter ('Include the conversation array with recent messages'), leaving 'context' completely unexplained and 'message' only implicitly the report text. No format details are given for the conversation JSON string, and the 'context' parameter is a significant gap.

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 reports a bug, missing feature, or sends feedback, using an explicit verb ('report') and three distinct resource types. This distinguishes it from sibling tools like authenticate 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 implies when to use this tool (when the user reports a bug or provides feedback) and gives specific guidance to include the conversation array for reproduction. It doesn't explicitly say when not to use it, but the context is clear and no alternative reporting tool exists among 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 and idempotentHint=true, covering the safety profile. The description adds the detail that both platform and adapter versions are returned, providing slightly more context, but no additional behavioral traits such as side effects, auth requirements, or rate limits are disclosed.

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 ('Show the current MCP platform and adapter versions.') that is front-loaded with the verb and object. It contains no filler or redundant information.

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, zero-parameter tool with no output schema, the description is entirely sufficient. It clearly states what information is displayed (platform and adapter versions), leaving no ambiguity about the tool's purpose or expected result.

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 100% covered. Per the rubric, a 0-parameter tool gets a baseline of 4. The description adds no parameter-specific meaning because none exist.

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 identifies the resource as 'current MCP platform and adapter versions,' clearly stating what the tool does. It is distinct from sibling tools like authenticate or connect, which are action-oriented, while this is purely informational.

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 explicitly state when to use this tool versus alternatives, nor does it mention exclusions or conditions. However, the simple, self-explanatory nature of the tool makes its usage obvious (whenever version info is needed), so the usage is implied 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is known. The description adds valuable context about what the return value contains (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the annotations. No contradictions; it fully describes the tool's behavioral output.

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 conveys the full purpose and scope without any fluff. Every word earns its place, making it concise and well-structured.

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 read-only, zero-parameter tool with no output schema, the description is complete: it names the exact information returned and implies the general purpose. No additional context is needed given the simplicity of the tool and the presence of sibling tools with distinct roles.

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 input schema is empty with 100% coverage. Per the rubric, a no-parameter tool starts at 4. The description adds no parameter semantics because there are none to add, and the schema already says all that's 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 uses a specific verb ('Returns') and clearly defines the resource (current toolkit state), enumerating exactly what is included (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from siblings like authenticate or show_version, 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?

Usage context is clear: this is the go-to tool for inspecting toolkit state. It implies when to use it (e.g., before connecting or diagnosing issues) but does not explicitly state when not to use it or name alternatives. That said, the tool's purpose is inherently distinct from the siblings, so the guidance is adequate.

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