Conselho Regional de Enfermagem PR: Cadastro

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

Annotations indicate idempotent and non-destructive behavior, and the description adds valuable context about the permanent/config vs. session-only distinction and the link generation. It does not contradict the annotations and discloses the session expiration 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 contained in three sentences and is generally concise, but it is slightly wordy with parenthetical asides ('Cursor, etc.'). The purpose is front-loaded and the rest is actionable, earning a strong score.

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 auth tool with one optional parameter and no output schema, the description covers the full workflow: getting the link, pasting the token, and the config header option. It is complete and leaves no gaps for an agent to 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 schema has 0% coverage for the single 'token' parameter, but the description fully compensates by explaining it as an optional JWT to be passed for session-only login, with the alternative of no args to get a link. This gives complete meaning beyond the bare 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 the tool's purpose: authenticating to MCP.AI for IDE agents. It specifies the action (log in) and resource (MCP.AI), and the context about copying an access token distinguishes it from sibling tools like 'connect' or 'marketplace'.

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 operating instructions: call with no args to get a link, or pass a token for session login. It also recommends the config header approach for permanent access, but does not explicitly mention when to avoid using this tool or name alternative sibling 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?

The description discloses behavioral details beyond annotations: it specifies two possible response scenarios (all connected vs. missing credentials) and what fields appear, adding clarity. Annotations already indicate read-only and idempotent 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 exceptionally concise, using two sentences to convey key functionality and distinct outcomes. 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 no parameters and no output schema, the description sufficiently explains the tool's behavior in common scenarios. It could elaborate on the exact meaning of 'connection status' but covers the essential 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?

The tool has no parameters, so schema coverage is complete. The description adds no parameter-related information, which is acceptable since 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 clearly states the tool's purpose: it returns connection status and URLs. It distinguishes from siblings like 'authenticate' by focusing on status rather than the authentication action itself.

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 checking connection status but does not explicitly state when to use this tool versus alternatives like 'authenticate'. No direct guidance on use cases or prerequisites.

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 that the tool accesses non-confidential official data, is not destructive (implied by 'consulta'), and clarifies payment and data controller responsibilities. Combined with annotations indicating read-only and idempotent behavior, it provides good transparency, though it does not explicitly mention network 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 paragraph that is moderately concise but includes redundant legal statements about LGPD and repeats the notion of official sources. It could be streamlined without losing necessary information, though it is not excessively wordy.

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 does not explain the expected output or return format, nor does it detail the purpose of each parameter or provide examples. While it mentions the source and payment model, it remains incomplete for a self-contained tool specification.

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 includes three parameters (nome, registro, categoria) but the description offers no explanation for any of them, leaving their meaning, format, or relations unclear. This is a major gap since the description does not compensate for the lack of schema 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 that the tool performs a query (consulta) for registration data from the Regional Nursing Council of PR, specifying it queries official sources. It effectively distinguishes itself from sibling tools like authentication or reporting by naming its specific domain.

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 mentions the tool is hosted by the platform, requires prepaid credits, and queries official public data, providing some usage context. However, it does not explicitly state when to use this tool versus alternative tools or describe typical scenarios, such as 'use when verifying a nurse's registration.'

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 openWorldHint=true and destructiveHint=false from annotations, the description goes well beyond them: it discloses that invoke runs one-off without installation, returns connect links on credential needs and checkout links on empty wallet with a retry instruction, states writes require workspace owner/admin, and warns that invoke does not bloat the tool list. It also covers the prompt library's open-without-login behavior. No annotation contradictions.

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 run-on block with no paragraph breaks or structural cues. Every sentence does carry functional information, but the flow from marketplace catalog → core search/describe/invoke → install distinction → permissions → prompt library is packed into one unbroken passage. It's not wasteful, but it could be split for readability. Acceptable but not optimal for a high-traffic tool.

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, multi-action tool with no output schema, the description covers the critical decision points: when to invoke vs install, auth/checkout link handling, permission requirements, installed_in_toolkit vs installed_in_workspace flags, and the prompt library sub-system. It does not detail return formats (no output schema to fall back on), but given the breadth of actions it must describe, the coverage is strong with minor gaps on edge-case params like resume, immediate, and cancel_reason 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 coverage is 0% with 23 params, so the description must compensate heavily. It explicitly enumerates the action enum and explains each action's role (search→describe→invoke core flow, install for permanence, subscribe/cancel for billing, request_mcp for new builds, search_prompts/get_prompt/publish_prompt for the prompt library). It references tool_id (pick the right tool_id), arguments, mcp_id implicitly, and prompt_vars/variables fill-in. However, params like cancel_reason, cancel_comment, immediate, tier_slug, prompt_targets, conversation, report_context receive no direct mention, leaving a partial gap at this coverage level.

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 establishes a specific purpose: 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It clearly distinguishes itself from siblings by naming alternatives like search_calls_extensive for filtering, and explicitly maps its action enum to distinct responsibilities (search, describe, invoke, install, list_tools, subscribe/cancel, prompt library). The verb+resource structure (discover, describe, run, install) is precise.

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 'Use install only to make an MCP PERMANENT in the active toolkit' and names the alternative 'list_tools lists what is callable right now.' It also contrasts with siblings (connect, authenticate) implicitly by stating invoke returns connect links when credentials are needed. This is model Tier A guidance with explicit exclusions and 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 cover idempotency (idempotentHint=true) and non-destructiveness (destructiveHint=false). The description adds that the conversation array should be included for reproduction, which is useful context but does not disclose other behavioral traits like potential notification side effects or response 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?

Two sentences, front-loaded with the core purpose, and every word earns its place. The instruction to include the conversation array is directly relevant and avoids unnecessary detail.

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 feedback-reporting tool with three parameters and no output schema, the description covers the primary purpose and the one parameter that needs behavioral nuance (conversation). It could go further by noting what happens after submission, but the complexity is low enough that the description is nearly complete.

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 the conversation parameter should contain recent messages for reproduction, and the message parameter is implicitly the bug/feature/feedback text. However, the context parameter is left entirely undocumented, leaving a small 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's action ('Report a bug, missing feature, or send feedback') and identifies the resource (bug reports/feedback). This differentiates it from sibling tools like authenticate or marketplace, which serve completely 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 provides clear context for when to use the tool—when a bug, missing feature, or feedback needs to be reported. It does not explicitly exclude alternatives, but none of the sibling tools overlap with this function, so the guidance is sufficient.

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 fully covered. The description adds no extra behavioral context (e.g., network usage, latency), but for a read-only version check this is acceptable. 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 a single, concise sentence that fully conveys the tool's purpose without any filler. Every word earns its place.

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 zero-parameter, read-only tool with no output schema, the description is complete. It states exactly what it does, and annotations cover side effects and idempotency. No further detail is needed.

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 the schema is trivially complete (100% coverage). Per the rubric, 0 params warrants a baseline of 4. The description doesn't need to explain parameters.

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 'Show the current MCP platform and adapter versions' uses a specific verb (show) and resource (versions), clearly distinguishing it from siblings like toolkit_info which likely provides broader system info. The scope is precise and unambiguous.

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 clearly implies when to use this tool (when needing version information) without explicit exclusions or alternatives. Given the tool's trivial nature, this is adequate, but it doesn't name any sibling alternatives like toolkit_info that might overlap.

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. The description adds context by listing what the state includes (installed MCPs, connection status, accounts, catalog tool counts), which is beyond the annotations. It does not contradict any annotations and provides useful detail for the agent.

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, well-structured sentence conveys the complete purpose and content with no fluff. The most important information appears immediately, and every phrase earns its place.

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 state query with no parameters, the description adequately covers the categories of returned information. It could be more precise about the structure of 'connection status' or 'accounts connected', but given the tool's simplicity and the presence of sibling tools for other operations, this is sufficient.

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 trivially 100%. Per rubric, a baseline of 4 applies for parameterless tools. The description appropriately focuses on the output and does not waste space on parameter explanations.

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' with a well-defined resource 'current toolkit state' and enumerates the contents (MCPs, connection status, accounts, catalog tools). This clearly differentiates it from siblings like 'show_version' even 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 provides no guidance on when to use this tool versus alternatives. It does not mention that this is the read-only overview or give any exclusions or alternative scenarios, leaving the agent without direct usage direction.

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