Conselho Regional de Odontologia AC: Cadastro

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

Beyond annotations (idempotent, non-destructive), the description explains side effects: session-only login vs. permanent config connection, and that calling with no args returns a link. It does not detail what happens after login (e.g., session timeout), but overall adds meaningful behavioral 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 slightly dense but each sentence serves a purpose. It front-loads the action and then provides alternatives. While a bit run-on, it remains concise enough for the information covered.

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 interactive nature (browser login, token paste), the description covers both primary use cases and the no-args link retrieval. It does not mention error handling or output format, but with no output schema and a clear flow, it is reasonably 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 has one optional parameter 'token' with no description (0% coverage). The description fully compensates by explaining the token is a JWT to paste for session-only login, and that omitting it yields a link. This adds crucial 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 it is for authentication to the MCP server, explaining both permanent (via config header) and session-based methods. It distinguishes itself from siblings by specifying it is for IDE agents and covers token handling.

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 explicit when-to-use guidance: permanent setup via config header vs. session login via token argument, and when to call with no args to get a link. Clearly explains the two invocation modes without ambiguity.

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 the readOnly and idempotent annotations, the description adds conditional behavior for two scenarios: when all providers are connected and when credentials are missing. This provides useful insight into expected responses, though it does not cover partial connection states.

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 and well-structured, leading with the primary function and then presenting conditional details. It contains no unnecessary words 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?

Since there is no output schema, the description partially covers the return structure (authenticated, pending, connect_url) but does not fully specify the data shape or handle all edge cases, such as partial connectivity. This leaves some gaps in completeness.

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 the description cannot add parameter semantics. With an empty input schema, a baseline score of 3 is appropriate, as there is nothing to clarify.

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 returns connection status and URLs. It also distinguishes itself from sibling tools by focusing on connection state, which is distinct from authentication or version checks.

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 provide explicit guidance on when to use this tool versus alternatives like 'authenticate' or 'toolkit_info'. It describes what the tool returns but not the circumstances that would make it the appropriate choice.

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. The description adds meaningful transparency beyond those: no platform credentials required, pay-per-query with prepaid credit, source is official public data, data is not confidential, and the customer is the data controller under LGPD. This is strong behavioral and contextual disclosure.

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 and front-loaded with the core purpose. It includes some extra legal/context sentences about LGPD and data controllership, which are relevant but slightly beyond the minimal necessary; still, each sentence adds some useful operational context and the overall length is appropriate.

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 single-parameter simplicity and rich annotations, the description covers purpose, access model, payment, and data sensitivity well. However, there is no output schema, and the description does not describe what the response contains or example result fields, leaving the agent without a clear picture of the query outcome. It is adequate but not fully 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?

With only one parameter, 'inscricao', and 0% schema description coverage, the description needed to explain what this value is (e.g., the dental council registration number) and its expected format. It only vaguely references 'Cadastro' and does not clarify how to fill the parameter or what values are valid, so the description fails to compensate for the sparse 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 identifies the tool as a consultation/query for Conselho Regional de Odontologia AC registration data in an official source. It distinguishes the resource via the council name and the 'consulta' intent, though it is not as explicit or action-forward as a direct 'Consultar cadastro...' phrasing.

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 useful context about access (no platform credentials, prepaid credit) and the legitimate use case (official public data, LGPD compliance). However, it does not state explicit 'when to use this tool versus alternatives' or provide any exclusion criteria, leaving the usage guidance implied rather than direct.

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 side effects: invoke runs one-off without installing, returns connect or checkout links when credentials or payment are needed, writes require owner/admin, and search/describe flag installation status. This is thorough and goes beyond the minimal readOnlyHint=false.

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 front-loaded with the core purpose and flow, but it is a single dense paragraph covering many actions and edge cases. While the complexity warrants detail, it could benefit from bullet points or clearer separation between the MCP flow and prompt library. It is not concise but is appropriately structured for the scope.

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 14 actions, 23 parameters, and no output schema, the description is remarkably complete. It covers the core discovery/invocation flow, the distinction between installed and not-installed behavior, permission requirements, payment/auth exceptions, and the separate prompt library. No critical usage context is missing.

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 adds meaning to the critical action parameter by explaining each enum value and its purpose (search, describe, install, etc.). It also explains parameters like tool_id, arguments, and prompt-related fields through the workflow. However, with 23 parameters and 0% schema coverage, not all parameters (e.g., limit, query, cancel_reason) are individually documented, though many are self-explanatory by name.

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 marketplace for discovering and running MCPs/tools, with a specific flow for search→describe→invoke. It distinguishes itself from siblings like authenticate and connect by detailing its role as the in-platform catalog and execution layer.

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 explicitly instructs when to use each action (e.g., prefer invoke for one-off use, install only for permanent toolkit additions, list_tools to see current callable tools). It also explains when to use request_mcp, subscribe/cancel, and the prompt library functions, providing clear alternatives and exclusions.

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 some context beyond the annotations by indicating that the conversation array is used 'for reproduction,' implying the tool likely sends data to a server. Annotations already declare this is not read-only (readOnlyHint: false) and not destructive (destructiveHint: false), and the description does not contradict them. However, it does not discuss potential side effects, rate limits, or authentication needs, leaving room for more 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?

The description is two sentences long, front-loads the purpose, and includes a practical tip in the second sentence. Every word adds value without redundancy. It is an excellent example of brevity coexisting with utility.

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 no output schema and straightforward behavior, the description covers the essentials: what it does and what to include for best results. It does not specify return values or error handling, but these are less critical given the tool's simplicity. The description is adequately complete for an agent to use 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?

Schema description coverage is 0%, so the description carries the burden of explaining parameters. It explicitly explains the 'conversation' parameter's purpose ('recent messages for reproduction'), which adds value. Yet 'message' (required) and 'context' receive no clarification, and the description does not mention the JSON-encoded format expected for 'conversation.' Partial coverage at best.

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 with a specific verb and object: 'Report a bug, missing feature, or send feedback.' This is unambiguous and easy to understand. However, it does not explicitly distinguish itself from sibling tools, though the siblings (e.g., 'marketplace', 'show_version') are semantically distinct, so no confusion arises.

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 a clear instruction to 'Include the conversation array with recent messages for reproduction,' which gives useful usage context for one of the parameters. However, it does not mention when to avoid this tool or reference any alternatives. The guidance is implicit and partial rather than comprehensive.

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 readOnly, non-destructive, and idempotent nature. The description adds no further behavioral details, but the annotations fully cover safety aspects, so this is acceptable.

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 efficiently conveys the tool's purpose without 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 version-query tool with no parameters, the description is fully complete. It does not need to explain return values as there is no output schema, but the purpose is unambiguous.

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 complete. The description does not need to add 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 clearly states the tool's function: showing current MCP platform and adapter versions. It is specific and distinguishes 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 retrieving version information, which is clear enough given the tool's simplicity. It does not explicitly mention when to use alternatives, but no alternatives are relevant for this task.

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 annotations already declare readOnlyHint and destructiveHint as false, and the description adds specific details about the returned data (installed MCPs, connection status, accounts, catalog counts). This fully discloses the tool's behavior without contradiction, exceeding the baseline expected with annotations present.

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, focused sentence that lists the exact output dimensions with no filler or redundancy. Every word contributes to understanding the tool's function.

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 absence of parameters and output schema, the description fully specifies what the tool returns. It covers all relevant aspects of the toolkit state, making it complete for the tool's 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?

The tool takes no parameters, so there is no ambiguity. The description and schema align perfectly, making parameter semantics irrefutably clear.

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 returns the current toolkit state, listing specific components (installed MCPs, connection status, accounts, catalog tools). This is a clear, non-redundant statement of purpose that distinguishes 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?

While not explicitly stating when to use versus alternatives, the nature of a state-query tool is self-evident given sibling tools like authenticate and connect. The description implies it should be used to inspect overall toolkit health and configuration, which is adequate context.

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