Conselho Regional de Odontologia DF: Cadastro

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

The description explains the side effects of different usage modes (permanent vs session) and the interaction (browser login). It adds context beyond the annotations (idempotent, non-destructive), though it doesn't state outcomes or failure cases explicitly.

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 relatively concise but includes a slightly verbose intro ('MCP.AI for IDE agents (Cursor, etc.)') and repeats the token concept. The structure with 'Best:' and 'Or' is clear, but could be trimmed slightly without losing 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?

Given no output schema, the description covers the main usage scenarios and the expected input. It does not mention return values or success/failure indicators, but for a simple authentication tool, the provided context is sufficient for most agents. Slight gap on what happens after authentication.

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 only lists an optional 'token' string with no description. The description clarifies that the token is the authentication token obtained from the browser and explains how its presence/absence changes behavior (session vs. link retrieval). This fully compensates for the 0% schema coverage.

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 is authentication for MCP.AI IDE agents. It outlines the auth flow (browser login, token retrieval) and distinguishes it from siblings by implying it is the sole authentication entry point.

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 usage instructions: add token to config for permanent access, pass token as argument for session, or call with no args to get the login link. This gives clear when-and-how guidance, though it doesn't mention alternatives since none likely exist.

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=true, idempotentHint=true, so the bar is lower. The description adds value by explaining condition-dependent output (authenticated:true with empty pending[] vs connect_url and per-install URLs), which matches and enriches the read-only behavior without contradicting 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 at two sentences, front-loading the primary purpose ('Returns connection status and URLs') and then clarifying both output conditions. Every sentence adds value with no 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?

With 0 parameters and no output schema, the description fully covers the tool's behavior by specifying both possible outcomes based on provider connection status. It is complete for the tool's purpose and context.

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 and schema coverage is 100%. Baseline for 0 params is 4, and the description adds no parameter information, which is appropriate 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 'Returns connection status and URLs', with specific details on the two possible states (authenticated vs missing credentials). This distinguishes it from siblings like 'authenticate' and 'show_version' 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 for checking connection state but does not explicitly state alternatives or when not to use it. It provides contextual behavior for two states, giving some guidance on expected results, but no explicit when/when-not or alternative naming.

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 valuable behavioral details: it is hosted by the platform, requires no platform credentials, uses a prepaid credit system, and clarifies that the client is the data controller under LGPD. This goes well beyond the annotations and gives the agent operational 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 a single run-on sentence with multiple clauses, covering hosting, payment, legal aspects, and data nature. It is informative but not concise; it lacks clear sentence breaks and front-loading of the core purpose. Every clause adds some value, but the structure could be improved for scanning.

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 tool is simple (one parameter, no output schema), but the description omits essential details like what the input parameter represents and what the output looks like. It does provide context on legality, payment, and data confidentiality, which helps, but without parameter/output guidance, the agent may misapply the tool. Given the lack of output schema, the description should have explained the return format, so it falls short of 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?

The input schema has a single parameter 'inscricao' with no description, and schema description coverage is 0%. The description does not explain what 'inscricao' means (e.g., registration number) or any format expectations. Since the description must compensate for the missing schema documentation, it completely fails to do so for the parameter.

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 performs a query ('consulta') on registration records from the Brazilian dental council (CRO-DF). It uses a specific verb+resource construction and the tool is distinct from generic siblings like authenticate or connect, so the purpose is 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 provides context that this is an official public source, non-confidential data, and requires prepaid credits. It does not explicitly say when NOT to use it or name alternative tools, but given the sibling list, it's clear this is the only query tool for such records. It implies usage for official lookup while noting payment requirements.

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 are minimal (readOnlyHint=false, openWorldHint=true, etc.), so the description carries the full burden. It discloses that invoke runs one-off without installing, may require auth via connect links or payment via checkout links, requires owner/admin for writes, and explains the prompt library separately. No contradictions 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 long, dense paragraph, but it is front-loaded with the purpose and flow, and every sentence adds value. It is structured around the core flow and key distinctions, making it efficient despite its length. 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 the complexity (23 parameters, 14 actions, no output schema, minimal annotations), the description is remarkably complete. It covers all action categories, edge cases (auth, payment, permissions), the prompt library, and even differentiates installed_in_toolkit vs installed_in_workspace. Nothing significant 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?

Schema coverage is 0%, but the description explains the core parameter `action` with its many enum values, and gives context for `mcp_id`, `tool_id`, `arguments`, and prompt-related parameters through the workflow. It does not enumerate all 23 parameters, but it provides enough semantic grounding for the most critical ones, compensating for the lack of 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 identifies the tool as the official mcp.ai marketplace, specifying its role as a catalog and execution interface for MCPs/tools. It distinguishes itself from sibling tools by explicitly covering actions like search, describe, invoke, and install, and mentions the core flow, making its scope 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?

Extensive guidance is provided: it explains when to use invoke vs install, how search/describe lead to invoke, when to use list_tools, subscribe/cancel, and even contrasts with request_mcp for new MCPs. Alternatives are explicitly named, and permission requirements for writes are 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 idempotentHint (safe to retry) and destructiveHint false (non-destructive). The description adds that including the conversation array aids reproduction, which is useful context beyond annotations. Yet it does not disclose what happens post-submission (e.g., sending, storage, response behavior) beyond the parameters.

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 contains no fluff or redundant details. 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?

Given the tool's simplicity (3 params, no output schema, no enums), the description covers the core purpose and one parameter effectively. However, omitting any explanation for the 'context' parameter leaves a gap for an agent deciding how to fill it. Overall adequate but with room for improvement.

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 the 'conversation' parameter's role (for reproduction) but leaves 'message' (only implied as the report text) and 'context' entirely unexplained. Since only one of three parameters gets meaningful semantic clarity, the compensation is insufficient.

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: reporting a bug, missing feature, or sending feedback. It distinguishes itself from sibling tools like authenticate, connect, and marketplace, which serve different functions.

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 implies when to use the tool (when you need to report an issue or provide feedback) and even hints at the requirement to include conversation for reproduction. However, it does not explicitly mention when not to use it or alternative tools, but the sibling names are sufficiently distinct.

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, covering safety. The description adds context by specifying exactly what versions are shown (MCP platform and adapter), which goes beyond the structured fields. No contradictions 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?

A single, front-loaded sentence ('Show the current MCP platform and adapter versions.') with zero wasted words. Efficient and perfectly sized for the tool's simplicity.

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 a trivial purpose, the one-sentence description fully explains what it does. No additional context is needed 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 tool has zero parameters, so the description does not need to elaborate on parameters. Baseline 4 is appropriate; the description provides no parameter info but none exists.

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 resource ('current MCP platform and adapter versions'), clearly distinguishing it from siblings like authenticate, connect, and toolkit_info. It is precise about what the tool returns without ambiguity.

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 the tool (to check versions) but does not explicitly state when not to use it or mention alternatives. Given its trivial nature and lack of overlapping siblings, clear context suffices without 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds detail about the returned state contents, but does not disclose additional behavioral traits such as permission requirements or rate limits. It does not contradict 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 a single, front-loaded sentence that efficiently enumerates the exact information returned. Every phrase earns its place, 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 tool is simple (no parameters, no output schema), and the description fully covers the return value's scope by listing the key elements: installed MCPs, connection status, connected accounts, and catalog tool counts. This is sufficient for an agent to understand what the tool provides.

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 there are no parameter semantics to describe. According to the rubric, 0 params merits a baseline of 4, and the description does not need to compensate for missing schema coverage since schema coverage is 100%.

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 identifies the resource ('current toolkit state') with a clear enumerable scope: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from siblings like show_version (version only) or connect/authenticate (state-changing 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 the tool is a read-only status query, making its use case clear for inspecting the toolkit's current configuration. However, it does not explicitly state when to prefer this over alternatives like show_version or connect, nor does it mention any exclusions.

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