Conselho Regional de Odontologia RN: Cadastro

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

Beyond the annotations (idempotent, non-destructive), the description discloses that adding to config yields a non-expiring connection while pasting gives session-only. It also mentions that calling with no args returns a link, adding transparency about its 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 somewhat verbose and not tightly structured, with multiple clauses and parentheticals. It could be more concise while conveying the same 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?

The description explains the authentication flow and mentions obtaining a link with no args, but it doesn't state what the tool returns when a token is provided or any error handling. This leaves some gaps in understanding the full behavior.

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 only parameter 'token' is explained as an optional JWT used for session login, and the description clarifies behavior when it's omitted. However, it doesn't specify the token's format or origin in detail, leaving some ambiguity.

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 MCP.AI IDE agents, explaining the login flow. It is distinct from sibling tools like connect or show_version, as it focuses 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?

It provides explicit instructions for two usage modes: adding a token to config for permanent connection or pasting for session-only. It also explains how to call with a token or without to get a link, offering clear guidance.

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?

While annotations already establish read-only and non-destructive behavior, the description adds valuable details about the output structure and conditional responses (authenticated: true vs. connect_url), enhancing transparency 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?

The description is succinct, using only two sentences to convey core functionality and variations. There is no extraneous information, making it well-structured and to the point.

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 lack of an output schema, the description adequately explains the primary output fields (authenticated, pending, connect_url) and the two main scenarios. It is complete enough for a simple tool, though it doesn't cover potential error cases or additional edge scenarios.

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 there is nothing to explain. The description does not need to add meaning to parameters, and the empty schema is fully covered.

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: it returns connection status and related URLs. It further specifies distinct outcomes (authenticated vs. missing credentials), making the purpose 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 does not explicitly indicate when to use this tool compared to alternatives, nor does it provide context such as prerequisites or scenarios where another tool might be preferred. It only describes the tool's behavior without usage guidance.

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 indicate read-only, idempotent, and non-destructive. The description reinforces this by stating it is a 'consulta' (query). It adds behavioral details about prepaid credits and LGPD compliance, and clarifies that the data is not confidential. This goes beyond the annotations by explaining the payment model and legal responsibility.

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 main purpose and then provides operational and legal context. It is concise, using three sentences without extraneous wording. The information about hosting, payment, and LGPD adds valuable context without bloat.

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 data nature (official, non-confidential), legal responsibility, and payment model, but it lacks details about the input parameter (registration number) and the output format. Since there is no output schema, the description should have explained what data is returned. It also doesn't mention any limitations or pagination. It is somewhat complete for a simple lookup but missing key operational details.

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 a single parameter 'inscricao' with no description, and the tool description does not explain its meaning, format, or expected values. With 0% schema coverage, the description fails to compensate for the missing parameter documentation, leaving the agent without guidance on what to provide.

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 is for consulting the CRO RN registry ('Cadastro, consulta em fonte oficial'). It specifies the domain (Conselho Regional de Odontologia RN) and the action (query), making the purpose unambiguous. It also distinguishes itself from generic sibling tools by naming the specific council.

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 usage context: the tool is hosted by the platform, requires no platform credentials, and uses prepaid credits. It also specifies legitimate use under LGPD, which guides when to use the tool. While it does not explicitly state 'use this to verify registration', the legal and payment notes give operational guidance.

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 disclose that the tool is writable and non-idempotent, but the description adds significant behavioral context beyond that: it explains that 'invoke' works even for uninstalled MCPs, runs one-off without bloating the tool list, and may return connect or checkout links if credentials or payment are needed. It also flags that writes (install/uninstall/subscribe/cancel) require workspace owner/admin, and that 'subscribe/cancel' handle billing. It does not contradict the annotations; it complements them with details about side effects like 'one-off install behind invoke'.

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, which is efficient for the complexity, but it is quite long and dense, making it slightly harder to parse. It is front-loaded with the core purpose, but quickly dives into many sub-actions and edge cases. It would benefit from visual structure (like bullet points) to improve scannability, but it stays focused and avoids redundancy. Given the breadth of the tool, the length is justified, so it earns a 4.

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 is exceptionally complete for a tool of this complexity, covering all major action categories (search, describe, invoke, install, billing, bug reporting, and prompt library), auth requirements, payment flows, and behavioral nuances. Even without an output schema, the description explains what to expect (e.g., 'invoke returns a connect link' or 'checkout/top-up link'). It anticipates common user needs and edge cases, making it highly useful for an AI agent to decide when and how to invoke this 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?

Schema description coverage is 0%, so the description carries the full burden for parameter semantics. It does not enumerate each parameter's meaning, but it explains the high-level flow: 'action=search discovers MCPs by intent → describe returns one MCP's full profile → invoke RUNS that tool' and mentions parameters like 'tier_slug' for billing and 'cancel_reason' from the enum. It covers key parameters indirectly through action descriptions, but lacks detailed syntax for each parameter, so it earns a 4 rather than a 5. For a tool with 23 parameters, more explicit mapping would be ideal.

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 identifies 'marketplace' as the official mcp.ai marketplace, distinguishing it from siblings like 'authenticate' and 'connect'. It clearly states the core purpose: discover, run, and manage MCPs, with concrete capabilities (search, describe, invoke, install). It uniquely positions this tool as the central hub for finding and running MCPs, contrasting with specialized tools like 'report_bug' and 'toolkit_info'.

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 extensive guidance on when to use the tool and its sub-actions, including explicit directives: 'use install only to make an MCP PERMANENT in the active toolkit; prefer invoke for a single/occasional use.' It clearly contrasts 'invoke' with alternatives like 'list_tools' and 'install', and mentions that for prompt library functions, 'search_prompts' finds one, 'get_prompt' returns text, and 'publish_prompt' saves. This helps the agent choose the right action and action flow.

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 provide idempotentHint=true and destructiveHint=false. The description adds the requirement to include conversation for reproduction but does not disclose what happens after reporting (e.g., confirmation, ticket creation). It provides minimal extra context 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?

The description is two concise sentences with no redundancy. It front-loads the purpose and includes a key instruction about conversation, making every word valuable.

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 3-parameter tool with no output schema, the description covers the core purpose and the critical instruction about conversation. It does not describe return values or side effects, but given its simplicity and existing annotations, 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 description coverage is 0%, so the description must compensate. It explains the 'conversation' parameter ('recent messages for reproduction') but does not explicitly define 'message' or 'context'. The mention of 'conversation' adds some value, but message (required) remains vague.

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: report a bug, missing feature, or send feedback. The verb 'report' and resource (bug/feature/feedback) are specific, and the tool is distinct from siblings like authenticate 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 gives clear context on what to include (conversation array) but does not mention when not to use it or compare alternatives. Since siblings are unrelated, this is adequate, though explicit exclusions are absent.

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 behavior is covered. The description adds meaningful context by specifying exactly what is reported: the current MCP platform and adapter versions, with no side effects indicated.

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 conveys the tool's purpose. Every word earns its place, with no filler or repetition of the tool name.

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 version-reporting tool, the description is complete. It names both the subject (platform and adapter versions) and the action (show current), which is sufficient given the simple scope and strong annotations.

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 baseline is 4. The description correctly does not attempt to explain nonexistent parameters, and the schema's 100% coverage requires no additional parameter 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 uses a specific verb and resource: "Show the current MCP platform and adapter versions." This clearly identifies what the tool does and is distinct enough from sibling tools, which focus on auth, connection, marketplace, and bug reporting.

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 no guidance on when to use this tool versus alternatives like toolkit_info or similar informational tools. It states what the tool does but provides no explicit usage context, exclusions, or alternative references.

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 the safety profile is covered. The description adds useful content detail about what state is returned, but does not disclose any additional behavioral traits such as freshness, caching, or connection-check 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?

A single, front-loaded sentence contains the verb, the resource, and a complete list of returned information. Every word 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?

For a simple zero-parameter introspection tool without an output schema, the description adequately explains the return contents (installed MCPs, connection status, accounts, catalog tool counts). No critical context appears missing given the tool's low complexity.

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 schema coverage is 100%, so there is no parameter ambiguity. Per the rubric, a zero-parameter tool gets a baseline of 4; the description correctly implies it takes no input.

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 identifies the resource ('current toolkit state'), then enumerates exactly what is included: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from sibling tools 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 implies this tool is for inspecting the toolkit's overall state, which is clear context, but it does not explicitly state when to use it instead of similar informational tools like show_version. No exclusions or alternative recommendations are provided.

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