Conselho Regional de Odontologia RJ: Cadastro

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

The description discloses the token handling behavior, including the fact that adding to config gives a non-expiring connection, while pasting gives session-only. This goes beyond annotations (readOnlyHint false, idempotentHint true) and provides important context without contradiction.

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 dense but long-winded as a single run-on sentence. It conveys all needed info, but could be split for better readability. Still concise for the content 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?

The description is complete for an authentication tool with one optional parameter: it explains both invocation modes and the authorization header setup. It doesn't describe the response, but there is no output schema, and the purpose is primarily to establish authentication state.

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 zero schema description coverage, the description fully compensates by explaining the token parameter and its optional usage ('{ token: "<jwt>" }'), plus the no-args case for getting the link. This adds significant 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: authenticate with MCP.AI via browser login and token handling. It distinguishes from siblings by specifying the use case for IDE agents and the two modes (link generation and token submission).

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?

Explicitly explains when to use each mode: paste token for session-only, or add to config for permanent access. Also says to call with no args to get the link, providing clear guidance on 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral detail beyond that, such as the exact state returned (authenticated:true, empty pending[]) and the URL behavior when credentials are missing.

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 clause adds informative detail. No filler or redundant restatement 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 status tool, the description covers the main return value, the success state, and the failure/missing-credentials state. The tool is simple enough that this is sufficient even without an output schema.

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 schema provides 100% coverage. Per the baseline for zero-parameter tools, a score of 4 is appropriate; the description does not need to add parameter semantics.

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: returns connection status and URLs. It also explains the two distinct result scenarios (all providers connected vs. missing credentials), which clearly differentiates this from sibling tools like authenticate.

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 conditional context ('When credentials are missing, returns connect_url'), which implies when this tool is useful, but it does not explicitly say when to use it over alternatives like authenticate, nor does it mention when not to use it.

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 annotations (readOnly, idempotent, non-destructive), the description discloses important behavioral characteristics: it is a paid service ('pague por consulta com crédito pré-pago'), it uses public, non-confidential data ('não é dado sigiloso'), and it clarifies the client's data controller responsibility under LGPD. This adds meaningful context 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 structured with the core purpose in the first sentence, followed by additional context (hosting, payment, data source, LGPD). It is not overly verbose for the amount of information it conveys, though some legal and payment details could be condensed without losing value.

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 tool's purpose, data source, payment model, and privacy responsibilities. However, it does not describe what the response contains (since there is no output schema) or how errors are handled, leaving the agent without a clear expectation of the query 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 schema coverage is 0%, so the description must compensate. It fails to explain that 'inscricao' is the dentist's registration number or provide any format/constraints (e.g., numeric, length). The only hint is the tool name and 'Cadastro' in the purpose, which is insufficient for an agent to know exactly what to pass.

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: 'Cadastro, consulta em fonte oficial' – it queries registration data from the Regional Council of Dentistry of Rio de Janeiro. It explicitly names the resource (CRO RJ) and the action (consulta/query), distinguishing it from the sibling tools which are unrelated meta-tools (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 implies usage for querying CRO RJ registration data and provides context about hosting, payment via pre-paid credits, and lack of platform credentials. It does not explicitly state when not to use it or list alternatives, but since siblings are clearly different, the intended context is clear and 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?

The description goes beyond the annotations (readOnlyHint false, destructiveHint false) by detailing behavioral nuances: invoke works even if the MCP is not installed, runs one-off without bloating the tool list, and returns connect or checkout links when credentials or payment are needed. It also specifies that writes require owner/admin. This fully discloses the tool's side effects and prerequisites.

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 (about 200 words) but packs dense, essential information. It is front-loaded with the core flow and uses a logical narrative. While it could benefit from bullet points, given the breadth of functionality (14 actions plus prompt library), the length is justified and every sentence contributes useful 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 covers the main usage scenarios, permission requirements, edge cases (connect/checkout links), and the prompt library. It lacks details on return formats or error handling, but since there is no output schema and the tool is complex, it provides a solid overview. Missing parameter documentation is the main gap, lowering 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?

With 23 parameters and 0% schema description coverage, the burden falls on the description. While it explains the action enum and the high-level flow (e.g., 'action=search', 'choose the right tool_id', 'invoke RUNS that tool'), it does not explain the majority of parameters like query, limit, mcp_id, arguments, message, conversation, prompt_body, or prompt_slug. It leaves many parameters undefined, making it hard for an agent to know exactly what to fill for each action.

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 the official MCP marketplace, covering catalog discovery and execution. It enumerates all major actions (search, describe, invoke, install, subscribe, etc.) and explains the core flow, distinguishing it from sibling tools like authenticate and connect. The purpose is specific and detailed, leaving no ambiguity about what the marketplace tool does.

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 guidance on when to use each action: search for discovery, describe for profile details, invoke for one-off executions, install for permanent toolkit addition, and subscribe/cancel for billing. It explicitly says 'prefer invoke for a single/occasional use' and 'install only to make an MCP PERMANENT', giving clear decision criteria. It also notes write permissions required for certain actions.

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 indicate non-read-only, non-destructive, and idempotent behavior. The description adds no additional transparency about side effects (e.g., whether a ticket is created). However, given the annotations already cover basic behavioral traits, the lack of extra detail keeps it neutral.

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 conveys the purpose and a key usage instruction without unnecessary fluff. It is well-structured and directly actionable.

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 purpose and usage sufficiently for a bug reporting tool. It does not mention output or return values, but that is not critical given the tool's nature. It is complete enough for an agent to understand when and how to invoke it.

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 explains the 'conversation' parameter ('Include the conversation array with recent messages for reproduction'), which adds value beyond the schema. However, it does not clarify the 'context' parameter, which might be ambiguous to users unfamiliar with the tool. 'message' is self-explanatory.

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.' This is a specific verb (report) with a clear object, distinguishing it from sibling tools 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 explicitly specifies when to use the tool (for reporting bugs, missing features, or feedback) and provides guidance on how to use it (include the conversation array for reproduction). It does not explicitly exclude other tools, but the context makes the use case clear.

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. The description adds that it shows both platform and adapter versions, which is useful behavioral context beyond the annotations. It confirms the return data's nature without contradicting any annotations. Could add details about the format, but not necessary for this simple tool.

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 directly states the tool's function with no wasted words. It is concise and immediately understandable.

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 trivial nature (no parameters, no output schema, clear intent), the description is complete. The annotations provide safety hints, and the description covers what information is displayed. No additional context is needed for an AI 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?

This tool has zero parameters, so the baseline is 4 per the rubric. The description does not need to add parameter semantics since there are none, and the schema is trivially complete.

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') with a clear resource ('current MCP platform and adapter versions'). It distinguishes this tool from siblings like 'authenticate' or 'connect' by stating exactly what informational content is retrieved.

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?

No usage guidance is provided. It does not mention when to use this tool versus alternatives (e.g., 'toolkit_info'), nor does it provide context about scenarios where the version info would be relevant. This is a minimal description with no explicit or implied usage instructions.

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, and destructiveHint=false, so the safety profile is established. The description goes beyond this by explaining exactly what kind of information the tool returns, which helps the agent set expectations and confirm this is a non-mutating query tool.

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, well-structured sentence with no filler. Every component—installed MCPs, connection status, account list, tool counts—adds meaningful detail while remaining compact.

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 status tool with no output schema, the description is complete enough: it names all major pieces of returned information and makes its non-mutating nature evident. Nothing essential is missing for the agent to select and invoke the tool 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?

There are zero parameters, so there is no schema semantics to clarify. The description adds sufficient detail about what the tool returns, and with no parameters it does not need to compensate for schema gaps.

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 returning the current toolkit state, with a specific verb ('Returns') and concrete details about what is included: installed MCPs, connection status, connected accounts, and exposed catalog tool counts. It is distinguishably different from sibling tools like authenticate, connect, or show_version, which appear to perform actions or report version 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 clearly implies this is the tool to use when the agent needs an overview of the toolkit's setup and connectivity rather than taking an action. It does not explicitly state exclusions or name alternatives, but the 'current toolkit state' framing provides clear context for when it should be used.

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