Conselho Regional de Odontologia PE: Cadastro

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

Annotations already declare idempotentHint=true, readOnlyHint=false, destructiveHint=false. The description adds context about the two login modes and the recommendation to use a config header for permanent access, but it does not explicitly state what the tool returns (e.g., success/failure), how it validates the token, or any side effects beyond the session establishment. It is not contradictory but lacks deep behavioral detail.

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 not overly long. It front-loads the purpose and quickly moves to usage. It mixes user instructions with agent instructions, which slightly complicates structure, but every sentence earns its place. Could be broken into clearer bullets, but it remains concise.

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 tool with one optional parameter and no output schema, the description covers essential usage: how to obtain a link and how to use a token. It lacks explicit return value details and error handling, but the overall flow is understandable. Given the low complexity and existing annotations, this is fairly 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 'token' parameter with zero description coverage. The description fully compensates by explaining 'call with { token: "<jwt>" } after the user pastes, or with no args to get the link' – clarifying that token is an optional JWT and that absence yields a login link. This gives complete meaning to 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 the tool's purpose: authenticating for MCP.AI in IDE agents. It specifies the process (login in browser, copy token) and distinguishes between two modes (permanent via config header, or session-only via token). This is a specific verb+resource with clear scope, and it differentiates from siblings like 'connect' by focusing on token-based 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?

Provides explicit instructions on when to call with no args (to get the link) and when to call with a token (after user pastes it). It also recommends best practice for permanent vs session-only login. However, it does not explicitly mention alternatives or when not to use, though sibling 'connect' suggests a different connection 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?

With annotations already indicating readOnlyHint=true and destructiveHint=false, the description adds meaningful behavioral context by explaining the response for both connected and missing-credential scenarios. It does not contradict annotations and provides expectations beyond the structured metadata.

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 each sentence earns its place by detailing behavior. No wasted words.

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 read-only status tool with no parameters and clear annotations, the description fully covers all expected behaviors—returning authenticated state and URLs when possible, and connect_url when credentials are missing. It is sufficient for an agent to understand inputs, outputs, and conditions.

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 the schema coverage is 100% (vacuously). The description does not need to elaborate on parameters, and it adds no parameter-related meaning beyond the empty schema, which is acceptable per baseline rules.

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 returns connection status and URLs, with specific details on two possible outcomes (authenticated versus missing credentials). It distinguishes itself from sibling 'authenticate' by focusing on status reporting rather than performing 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?

The description implies using this tool to check connection state, but does not explicitly state when to use it versus alternatives like 'authenticate'. It lacks guidance on when not to use it or what conditions warrant it, though the two-case behavior hints at context.

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 the operation read-only and idempotent; the description adds valuable context beyond that: the query requires prepaid credit, no platform credentials, only public non-confidential official data are returned, and LGPD responsibilities rest with the client. This is behavioral detail that annotations don't fully disclose, so it earns recognition.

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 three sentences and front-loads the main purpose early. It packs in relevant business and compliance details without excessive fluff. The sentence structure is slightly run-on and cluttered, but overall it is efficient for the amount of context it provides.

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 a single string parameter and no output schema, the description conveys the core purpose, official source, cost model, and LGPD responsibility, which is reasonably complete for an intended use. It falls short of describing the exact return data or what qualifies as a valid 'inscricao', but the annotation and simple parameter count otherwise support a fairly complete profile.

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 required string 'inscricao', but the description provides zero coverage of that parameter. The agent must infer from the tool name that it's a registration number, but no expected format, possible examples, or other helpful semantics are given. Since schema coverage is 0%, the description should have picked up the slack and does not.

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 and title point to a specific tool: a query/consult of the Pernambuco Regional Dentistry Council (CRO-PE) registration from an official source. It distinguishes itself from sibling tools like authenticate and marketplace. However, it does not use a crisp verb+object construction and the phrase 'Cadastro, consulta em fonte oficial' is somewhat imprecise, leaving the exact action implicit.

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 communicates conditions that affect use—prepaid credit, no platform credentials, official public data—but it does not explicitly say when to use the tool versus alternatives or when not to use it. There are no semantically similar sibling tools, which lowers the need for alternatives, but the guidance is still implied at best.

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 well beyond the sparse annotations by disclosing important behaviors: invoke works even when the MCP is not installed, credentials trigger a connect link, paid tools with an empty wallet return a checkout/top-up link, writes require workspace owner/admin, and prompt links open without login. No contradiction with annotations exists.

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 efficient, front-loading the core marketplace concept and then expanding into action flows and edge cases. It is a single wall of text rather than structured bullets, but every sentence adds meaningful information, and the length is justified by the tool's 14 actions and complex behavior.

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 tool with 14 actions, 23 parameters, and no output schema, the description covers the major workflows, permission requirements, billing/connect fallbacks, and prompt-library details. Minor gaps remain: the resume action is never mentioned, some parameter semantics are incomplete, and return formats are only partially described (e.g., list_tools is vague). Overall, it is robust for the 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?

With 0% schema description coverage and 23 parameters, the description carries a heavy burden and explains the main workflow parameters (action, mcp_id, tool_id, arguments, prompt_* fields) reasonably well. However, several parameters remain unexplained, including limit, query, immediate, tier_slug, conversation, cancel_reason, report_context, and request_details. The description compensates for core flows but not for the full parameter surface.

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 mcp.ai marketplace: a catalog of MCPs/tools and the mechanism to run them. It articulates the core search→describe→invoke flow and differentiates key actions (invoke vs install, search vs request_mcp, prompt library vs MCP catalog), making the tool's purpose and scope unmistakable.

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 strong usage guidance: prefer invoke for one-off use, use install only for permanent toolkit additions, use request_mcp when nothing fits, and use search_prompts for prompt text. It explicitly contrasts invoke vs install and describes when to use billing/reporting actions, which helps an agent select the right action.

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 idempotentHint=true, readOnlyHint=false, and destructiveHint=false. The description adds that the conversation array is for 'reproduction,' implying the tool uses that data to help debug, which is a useful behavioral note. It does not disclose side effects like server-side actions or confirmation, but it does add some 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. It states the purpose upfront and then gives a specific actionable instruction. There is no fluff or redundancy; every word adds 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?

For a tool with 3 parameters and no output schema, the description is fairly adequate: it defines the purpose and gives a usage hint for a key parameter. However, it lacks details on what happens after reporting (e.g., confirmation, error handling) and does not clarify the format of the 'conversation' parameter beyond calling it an array (while schema says string), which could cause confusion. Overall, it covers the essentials but has 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 does add meaning to the 'conversation' parameter by specifying that it should contain recent messages for reproduction. However, it does not mention the 'context' parameter at all, and 'message' is only implied as the content of the report. The schema already provides types and defaults, but the description adds some value for conversation.

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: 'Report a bug, missing feature, or send feedback.' This is a specific verb-resource pairing that distinguishes it from sibling tools like authenticate or show_version. It also includes an additional instruction about the conversation array, which clarifies the function further.

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 a direct instruction: 'Include the conversation array with recent messages for reproduction.' This guides how to use the tool effectively. However, it does not explicitly state when to use this tool over alternatives or when not to use it, leaving usage context partially implied.

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 fully covered. The description adds the specific resource (MCP platform and adapter versions) but no additional behavioral traits beyond what annotations provide. With annotations present, this is acceptable and does not contradict them.

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 with no wasted words. It directly states the tool's purpose without redundancy or unnecessary details.

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 (no parameters, no output schema), the description is complete. It tells the agent exactly what the tool does (show versions) and implies it returns system information. No additional context is necessary for correct invocation.

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 explain parameter semantics. Baseline for 0 params is 4, and the description lacks any misleading parameter information. The simplicity is appropriate.

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 clearly states the resource (MCP platform and adapter versions), which distinguishes it from sibling tools like authenticate or connect. It fully describes the tool's function in one unambiguous sentence.

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 mention when to use the tool or provide exclusions, but the context is obvious: it is a version check tool. No alternatives exist among siblings for this action, so the lack of explicit alternatives is acceptable. The purpose is clear enough for an agent to infer the appropriate usage scenario.

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 destructiveHint=false, so the safety profile is covered. The description adds that it returns specific state details (MCPs, connection status, accounts, tool counts), which is useful. However, it does not mention any potential performance implications or that it might require pre-existing connections, but given the read-only nature, this is acceptable. The description is consistent 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 lists all key information with no fluff. Every phrase adds value (installed MCPs, connection status, accounts, catalog tool counts).

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, the description covers what it returns, which is adequate. It doesn't mention potential use cases or caching implications, but given the simplicity and the annotations (idempotent, read-only), it is sufficiently complete. A brief hint on when to call it would make it a 5.

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 history, so the baseline is 4. The description explains what the returned state includes, which is sufficient given no parameters 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 what the tool does: 'Returns the current toolkit state' and enumerates exactly what is included (installed MCPs, connection status, accounts, catalog tool counts). This is specific and unambiguous for a zero-parameter info tool.

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 guidance on when or how to use this tool. It does not mention typical use cases (e.g., checking connectivity before calling other tools) or relationship to sibling tools like authenticate or connect. The description is purely functional, not actionable.

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