Conselho Regional de Odontologia PB: Cadastro

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

Annotations show readOnlyHint=false and destructiveHint=false, but the description adds critical behavioral detail: it provides a link for login, accepts a token, and can establish a permanent or session-only connection. It transparently explains the token handling and the config recommendation, which goes beyond annotations. No contradictions.

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 block but dense with actionable info. It could be slightly more structured (e.g., lists), but it is efficient, front-loaded with the purpose, and every sentence contributes to usage or 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?

Given the simplicity (1 optional param, no output schema), the description is complete: it covers both invocation modes, prerequisites (browser, user), and alternative permanent setup. It is sufficient for an agent to execute correctly in both 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?

Schema coverage is 0%, so description is the sole source for parameter meaning. The description explicitly defines the 'token' parameter: it is a JWT string that the user pastes, used for session-only login. It also explains behavior when omitted (returns a link). This fully compensates 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 states the tool's purpose: to authenticate to MCP.AI, providing both a permanent method (via config header) and a session method (token param). It distinguishes it from siblings like 'connect', which is not explicitly clarified but the resource (MCP.AI) and login action are specific.

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 explains when to use this tool (to log in, get access token) and provides two usage scenarios: permanent config vs session-only. It gives concrete steps (browser login, copy token, add to config or paste) and mentions alternative (paste) for session-only, making it clear when to use which approach.

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 tool read-only, idempotent, and non-destructive, so the description does not need to repeat those. It adds useful behavioral detail by specifying return values for both connected and missing-credential states, including `authenticated:true`, empty `pending[]`, and the `connect_url` fields.

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 meaningful detail. No wasted words or redundant restatements 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 with strong annotations, the description is complete. It explains the main response states and the key returned fields without requiring 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 baseline is 4. The description adds semantic meaning by explaining what the response reflects, which is helpful even though no parameter documentation is needed.

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 a specific verb and resource. It also distinguishes itself from the sibling `authenticate` tool by focusing on status inspection rather than credential creation or provider 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 gives clear context for when the tool is useful: checking whether providers are connected and retrieving connection URLs when credentials are missing. It does not explicitly name alternatives, but the role of a read-only status check versus `authenticate` is strongly 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?

The description adds behavioral and compliance context beyond the annotations: the client requires prepaid credit per query, the data is non-confidential citizen-available information, and the customer is responsible for GDPR/LGPD purpose. This is useful information not present in annotations and does not contradict the read-only/idempotent hints.

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 compact and informative, with the main purpose placed first and then the relevant operational/payment and legal context. It does not contain filler or redundant repetition, although the Portuguese phrasing is a bit dense and somewhat compacted into one block.

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 source, payment model, and legal responsibilities well, but it is incomplete in important practical dimensions. There is no output schema and no description of the expected result or input format, so an AI agent cannot confidently predict the required input details or response shape.

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 one required parameter, 'inscricao', with no description at all. The tool description never explains the format, meaning, or accepted value for this parameter, and schema description coverage is 0%. The agent is left without any reliable instruction on how to fill the only required 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 tool identifies a specific resource, CRO-PB cadastro, and describes a query action against an official source. It is more specific than the tool name alone and distinguishes it from unrelated sibling tools like authenticate, marketplace, or report_bug. Still, the phrase 'Cadastro, consulta em fonte oficial' is not as crisp as 'queries the subscription status of a professional', so it leaves some room for interpretation.

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 useful context: the query is a prepaid, citizen-available, official-source lookup and does not require platform credentials. However, it never explicitly says when to prefer this tool over alternatives or how to combine it with authenticate/marketplace, so usage guidance is mostly implied rather than 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?

Beyond the annotations (which only hint at open world and non-idempotent behavior), the description discloses key behaviors: invoke runs one-off even without installation, returns connect links for missing credentials and checkout links for unpaid tools, and states that writes require workspace owner/admin. This gives the agent a realistic picture of side effects and user interactions.

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 dense single paragraph with no visual structure, making it harder to scan despite being content-rich. The core flow is front-loaded and every sentence adds value, but the lack of bullets or section breaks reduces readability for a tool with 14 actions and 23 parameters.

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 high complexity and absence of an output schema, the description covers the main flows, authentication/payment edge cases, permission requirements, and the prompt library. It omits some actions (e.g., resume), immediate behavior, and detailed return formats, but overall provides sufficient context for an agent to select and invoke actions 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?

With 0% schema description coverage, the description must compensate; it explains the action enum and core parameters like tool_id, mcp_id, and prompt_slug in context. However, it leaves many parameters (limit, query, immediate, tier_slug, cancel_reason, prompt_targets, etc.) unexplained, so semantic coverage remains incomplete.

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.ai marketplace, a catalog of MCPs/tools and a way to run them, covering capability requests. It names specific actions and the core flow (search → describe → invoke), distinguishing it as a multi-action orchestration tool rather than a single-purpose utility.

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 usage guidance: 'prefer invoke for a single/occasional use' versus install for permanent toolkit addition, and directs users to request_mcp when nothing fits. It also clarifies list_tools for currently callable tools and subscribe/cancel for billing, giving clear when-to-use versus alternatives.

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 tool is not read-only, not destructive, and idempotent. The description adds one behavioral detail—that conversation data is needed for reproduction—but does not disclose side effects (e.g., whether a ticket is created) or response behavior. 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 one sentence that covers purpose and a key usage instruction without extraneous words. Every clause contributes information, making it concise and front-loaded.

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 low-complexity tool, the description states purpose, usage, and one parameter instruction. However, it leaves the semantics of 'message' and 'context' implicit and gives no indication of what happens after submission or whether a response is returned, which is a notable gap given there is no 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?

Schema description coverage is 0%, so the description must compensate. It mentions the 'conversation array' but the schema defines 'conversation' as a string with default '[]', creating ambiguity about the expected format. It does not clarify the required 'message' or the 'context' parameter, though their names are somewhat 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 uses specific verbs ('Report', 'send') and clearly identifies the tool's purpose: reporting bugs, missing features, or sending feedback. It distinguishes from sibling tools like 'connect' or 'marketplace' by focusing on user feedback rather than other operations.

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 for when to use the tool (for bugs, missing features, or feedback) and includes an explicit instruction to add the conversation array for reproduction. It does not explicitly name alternatives or say when not to use it, but no sibling tool serves a similar reporting function.

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, destructiveHint=false, and idempotentHint=true, so the description's 'Show' aligns with these. However, the description adds no additional transparency beyond what annotations provide, making 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 extremely concise, consisting of a single sentence that directly conveys the tool's function. There is no unnecessary verbosity or redundant 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?

For a simple read-only version check, the description adequately conveys the purpose. It does not specify details like return format or version naming, but given the simplicity, it is sufficiently 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?

There are no parameters in the schema, so the description adds no parameter-specific context. The baseline of 3 applies as the schema fully covers the absence of parameters.

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 shows the current MCP platform and adapter versions, specifying the exact resource and action. It is unambiguous and distinguishes itself from sibling tools that serve different purposes (e.g., authenticate, 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 does not provide any explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or scenarios where it should be avoided. It only states what it does without contextual usage hints.

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 agent knows this is a safe, non-mutating read. The description adds useful behavioral context by specifying what state is reported, including connection status and per-MCP account and catalog-tool counts, which is not inferable from annotations alone.

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 fully specifies the tool's output without redundancy or filler. Every phrase earns its place by adding a distinct category of information returned.

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?

This is a simple, parameterless inspection tool, and the description fully covers the return contents: installed MCPs, connection status, accounts, and catalog tool counts. With no output schema present, this enumerated description is sufficient for an agent to infer what the tool provides, and the annotations cover side-effect 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 tool has zero parameters and the schema is an empty object, so there is no parameter meaning to clarify. The baseline of 4 for a parameterless tool applies, and the description's lack of parameter information is not a deficiency.

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 begins with a clear verb ('Returns') and a specific resource ('current toolkit state'), then enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from siblings like show_version, which focuses on version rather than the broader toolkit state.

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 establishes clear context: this is the tool to call when you need an overview of the toolkit's installed integrations and their statuses. It does not explicitly name alternatives or exclude other tools, but the listed contents make the usage scenario unambiguous relative to the sibling tools.

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