Conselho Regional de Odontologia BA: Cadastro

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

Annotations indicate readOnlyHint=false and idempotentHint=true, and the description adds valuable behavioral context: it explains that providing a token results in a session-only login, while configuring as a header gives a permanent connection. It also implies that calling with no args returns a link. This goes beyond the annotations without contradicting 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 front-loaded with the core action and then expands into usage details. It is somewhat dense with parentheticals and options, but each clause serves a purpose. Slightly verbose, but not wasteful.

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 moderate complexity (authentication with two modes), the description covers invocation, persistence, and token usage. There is no output schema, but the description implies the tool returns a link or confirmation, which is sufficient for an auth tool. It provides enough context without requiring additional 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 single optional parameter 'token' is well-explained: it is used for session-only login by pasting the JWT, and omitting it triggers the link retrieval. Although schema description coverage is 0%, the description compensates fully for the one 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: to authenticate by logging in via browser and obtaining an access token, with options for permanent or session-scoped tokens. It is not a tautology and identifies the key action (authenticate/log in), but it does not explicitly differentiate from the sibling 'connect' 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?

Provides explicit usage guidance: recommends adding the token as a header for a permanent connection, or pasting it for a session-only login. It also explains two invocation modes (with token argument or no arguments to get a link), leaving no ambiguity about when and how 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the description does not contradict them. It provides additional context about return states (authenticated:true vs connect_url), which is valuable beyond the structured 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?

Two sentences, no fluff, immediately states the purpose and key behavior. Every sentence 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?

Since there is no output schema, the description adequately explains the two main return scenarios (authenticated:true with empty pending[], or connect_url for toolkit and per-install). It could mention the content of the pending array or edge cases, but it is sufficient for a zero-parameter 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?

The tool has zero parameters and the schema is fully covered with an empty object, so there are no parameter semantics to explain. The baseline of 4 is appropriate 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 the tool returns connection status and URLs, using a specific verb and resource. It distinguishes itself from siblings like 'authenticate' by focusing on status 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 usage for checking connection status but does not explicitly say when to prefer this over 'authenticate' or other sibling tools. Adding a note like 'Use this to verify connectivity before invoking actions' would improve 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 mark the tool as readOnly, idempotent, and non-destructive-play, which the description enforces by calling it 'consulta'. The description adds that data is not confidential and that the client is the data controller, which is useful. However, it does not describe the output format, potential errors, or that payment is deducted per query (beyond prepaid credit). Adds some value but lacks depth.

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, front-loaded with the purpose, followed by billing and legal notes. It is efficient and to the point, without excessive fluff. Good structure for a value-added description.

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 a simple read-only consultation with one parameter. The description covers the source (official), the context (CRO-BA), payment, and legal compliance. Missing details like the exact type of registration (e.g., dentist number) and expected output format. A bit more context would make it complete, but it's adequate for a straightforward query.

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 0% description coverage for the single parameter 'inscricao'. The description mentions 'Cadastro' which implies it's the registration number, but it never explicitly defines the parameter's format or meaning. Given zero schema descriptions, the description should compensate more but 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 clearly states the tool consults registrations from the Regional Council of Dentistry of Bahia (CRO-BA). It uses the verb 'consultar' and specifies the data source (official registry). The purpose is unambiguous, though it does not explicitly contrast with sibling tools.

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 mentions the payment model (pay per query with prepaid credits) and legal responsibility for LGPD compliance, but does not explain when to use this tool vs. others, or the required input format for 'inscricao'. Some usage context is provided, but it's incomplete.

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 only provide generic hints, so the description carries the burden and delivers: invoke can run non-installed MCPs, returns connect or checkout/top-up links with retry guidance, install makes tools native in future sessions, and publish_prompt returns a login-free shareable link. 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?

Dense but organized: opening definition, arrow-based core flow, KEY note, permission note, then prompt-library section. Every sentence carries functional information, though length could benefit from bullet structure.

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 14-action, 23-param dispatcher with no output schema, it covers the essential workflow, auth/billing branches, permanent-vs-once semantics, permissions, and an entire secondary prompt-library feature set. It does not spell out return shapes for search/list_tools/install, but the action-level behavior is sufficiently specified.

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 coverage, the description adds substantial meaning to the main action enum and core fields (tool_id selection, prompt vars via {{variables}}, prompt slug via publish link, billing fields via checkout). However, several optional params (arguments, limit, immediate, conversation, prompt_targets, cancel_reason) are only inferable from names or enums, so not all 23 params are clarified.

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?

First sentence identifies the tool as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' with capability-request examples. It then enumerates each action's role (search, describe, invoke, install, list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt library), making it distinct from sibling tools like authenticate or show_version.

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 lays out a Core flow (search→describe→invoke), contrasts invoke (one-off, no install) with install (permanent toolkit membership), and advises 'prefer invoke for a single/occasional use.' Also specifies when list_tools, subscribe/cancel, report_bug, request_mcp, and prompt-library actions are appropriate, plus owner/admin requirements for writes.

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 idempotent hint and non-destructive behavior, so the description is not required to repeat those. It adds a useful instruction to include the conversation array for reproduction, which is beyond annotations but does not fully disclose side effects or auth requirements. It provides some added context but not rich 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?

Two sentences, front-loaded with purpose, and the second sentence adds a practical instruction. Every word earns its place with no redundancy or fluff.

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, the description covers purpose and one key parameter instruction. However, it omits parameter details for 'message' and 'context,' does not mention output or side effects (though annotations cover safety), and gives no guidance on alternative tools. It is adequate but has clear gaps in parameter coverage.

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 (array for reproduction) but does not elaborate on 'message' (the core required field) or 'context.' Only one of three parameters gains clarity, which is insufficient given the low 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 with a specific verb and resource: 'Report a bug, missing feature, or send feedback.' It distinguishes itself from siblings like authenticate, connect, and marketplace by focusing on issue reporting, which is unique among the sibling tools.

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 usage for reporting issues but does not explicitly exclude alternative uses or reference sibling tools for other purposes. The context is clear enough that an agent would know when to invoke this tool, though it lacks explicit 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, so the safety profile is fully covered. The description adds the fact that it reports 'current' versions, but does not disclose return format or any runtime dependencies; this is adequate but not beyond baseline.

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 sentence with a front-loaded verb and no extraneous content. Every word contributes to the meaning.

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, read-only tool with no inputs and no output schema, the description covers all relevant context. It clearly states what the agent can expect to learn: the current platform and adapter versions.

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 an empty input schema, so there are no parameter details to add. The description compensates appropriately; the baseline of 4 for a zero-parameter tool is met.

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 names the exact resource ('current MCP platform and adapter versions'), making its purpose unambiguous. It naturally distinguishes itself from sibling tools like authenticate, connect, and report_bug.

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 intended use is implied by the simple version-focused wording, but there is no explicit guidance on when to use it versus alternatives or when it would be diagnostically appropriate. For a trivial version check this is acceptable, but the description does not provide clear context or 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 provide the safety profile (readOnlyHint=true, destructiveHint=false, idempotentHint=true), so the description doesn't need to repeat those. It adds value by detailing the return fields, but it doesn't disclose other potential behavioral nuances like latency or prerequisites, which is acceptable for a simple read-only 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 sentence, front-loaded with 'Returns the current toolkit state', and lists all four return categories without any fluff or redundant wording.

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 parameterless read-only tool with strong annotations and no output schema, the description fully covers what the agent will get: installed MCPs, connection status, connected accounts, and catalog tool counts. It is sufficiently complete for this level of 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, so the baseline is 4. The description correctly focuses on the return value since there are no inputs to explain, and the schema also confirms no parameters are 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 states the exact verb and resource: 'Returns the current toolkit state', and enumerates the contents (installed MCPs, connection status, accounts, catalog tool counts). It clearly distinguishes itself from sibling tools like authenticate and connect, which are action-oriented rather than state-inspecting.

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 a clear usage context: use this when you need the overall toolkit status, such as installed MCPs, connections, and tool counts. It does not explicitly mention when not to use it or offer alternative tool guidance, so it's just short of a 5.

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