Conselho Regional de Odontologia AP: Cadastro

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

Annotations already declare idempotentHint=true (safe to repeat) and readOnlyHint=false. The description adds context about the token flow and session vs permanent modes, but does not disclose side effects, success/failure behavior, or post-auth state changes. It complements 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 moderately concise but packs three distinct usage instructions into two sentences. It is front-loaded with the purpose and quickly delivers actionable steps without filler, though it could be slightly tighter.

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 an authentication tool with no output schema and one optional param, the description fully explains how to invoke it and the two login strategies. It lacks explicit return-value details, but for a login endpoint, the expected outcome is implicit. The description is sufficient given the tool's simplicity.

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 parameter 'token' has zero schema description. The description compensates by explaining that it's optional, used for session login with a JWT, and that calling with no args returns a 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 it is for authenticating with MCP.AI for IDE agents, explaining the token-based login process. It specifies the resource (MCP.AI) and the action (log in, copy token, add to config or paste). It does not explicitly distinguish from sibling 'connect', but the overall action is 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?

It gives two distinct usage paths: permanent via config header and session-only via token argument, plus a no-arg fallback to get the link. It clearly indicates when each method is appropriate, though it does not mention alternative tools or exclude 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, destructiveHint=false, and idempotentHint=true, so the safety profile is established. The description adds value by explaining the two possible response states (authenticated:true with empty pending[], or with connect_url and per-install URLs), which goes beyond the annotations. However, it doesn't fully elaborate on the connection behavior or why a caller might see each state.

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, zero wasted words, and the critical behavior is front-loaded. The description earns its place by revealing both normal and edge-state responses without 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 zero-parameter status-checking tool with clear annotations and no output schema, this description is complete. It covers the success case, the error case, and differentiates itself from 'authenticate' and 'toolkit_info' siblings. No output schema exists so return values don't need documentation beyond what's given.

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 0 parameters and schema coverage is 100%, so the description is not burdened with documenting parameters. The baseline of 4 applies given no parameters exist and the description sufficiently explains the return behavior. Minor deduction because the description could explicitly state it takes no input, though this is minimal.

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', specifies the resource (connection status), and the behavioral detail about authenticated:true and pending[] distinguishes it from related tools. Despite being a sibling of 'authenticate', this is clearly the status-check variant, providing strong differentiation.

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 clear context on when to expect certain outputs (when all providers are connected vs. when credentials are missing). It doesn't explicitly name sibling alternatives or state 'use X instead', but the context for use is strongly implied by describing the two states. A small deduction for not explicitly mentioning when this tool should not be used or what alternatives exist.

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 context about official data sources, non-confidential nature, and LGPD responsibility, which goes beyond the annotations. However, it does not elaborate on error handling, rate limits, or other behavioral aspects, so it adds only moderate transparency.

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 with redundant phrases like 'fonte oficial' and 'fontes e órgãos oficiais', but it is not overly long. It lacks structured formatting such as bullet points or bulleted usage notes, though it is readable.

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 there is no output schema, the description does not explain what the tool returns (e.g., fields, structure). It also omits the meaning of the 'inscricao' parameter and how the query works, leaving the tool's full functionality underdescribed.

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 'inscricao' is not described in the schema or the tool description. The description mentions 'cadastro' but does not explain what 'inscricao' represents or what format is expected, leaving the parameter ambiguous.

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 indicates a query tool for registration data from the Regional Council of Dentistry, with 'consulta em fonte oficial' and 'consulta informação' specifying the action. It is somewhat general about the exact data returned, but the purpose is evident.

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 mentions payment via prepaid credits and lack of platform credentials, but does not compare with alternative tools or specify when this tool should be preferred over others. No explicit guidance on usage scenarios beyond the query itself.

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 annotations by disclosing that writes require workspace owner/admin, that invoke works without installation, and that it returns connect or checkout links for auth/payment. These are valuable behavioral details not inferred from 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 lengthy but logically structured, starting with the core flow, then invoking details, then other actions. However, it has some redundancies and could be more concise by using bullets or segmentation.

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 23 parameters, the description covers all major actions and the invoke edge cases (auth/payment, permissions), plus the prompt library. It lacks fine-grained details on some actions like resume or list_tools, but overall provides sufficient context for an agent to understand the tool's scope.

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%, and the description does not systematically explain parameters like arguments, immediate, tier_slug, prompt_vars, etc. While it mentions some (query, mcp_id, tool_id) in the flow, it lacks a mapping of parameters to actions, leaving many fields ambiguous.

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 official mcp.ai marketplace, covering discovery, description, and invocation of MCPs, plus the prompt library. It names specific actions and the overall flow, clearly differentiating it 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?

It provides explicit guidance on when to use each action: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', and clarifies the core flow from search to describe to invoke. It also notes prerequisites like auth/payment links.

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 cover safety (readOnlyHint false, idempotentHint true). The description adds that the conversation array is needed for reproduction, which is useful behavioral context. However, it doesn't disclose other behaviors like whether data is transmitted, rate limits, or expected response.

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 with no fluff. The primary purpose is front-loaded, and the key instruction about the conversation array is presented directly.

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 core purpose and one key parameter, but given 3 parameters and no output schema, it doesn't fully explain what happens after reporting, nor the 'context' parameter. It is adequate for a simple tool but has clear gaps.

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 the description must compensate. It explains the 'conversation' parameter's purpose but leaves 'context' undefined and only implies 'message' is the bug/feedback content. The description doesn't provide enough detail for all three 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 uses a specific verb 'Report' with clear resources (bug, missing feature, feedback). It distinguishes itself from sibling tools like 'authenticate' or 'connect' which have unrelated purposes.

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 clear context for when to use the tool (reporting any issue or feedback) and instructs the agent to include the conversation array for reproduction. It doesn't explicitly list alternatives, but the sibling tools are clearly unrelated, so usage is well 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 annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description only adds that the tool reports platform and adapter versions, without detailing return format or potential error behavior; this is sufficient but not rich.

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 the action verb front-loaded and no unnecessary words. Every part of the sentence contributes to understanding the tool's purpose.

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 low complexity, empty schema, and strong annotations, the description is largely complete by stating the exact information returned. However, with no output schema, a bit more detail about the return format would be beneficial, so it is not a perfect 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, and the schema explicitly documents an empty properties object with 100% coverage. With no parameters, the baseline is 4, and the description does not need to add parameter-level 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 uses the specific verb "Show" with a clear resource: current MCP platform and adapter versions. This clearly distinguishes it from sibling tools like authenticate, connect, and marketplace, which address different concerns.

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?

Usage is implied: call when version information about the MCP platform or adapters is needed. However, the description does not explicitly mention alternatives or state when not to use this tool, leaving usage guidance implicit rather than explicit.

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 and non-destructive, and the description adds value by specifying exactly what data is returned (installed MCPs, statuses, accounts, counts). It goes beyond annotations by detailing output structure, though it does not mention potential errors or latency.

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 that efficiently states the action and the key return facets. No fluff, all content is meaningful.

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?

With no output schema, the description fully describes the return payload. Combined with strong annotations and zero params, it provides complete context for correct use.

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 need not explain them. Baseline for 0 params is 4; description is entirely sufficient in this dimension.

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: returns current toolkit state with specific details (installed MCPs, connection status, accounts, catalog tool counts). It distinguishes from sibling tools like authenticate or connect, which are action-oriented, making it obvious this is an informational read.

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 toolkit state but does not explicitly contrast with alternatives like show_version or provide when/when-not guidance. It lacks exclusions or recommended contexts, so it's adequate but not proactive.

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