Conselho Regional de Odontologia AL: Cadastro

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

Beyond the annotations (idempotentHint=true, readOnlyHint=false), the description discloses meaningful behavioral context: it triggers a browser login flow, the token is a JWT, the session-only login is non-permanent, and the recommended permanent path is via server config rather than the tool itself. This adds real value beyond 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, front-loaded with the purpose ('log in in the browser, copy the access token'). The second sentence is a bit dense with multiple alternatives ('Best... Or... Or...'), but every clause earns its place and nothing is redundant.

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 1-parameter tool with no output schema, the description covers the authentication flow, both usage modes, token format, and the no-args behavior. Minor gaps exist around return values or post-login confirmation, but the description is largely sufficient for correct tool 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?

With 0% schema description coverage, the description fully compensates by explaining the token parameter: it's a JWT pasted after browser login, optional, and used for session-only authentication. The schema merely defines it as a string, so the description carries the semantic weight.

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: authenticate an IDE agent with MCP.AI by logging in via browser and obtaining an access token. It gives a specific verb+resource and explains the two authentication modes, leaving no ambiguity about what the 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 gives explicit usage guidance for two scenarios: configuring the token as a header for a permanent connection, or passing it as a session-only token. It also explains the no-args behavior (get the link). It doesn't explicitly exclude alternatives or contrast with sibling tools like 'connect', but the mode-based guidance is clear and actionable.

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 as read-only and idempotent. The description adds value by explaining conditional response fields (authenticated, pending[], connect_url) and the behavior under missing credentials, which goes beyond the annotation metadata. It does not fully detail all possible response branches but provides useful insight.

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 deliver all essential information with no fluff. The most critical information (returns status and URLs) is front-loaded, and the conditional logic is succinctly summarized.

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 status-check tool with no output schema, the description covers the main behavioral branches (all connected vs. missing credentials) and clarifies key fields. It does not enumerate the complete response structure, but it is sufficiently complete for an agent to understand the tool's primary purpose and edge cases.

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 schema coverage is trivially 100%. Per the rubric, a baseline of 4 is appropriate since there are no parameters to explain. The description 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 states the tool 'Returns connection status and URLs,' using a specific verb and resource. It distinguishes itself from the sibling 'authenticate' by focusing on status retrieval rather than establishing connections, and the conditional response details add specificity.

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 state when to use this tool versus alternatives like 'authenticate' or 'toolkit_info.' The conditional behavior ('When all providers are connected...') offers context but no direct comparison or exclusions, so usage guidance is only 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 discloses several behavioral aspects beyond annotations: no platform credentials needed, pay-per-query with prepaid credit, data is not confidential, and the client is the data controller under LGPD. These details are useful and do not contradict the annotations (readOnly, idempotent, non-destructive).

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 relatively short but mixes operational details, legal disclaimers, and data sensitivity statements in a somewhat unstructured way. It could be more concise and logically organized, but it is not excessively verbose.

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 does not explain what the tool returns (e.g., registration details, status, success/failure indicators) or how the output is structured. Since there is no output schema, the description should clarify the return value, but it does not, leaving the agent with incomplete context.

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 is 'inscricao', but the description does not explain its meaning, format, or expected values. The name suggests a registration number, but the description provides zero information about it. Since schema coverage is effectively 0%, the description fails to compensate.

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 it is a query for registration from an official source (Conselho Regional de Odontologia AL), but it does not specify exactly what data is returned or what kind of registration (e.g., dentist license, status). It is clearer than a tautology but lacks the precision of a well-defined purpose.

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 operational guidance (hosted by platform, no platform credentials, prepaid credit required) and clarifies that data is non-confidential. However, it does not explicitly state when to use this tool versus alternatives, though the sibling tools are unrelated. The usage context is implied rather than explicitly defined.

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 by explaining key behavioral traits: invoke works even without installation and returns connect or checkout links, writes require owner/admin, and search/describe flag installation status. Since annotations only indicate non-read-only, non-destructive, non-idempotent, this added context is valuable and accurate, with 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 dense paragraph that is front-loaded with the core purpose but then crams in a lot of detail about actions, permissions, and the prompt library without clear section breaks. It is longer than ideal and could be structured with bullets or lists for readability, but it is still informative and avoids 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?

Given the high complexity (23 parameters, 14 actions) and no output schema, the description is quite comprehensive. It covers the workflow, key behavioral nuances (invoke without installation, permission requirements, link returns), and the prompt library distinction. While not every parameter is detailed, the description provides enough context for an agent to navigate the tool effectively.

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)Skip schema coverage, the description must compensate for all 23 parametersoma? It does not individually explain each parameter, but it does clarify the core ones by explaining the 'action' values and their roles (e.g., 'search' discovers MCPs, 'invoke' runs a tool, 'describe' returns a profile). It also mentions 'prompt_body', 'prompt_slug', etc. in context of the prompt library, giving some semantic grounding. However, many parameters like 'immediate', 'tier_slug', 'conversation' are not explained directly, which is a gap.

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 marketplace is the official mcp.ai catalog for finding, describing, and running MCPs, listing multiple specific actions (search, describe, invoke, install, etc.) and the overall workflow. It distinguishes itself from siblings by covering the entire marketplace ecosystem, unlike the other tools which focus on specific functions like authentication or reporting bugs.

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, such as using 'invoke' for one-off runs versus 'install' for permanent additions, and notes that writes require owner/admin permissions. However, it does not explicitly state when not to use the marketplace as a whole or reference sibling tools as alternatives, so it misses some exclusion details.

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=false, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds the key behavioral instruction to include the conversation array for reproduction, which goes beyond annotations and helps the agent provide the necessary context without conflicting with 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 two sentences with zero fluff. Every word adds value—stating the purpose and the key usage guideline. It is appropriately front-loaded and easy to parse.

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 simple (3 parameters, no output schema), and annotations cover safety. However, because the schema provides no parameter descriptions, the description must fill that gap. It only explains the conversation parameter, leaving message and context unexplained. While the purpose is clear, the absence of parameter explanations makes it incomplete for an agent to correctly construct a request, so it falls short of a higher score.

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 explain parameter usage. It explicitly mentions the 'conversation' parameter and how to use it, but it does not clarify the 'message' (which is required) or 'context' parameters. This leaves significant ambiguity about what to put in those fields, meaning the description only partially compensates for the lack of schema documentation.

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.' It uses a specific verb ('report') and resource ('bug/missing feature/feedback'), and it distinctly differs from sibling tools like connect 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 provides clear context on when to use the tool (for reporting issues) and gives an explicit guideline to include the conversation array for reproduction. It does not mention exclusions or alternatives, but the purpose is straightforward enough that this is 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description's 'Show' aligns with these traits. It adds useful specificity by naming platform and adapter versions, confirming a non-mutating informational operation. No contradiction 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 a single focused sentence with no wasted words. It is front-loaded with the action verb and immediately conveys the exact scope of the tool.

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, zero-parameter, read-only version tool with strong annotations, the description is sufficiently complete. It explicitly states what is displayed and implies the return type without needing to describe output schema 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 tool has zero parameters and the input schema is fully covered, so no parameter documentation is needed. The description adds no parameter details, but none are required, earning the baseline score for no-parameter tools.

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 identifies the resource ('current MCP platform and adapter versions'). It fully distinguishes the tool from siblings like authenticate, connect, and marketplace, none of which retrieve version information.

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 use whenever version information is needed, but it doesn't explicitly state when to use this tool versus alternatives or mention exclusions. The context is clear enough for a simple zero-parameter utility, but no comparative guidance is given.

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 readOnlyHint=true and idempotentHint=true, covering the main behavioral aspects. The description adds detail about what the returned state includes, which is consistent and helpful, but does not go beyond what annotations convey.

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 directly states the tool's function without unnecessary words or repetition.

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 absence of an output schema, the description provides a clear summary of the return content (state with MCPs, connection status, accounts, catalog count). It is sufficiently complete for a simple query tool, though it does not specify data types or structure.

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 no parameters, so the schema coverage is complete. The description adds no additional parameter semantics because none exist, matching the baseline of 3.

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 the current toolkit state, listing specific components (installed MCPs, connection status, accounts, catalog count). It effectively distinguishes this from sibling tools like 'connect' or 'authenticate' by focusing on state retrieval.

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 inspecting toolkit state but does not explicitly state when to use it versus alternatives (e.g., 'use this to check status before connecting'). It lacks explicit when/when-not guidance.

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