Conselho Regional de Odontologia MA: Cadastro

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

Annotations provide idempotentHint and readOnlyHint false, and the description adds meaningful behavior beyond them: no-arg invocations return a login link, token-bearing invocations establish a session-only authenticated state, and config-level tokens avoid expiry. It does not detail error cases, but the important behavioral differences are disclosed.

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?

Three sentences convey the key flows without excessive bloat. The structure is slightly dense, mixing broader setup advice with tool invocation semantics, but it is still efficient and 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?

For a simple one-optional-parameter auth tool with no output schema, the description covers the main actions: retrieving a login link, using a token, and the persistent config alternative. It would be more complete with a note on what the tool returns after a successful token-based login, but the core context is sufficiently covered.

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 carries the full burden. It explains the token parameter as an optional JWT to paste for session-only login and explicitly describes the no-argument behavior. The description stops short of specifying token constraints like expiration or scopes, which is a minor 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 specifies an authentication/login action: 'log in in the browser, copy the access token', 'session-only login', and 'get the link'. It names the resource/context (MCP.AI for IDE agents), so the purpose is clear, though it does not explicitly contrast itself with the sibling tool '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 gives explicit usage guidance: call with no args to get the login link, call with a token to complete session-only login, and prefer adding the token as an Authorization header for a permanent connection. It also distinguishes persistent configuration from session-scoped login, which helps the agent decide how to proceed.

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 description adds value by detailing response scenarios: authenticated:true with empty pending[] in one case, and connect_url with per-install URLs in another. This goes beyond annotation-provided safety cues.

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 clear sentences with no redundancy. The first sentence states the main purpose, and the second adds conditional details in a scannable way.

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-input, no-output-schema status tool, the description covers both key response states. It does not detail the contents of pending[] or clarify the structure of per-install URLs, but that is minor 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 tool has zero parameters, and schema coverage is vacuously 100%. The description appropriately avoids repeating parameter info; baseline for a zero-parameter tool is 4.

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?

Description uses specific verb 'Returns' and identifies the resource 'connection status and URLs'. It clearly distinguishes from sibling 'authenticate' by focusing on status reporting rather than the authentication action.

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?

Description provides conditional context for when all providers are connected versus when credentials are missing, making the tool's behavior predictable. It does not explicitly mention alternatives, but the sibling list implies the distinction from 'authenticate'.

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 read-only and idempotent hints, and the description adds that it requires payment, is not confidential, and involves LGPD responsibilities for the client, going beyond the structured annotations. 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 moderately sized block of text with several sentences covering purpose, hosting, payment, and legal aspects. It is not overly verbose, but some details like LGPD compliance could be considered background context rather than essential usage 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?

Given the single parameter and no output schema, the description should at least clarify the input and expected output. It explains the purpose and payment but omits any explanation of the registration number format or what the response will contain, leaving the agent with insufficient information 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 schema has one required parameter 'inscricao' with zero description coverage. The description does not explain what 'inscricao' refers to or provide any format or meaning beyond the name, so the parameter semantics are not conveyed.

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 consult the registration in the Regional Council of Dentistry MA (Cro MA) from an official source. It uses a specific verb ('consultar') and resource ('cadastro') and distinguishes from siblings by naming the specific council and consultation type.

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 explains it's a paid service using prepaid credit and is for official data, implying legitimate verification use. However, it doesn't provide explicit when-to-use or when-not-to-use guidance or mention alternatives, as siblings are unrelated.

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?

Adds substantial behavior beyond the sparse annotations (readOnlyHint=false, openWorldHint=true). It discloses the key one-off execution trait ('invoke works even when the MCP is NOT installed... without bloating the tool list'), the auth and payment flows ('returns a connect link'; 'returns a checkout/top-up link... then you retry'), permission requirements ('Writes... require workspace owner/admin'), and published-prompt behavior ('opens without login'). Nothing contradicts 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?

Dense and front-loaded with the most important facts, but rendered as a single unbroken ~350-word paragraph with no line breaks or section headers, which hurts scannability for an agent parsing quickly. The prompt-library content is tacked on with 'It also carries...' and demonstrates the wall-of-text issue. The Portuguese 'consulta um CPF' mixed into English prose is a minor quality quirk.

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 extreme complexity (14 action values, 23 params, 0% schema coverage, no output schema), this is strong but incomplete. It thoroughly covers the search→describe→invoke flow, auth/checkout, permissions, and prompt-library functions. Gaps: action=resume is in the enum but never explained, parameters like immediate, tier_slug, conversation, prompt_targets, and report_context are undefined, and no return-format info is given — but the core user journey is well covered.

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 across 23 params, the description carries the full burden. It meaningfully explains the critical dispatch parameter (action) by walking through each value: search, describe, invoke, install, list_tools, subscribe/cancel, report_bug, request_mcp, search_prompts, get_prompt, publish_prompt. However, 22 other parameters are never explicitly mapped, and action=resume from the enum is never mentioned — though many (query, limit, mcp_id, tool_id) are self-explanatory by name.

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 opening sentence states precisely what the tool is: 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' This is a specific verb+resource statement that names the subject and immediately distinguishes it from siblings (authenticate, connect, report_bug, show_version, toolkit_info) which cover different concerns. It also enumerates the capability requests it serves, making the purpose 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?

Excellent when-to-use guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT in the active toolkit'; 'list_tools lists what is callable right now'; and 'request_mcp asks us to build a NEW MCP when nothing fits.' It also clearly separates the prompt-library actions from MCP actions, preventing misuse between the two domains.

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 and destructiveHint=false, which the description does not contradict. The description adds the important instruction to include the conversation array for reproduction, which goes beyond the schema. However, it does not disclose any side effects (e.g., data being sent externally) or success/failure behavior, leaving room for improvement.

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 only two sentences long, starting with the primary purpose and then providing a crucial usage tip. Every word contributes value, and there is no filler or redundancy.

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 reporting tool with three flat string parameters and no output schema, the description covers the key usage point (including conversation). It might benefit from a note about expected response or action taken, but overall it is sufficiently complete for an agent to decide to use it 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 for parameter meanings. It explains the 'conversation' parameter's purpose ('recent messages for reproduction') but says nothing about 'context' or 'message.' Since 'message' is self-explanatory and required, and the description adds some value, a middle score 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 clearly states the tool's purpose: 'Report a bug, missing feature, or send feedback.' This uses a specific verb and resource, and it is distinct from sibling tools, which include authentication, connection, and info 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 provides clear context for when to use the tool by listing 'bug, missing feature, or send feedback.' It also offers a usage hint about including the conversation array, but does not explicitly exclude alternatives or mention when not to use it. Since siblings are not similar in purpose, this is adequate.

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 covered. The description adds that it reports platform and adapter versions, which is useful context beyond annotations, but it doesn't disclose any additional behavioral traits (e.g., rate limits, auth requirements).

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 with no superfluous words. It is front-loaded with the action and resource, making it easy to scan.

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, rich annotations), the description is fully adequate. It states exactly what the tool returns (versions) and needs no further elaboration.

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 parameter semantics are a non-issue. The baseline for 0 params is 4, and the description correctly focuses on what the tool does rather than parameter details.

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 verb ('Show') and resource ('current MCP platform and adapter versions'), distinguishing it from sibling tools like authenticate or connect. The purpose is unambiguous and 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 does not explicitly state when to use this tool versus alternatives, but for a simple version lookup tool no exclusions are necessary. It is clear that this is for checking versions, which is implicit usage 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 establish read-only, idempotent, non-destructive behavior, so the description adds value by disclosing the output contents and emphasizing that the returned data reflects the current state. It 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?

A single sentence front-loads the purpose and then uses a colon to efficiently enumerate the return details. Every element is informative, with no filler or repetition of schema or annotation data.

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, zero parameters, and existing annotations, the description is complete enough for an agent to invoke it confidently. It fully describes what the response will cover despite there being 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?

The tool has zero parameters, so the baseline is 4 and the description does not need to explain parameter semantics. The empty schema already fully covers this aspect, and the description appropriately focuses on the returned state.

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 ('Returns') and clearly names the resource ('current toolkit state'), then enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it well from siblings like connect, authenticate, and 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?

The description clearly implies the tool is for inspecting toolkit status, but it does not explicitly state when to use it instead of alternatives or mention any exclusions. It relies on the reader to infer the usage context from the purpose.

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