Registradores (ARISP) Matrícula: Novo Pedido de Visualização de Matrícula

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

The description explains key behavioral aspects beyond annotations: it differentiates between permanent (config) and session-only (token) logins, and notes that calling with no args returns a link. It discloses that the token is a JWT and that the config method creates a non-expiring connection. Annotations only indicate idempotency and non-destructiveness, so the description adds valuable context 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 concise and well-structured. The first sentence states the purpose, the second gives the best practice, and the third explains the two calling modes. Every sentence contributes essential information 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 with one optional parameter and no output schema, the description is complete. It covers all usage paths (config, token, no args), describes the token format, and implies the return (link) when no args are given. Annotations provide safety hints, so no gaps remain.

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 only specifies 'token' as a string, with no description. The description fully compensates: it explains that token is an optional JWT, that providing it logs in for the session, and that omitting it returns the login link. This gives complete semantic meaning beyond the raw 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 the tool's purpose: to log in via browser and obtain an access token for MCP.AI IDE agents. It explicitly mentions the action (log in, copy token) and the resource (MCP.AI for IDE agents). It distinguishes from siblings like 'connect' by focusing on authentication, though it doesn't explicitly compare with other tools, so not a full 5.

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 usage instructions: either add the token to the server config for a permanent connection or pass it as a parameter for a session-only login. It also explains when to call with no args to get the link. However, it does not explicitly state when to avoid using this tool or mention alternative tools, so it lacks exclusionary 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?

The annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is clear. The description adds specifics about return format (authenticated:true, empty pending[], connect_url for toolkit and per-install URLs) which goes beyond annotations. However, it does not explain potential edge cases like partial connectivity or what happens when authentication expires. Given annotations cover the basic safety, a 3 is appropriate.

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, front-loads the core purpose, and provides conditional details efficiently. Every word earns its place without 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?

Given the simple 0-parameter tool with rich annotations (readOnly, idempotent, non-destructive) and no output schema, the description adequately covers purpose and output conditions. It is not described what the connect_url looks like or how to act on the status, but that may be beyond scope. It could be more explicit about how to get authenticated, but that is likely the role of 'authenticate'. So it is complete enough for its purpose.

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 description coverage is 100% (empty schema). Since there are no parameters to document, the description does not need to add parameter meaning. Baseline 4 applies for 0 params.

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 returns connection status and URLs, distinguishing it from siblings by focusing on status and URLs rather than authentication actions (authenticate) or general info (toolkit_info). It is not a mere restatement of the name '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 explains the output based on connection state but does not explicitly state when to use this tool versus alternatives. It implies it is for checking connection status, but no explicit comparison to sibling tools like authenticate or show_version is given. There is no explicit 'when not to use' 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?

The description goes well beyond the annotations by disclosing that invoke works even when the MCP is not installed, does not bloat the tool list, and may return connect or checkout links. It also states that writes require workspace owner/admin. These behavioral details are valuable and do not contradict 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?

The description is dense but well-structured, leading with the core flow and using 'KEY:' to highlight the most important invoke behavior. It is a long single paragraph, but given the tool's 14 actions and 23 parameters, the length is justified and nearly every sentence adds useful 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 complex, multi-action tool with no output schema and minimal annotations, the description covers the main workflows, auth requirements, one-off versus permanent installation, billing actions, and the prompt library. It gives enough context for an agent to select the right action and invoke it correctly in most 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?

With 0% schema description coverage, the description carries the burden of explaining parameters, and it does so for the critical ones: action values, mcp_id, tool_id, arguments, prompt_slug, prompt_vars, and publish_prompt's shareable link. However, several parameters like limit, immediate, tier_slug, conversation, cancel_reason, and report_context remain unexplained, so it does not fully compensate for the schema's lack of descriptions.

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 defines the tool as 'the official mcp.ai marketplace' and explains its dual role: cataloging MCPs/tools and running them. It specifies the core flow (search → describe → invoke) and distinguishes the prompt-library sub-features, making the overall purpose unmistakable even with multiple actions.

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 explicit when-to-use guidance: 'prefer invoke for a single/occasional use' versus 'use install only to make an MCP PERMANENT.' It also explains what to do when credentials are needed or the wallet is empty, and names alternatives like list_tools, subscribe/cancel, report_bug, and request_mcp. This is exemplary 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?

The description is transparent about payment requirements, lack of platform credentials, official data origin, and LGPD compliance. It aligns with readOnly and idempotent annotations, though it does not mention potential errors or rate limits.

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 run-on sentence with redundant phrasing, such as repeating 'consulta em fonte oficial' and later 'consulta informação de fontes e órgãos oficiais brasileiros'. While not excessively long, it could be more streamlined.

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?

No output schema is provided, and the description does not specify what information the query returns, error handling, or usage examples. It lacks details on how the prepaid credit model works or what happens with missing or invalid parameters.

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 lists 10 parameters with no descriptions, and the description contradicts the presence of credential-like fields (email, senha, pkcs12_cert, pkcs12_pass) by stating 'sem credenciais da plataforma'. Required parameters like matricula, uf, municipio, cartorio are not explained, leaving ambiguity about their format or purpose.

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 operation for viewing a property registration (matrícula) from ARISP, with mentions of official sources and prepaid credits. It is distinct from sibling tools like authentication or marketplace, though the verb 'consultar' is implicit rather than explicit.

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 a pay-per-query model and official data source, but does not explicitly state when to use this tool over alternatives. No clear conditions or exclusions are provided, leaving the agent to infer the appropriate context.

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 convey idempotentHint=true, readOnlyHint=false, and destructiveHint=false. The description adds the behavioral detail that conversation data should be included for reproduction, but it does not disclose side effects (e.g., whether a ticket is created, response behavior, or rate limits). This is consistent with annotations but provides moderate additional 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?

The description is a single, concise sentence that front-loads the purpose and includes a specific usage note. Every word earns its place, and there is no repetition of annotations or schema details.

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 has 3 parameters, no output schema, and no nested objects, so the description's job is moderate. It covers the core purpose and highlights the conversation parameter, but it omits the meaning of the optional context parameter and does not mention that conversation is a JSON string. This leaves some gaps for an agent to infer 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?

The schema has 0% description coverage, so the description must compensate. It explains the conversation parameter ('Include the conversation array with recent messages for reproduction'), which adds meaning beyond the raw schema. However, it does not clarify the context parameter or the exact format of the conversation string (likely JSON), leaving those partially 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 explicitly states the tool's purpose: 'Report a bug, missing feature, or send feedback.' This is a clear verb-plus-resource construction that covers the main use cases. It also distinguishes itself from sibling tools, which are all unrelated (e.g., authenticate, marketplace, 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 provides clear contexts for when to use the tool (reporting bugs, missing features, or feedback). It does not explicitly mention exclusions or alternatives, but the sibling tools are unrelated, so no real competition exists. The instruction to 'Include the conversation array with recent messages for reproduction' gives actionable guidance, but lacks an explicit when-not-to-use clause.

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 aligns with the annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false) but adds little beyond them. It specifies that both platform and adapter versions are shown, which is a minor addition, but does not elaborate on output format or side effects. With annotations already covering safety, a baseline score is appropriate.

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 fully conveys the tool's purpose without superfluous details. It is well-structured 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?

Given the tool's simplicity, no parameters, and strong annotations, the description is complete. It provides all necessary context for an agent to understand what the tool does and when to invoke it.

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 input schema has zero parameters, so there are no parameter semantics to explain. The description is not required to add anything for parameters, and the 100% schema coverage implies full clarity.

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 resource ('MCP platform and adapter versions'), making the tool's purpose clear. It also distinguishes itself from sibling tools like authenticate, connect, and marketplace, which serve different functions.

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 context of when to use this tool is clear—it is for checking version information. No exclusions or alternatives are mentioned, but given the tool's simplicity and unique purpose, the usage is self-evident.

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, covering safety profile. The description adds value by listing exactly what information is returned (installed MCPs, connection status, accounts, tool counts), which is behavioral detail beyond 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?

Single sentence, front-loaded with the core action and resource, then enumerates the return contents. Zero wasted words; ideal for a simple read-only 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?

Tool is simple with no parameters and no output schema, but description fully enumerates what is returned. Annotations cover safety traits. Nothing is missing for an agent to understand and invoke this tool 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?

Tool has zero parameters, so description adds no parameter-specific semantics. Baseline of 4 is appropriate since there is no parameter ambiguity to resolve.

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?

Clearly states it returns the current toolkit state and enumerates the specific details: installed MCPs, connection status, accounts, and catalog tool counts. Distinguishes from siblings like show_version (which likely returns version info) and marketplace (which lists available 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 implies usage for checking the toolkit's current status, but does not explicitly contrast with sibling tools or state when to prefer this over others. No when-not or alternative recommendations are given, though the purpose is clear.

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