Registradores (ARISP): Consulta de Informações da Conta

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

Description discloses behavioral traits beyond annotations: it explains the trade-off between permanent (config header) and session-only (token) authentication, and that calling with no args returns a link. Annotations already declare idempotent, and the description reinforces it by indicating that both methods are safe to repeat. No contradiction.

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 many clauses, but it's front-loaded with the key action and provides necessary alternatives. Slightly long but not 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?

The tool has one optional paramtons and no output schema alert. The description explains the two usage modes and the permanent config option, covering the complexity well. It's complete for an auth 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?

Schema defines only token (string) with no description. Description explains its usage: paste the JWT token for a session-only login, or omit to get the link. That's essential meaning beyond schema. Since schema coverage is 0% (no descriptions in schema), description fully compensates.

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 authenticates a user for MCP.AI IDE agents, with a specific verb ('authenticate') and resource (IDE agent access). It distinguishes from siblings by focusing on token-based auth vs other account operations. The alternatives (config header vs session token vs link request) are specific and actionable.

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 when-to-use guidance: recommends the best method (config header for permanent connection) and alternative (paste token for session-only). It also states when to call with no args to get a linkressive. This is clear usage context with alternatives.

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 agent knows it's a safe read operation. The description adds concrete response behaviors (authenticated:true with empty pending[] vs connect_url and per-install URLs) that go beyond annotations, enriching the agent's understanding of what to expect. No contradiction 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?

The description is two sentences, clearly front-loaded with the primary purpose, and every sentence provides useful detail. There is no redundant or filler text, making it appropriately concise.

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 no-parameter status tool, the description covers the two primary scenarios (all connected, missing credentials) and mentions the key response fields. However, it does not explicitly address partial connectivity (e.g., some providers connected, some not), which could be inferred from 'pending[]' but is not made explicit. Given the simplicity and annotation support, this is a minor gap.

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 100% (trivially). Per rubric, the baseline is 4 when there are no parameters. The description does not need to explain parameter semantics since none 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, specifying different responses for connected vs missing credentials. This is a specific verb+resource ('Returns connection status') that distinguishes it from sibling tools like 'authenticate' (which performs authentication) and 'show_version' (which returns version info).

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 this is the tool to check connection status but does not explicitly state when to use it over alternatives or provide exclusions. For instance, it doesn't say 'use this before calling authenticate' or 'use this when you need to see pending installations.' The usage context is implied but not stated.

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?

Beyond the annotations (readOnlyHint=false, openWorldHint=true), the description discloses that writes require workspace owner/admin, that invoke runs one-off without installing or bloating the toolkit, and that missing credentials or empty wallet produce connect/checkout links followed by a retry. This is substantial behavioral context not available from annotations alone.

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 long but front-loaded with the core flow and uses signposts like 'Core flow:' and 'KEY:' to organize a complex 14-action tool. It is dense and mostly non-redundant, though a few clauses could be tightened without losing 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 tool with 14 actions, 23 parameters, no output schema, and minimal annotations, the description covers the main flows, auth requirements, one-off vs permanent behavior, and the prompt library. It does not explain every action/parameter (e.g., resume, immediate, conversation) or return shapes for search/describe/list_tools, but it is sufficiently complete for an agent to select and invoke the 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?

With 23 parameters and 0% schema description coverage, the description compensates by explaining the action enum in prose and giving meaning to key parameters like tool_id, arguments, prompt_slug, and prompt_vars. However, several parameters (limit, query, immediate, tier_slug, conversation, cancel_reason, etc.) are not explicitly described, relying on their names/defaults.

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 opens with a specific definition: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It clearly identifies the resource (MCP/tool catalog) and the actions (search, describe, invoke, install), and distinguishes itself from sibling tools by positioning marketplace as the catalog/runner rather than auth or account 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 gives an explicit core flow: search → describe → invoke, and states when to prefer invoke over install ('prefer invoke for a single/occasional use') and when to use install ('only to make an MCP PERMANENT'). It also clarifies list_tools for currently callable tools and mentions auth/checkout link retry behavior, providing clear when-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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds valuable context: it's a paid service (prepaid credits), hosted by the platform (no platform credentials needed), and the data is not confidential (same as available to citizens). It also mentions LGPD compliance and data controller responsibilities, which is important behavioral context for a data query 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 paragraph of three sentences, which is concise and front-loaded with the core purpose. It packs a lot of information efficiently, though it could be slightly more structured with bullet points for the payment and LGPD details. No wasted words.

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 has 5 parameters, no output schema, and no parameter documentation, the description should provide more guidance on how to use the tool. It covers the business context (payment, hosting, data source) but lacks technical usage details like parameter requirements or expected response format. The annotations help with safety, but the description doesn't fully compensate for the missing parameter semantics.

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 explain any of the five parameters (email, senha, tipo_login, pkcs12_cert, pkcs12_pass). The parameter names are in Portuguese and suggest authentication credentials, but the description doesn't clarify their roles, which ones are required, or how they relate to the login type. With zero coverage and no compensation, this is a significant 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 the tool's purpose: 'Consulta de Informações da Conta' (Account Information Query) for Registradores (ARISP), consulting an official source. It distinguishes from siblings by specifying the domain (registradores) and the action (consult account info), though it doesn't explicitly contrast with other 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 context: it's a paid query using prepaid credits, hosted by the platform, and intended for consulting official Brazilian sources. However, it doesn't explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites beyond the payment model.

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 non-read-only, non-destructive, and idempotent behavior. The description adds the behavioral detail that a conversation array is needed for reproduction, but does not explain side effects (e.g., ticket creation). No contradiction with annotations is present.

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 purpose, and includes only the essential instruction about the conversation array. No unnecessary words.

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?

A simple tool with good annotation coverage; the description is adequate for the core action but leaves 'context' and the exact format of 'conversation' vague, especially since the schema type is string rather than array.

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%, and the description only clarifies the 'conversation' parameter as an array of recent messages. It does not explain 'message' or 'context,' leaving the agent to infer their meanings from the tool's name and defaults.

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 'Report a bug, missing feature, or send feedback,' providing a clear verb and resource scope. This distinguishes it from all sibling tools, which focus on authentication, connectivity, and version info.

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 when to use (when encountering a bug or wanting to send feedback) and instructs to include the conversation array for reproduction. However, it does not explicitly contrast with alternatives, though no sibling tool offers a similar function.

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, openWorldHint=false, and destructiveHint=false, so the description does not need to cover safety. The description adds the specific detail that both platform and adapter versions are returned, which is slightly more informative than the title. Overall, it doesn't add substantial behavioral context 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?

The description consists of one short sentence that completely conveys the tool's purpose. There is no redundancy or filler.

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?

This is a trivial read-only tool with no parameters and no output schema. The description fully explains what the tool does. Given the rich annotations, the description is sufficient to invoke 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?

There are zero parameters in the schema, so the baseline is 4. The description correctly does not address parameters since none exist. No additional semantics 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 uses the specific verb 'Show' and identifies the resource as 'current MCP platform and adapter versions.' This clearly distinguishes it from sibling tools like authenticate or marketplace, which have different 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?

No explicit guidance is provided about when to use this tool versus alternatives such as toolkit_info. The context is implied: use when you need version information. However, there is no exclusionary language or suggested alternatives, so it stops at an implicit level.

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. The description adds meaningful context beyond those flags by specifying exactly what state is inspected (installed MCPs, connection status, accounts, catalog tool counts), which helps the agent predict the tool's informational scope. It does not address potential network latency or stale data, but for a read-only state inspection tool this is adequate.

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, front-loaded sentence that wastes no words. Every clause adds distinct information (installed MCPs, status, accounts, exposure counts) and is immediately scannable.

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 has zero parameters, no output schema, and strong read-only annotations, the description is fully sufficient. It tells the agent exactly what the output will describe, and the sibling context clarifies it as a diagnostic overview tool. No critical 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 tool has zero parameters, so the baseline is 4. Through the schema, there is nothing to document, and the description fully compensates by clarifying what the returned toolkit state contains. No parameter ambiguities 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 uses a specific verb ('returns') and clearly identifies the resource ('current toolkit state'), then enumerates the exact information provided (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from siblings like show_version and 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 implies a clear diagnostic/read-only context: use when you need an overview of the toolkit's MCP connections and capabilities. It does not explicitly name alternatives or state when not to use it, but the sibling set (authenticate, connect, marketplace) makes the division of labor fairly obvious.

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