Registradores (ARISP) Matrícula: Lista de Pedidos

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

Annotations already indicate idempotent and non-destructive behavior; the description adds useful context beyond annotations: browser interaction, token copy/paste workflow, permanent non-expiring header config vs session-only login, and no-args behavior. There is no contradiction with 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 compact, front-loaded with the purpose, and uses clear 'Best:' and 'Or' alternatives. It is slightly dense and run-on, but every sentence conveys useful, non-redundant 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 tool with one optional parameter, no output schema, and an authentication workflow, the description covers the full user flow: browser login, token retrieval, permanent config, session token call, and no-args link retrieval. No major context is missing 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?

Schema coverage is 0%, but the description fully compensates for the single optional token parameter. It explains exactly what happens with no args (get the link) and what happens when passing { token: '<jwt>' } (session-only login), adding meaning the schema alone does not provide.

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 function: authenticating an MCP.AI server for IDE agents via a browser login and access token. It uses a specific verb ('log in', 'call with token/no args') and identifies the resource, but it does not explicitly distinguish itself from the sibling tool 'connect', so it falls short of a 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 gives actionable usage guidance: add the token as a permanent config header or paste it for a session-only login, call with no args to get the link, or call with { token: '<jwt>' } after pasting. It does not name when to prefer this over sibling alternatives like 'connect', so it is strong but not fully explicit about exclusions.

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, covering the safety profile. The description adds behavioral context about response content (e.g., when credentials are missing, it returns connect_url and per-install URLs), which is useful but does not disclose much beyond that. It does not contradict annotations, and it adds some value in terms of conditional responses.

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 main purpose, and includes only essential details about conditional behavior. Every word earns its place, with no redundant 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 tool's simplicity (no params, no output schema, simple read-only operation), the description is sufficiently complete. It explains the two main states (connected vs. missing credentials) and indicates what URLs are returned. It could mention edge cases like partial connection states, but nothing suggests that is necessary given the annotations and 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, and schema description coverage is 100%, meaning there is nothing for the description to add. Per the rubric, a baseline of 4 is appropriate for a tool with no parameters, and the description does not need to compensate for any parameter 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, and distinguishes it from siblings by specifying what it returns (authenticated flag and pending array) and when connect_url is provided. It goes beyond a simple verb+resource by detailing the tool's scope and key outputs.

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 when to use it (to check connection status and get URLs), but it does not explicitly state when not to use it or mention alternatives. Sibling tools like authenticate are related, but no explicit guidance is given on when to choose connect over authenticate, so the usage context is clear but not exhaustive.

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 declare readOnlyHint=false, and the description richly corroborates the mutation semantics: writes "require workspace owner/admin," install makes the MCP permanent, and invoke "RUNS that tool... without adding the MCP to the toolkit and without bloating the tool list." It further discloses side-effect-relevant details the annotations couldn't convey: the connect-link auth flow, the checkout/top-up link for empty wallets, retry expectation ("the user opens it, then you retry"), and the sharing-links-without-login behavior for published prompts. No contradiction with annotations — openWorldHint=true is well supported by the discovery-oriented examples.

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?

Every sentence earns its place — there is no fluff, and the density is justified by 14 actions and 23 parameters. However, it is an undifferentiated wall of text with no paragraph breaks, bullets, or section headers; KEY:, Core flow:, and the prompt-library pivot are all run together. Tightening the structure (e.g., separating the prompt-library concern into its own paragraph) would materially improve scannability.

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 this complex — dual concerns (marketplace dispatch + prompt library), auth requirements, billing behavior, and retry semantics — the description is admirably thorough. It covers the full lifecycle including edge cases (tool not installed, missing credential, empty wallet) and even captures the prompt_vars templating convention ("{{variables}}"). Gaps exist but are minor: the `resume` action is never explained, and behaviors like `immediate` or `tier_slug` are unaddressed. Given no output schema exists to offload this burden, a small amount of additional coverage would make it complete.

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% with 23 parameters, so the description must carry the burden. It does an excellent job with the critical `action` dispatch parameter, walking through each enum value (search → describe → invoke; install; subscribe/cancel; the prompt_* trio), and clarifies that `arguments` is a JSON string by defaulting to '{}'. However, many parameters (limit, immediate, tier_slug, conversation, report_context, cancel_reason/cancel_comment, prompt_targets, prompt_category, request_details) are never mentioned, leaving their semantics to inference. The core flow is thoroughly documented; the long tail is not.

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 clear, specific identity — "The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them" — and grounds it with concrete capability examples ("find an MCP that does X", "consulta um CPF"). It differentiates from siblings by naming distinct alternatives (subscribe/cancel, report_bug, request_mcp) and carves out the prompt library as a separate concern. The core search → describe → invoke flow is explicitly distinguished from the install-permanence model, leaving no ambiguity about scope.

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 with named alternatives: "Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use," "request_mcp asks us to build a NEW MCP when nothing fits," and "list_tools lists what is callable right now." The when-not guidance (invoke vs install vs subscribe) is exceptional — rare to see exclusion criteria stated this directly in tool descriptions.

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 valuable context beyond annotations: payment model (prepaid credit per query), absence of platform credentials, official-source nature of the data, LGPD compliance/controller responsibility, and the non-confidential nature of the data. This meaningfully enriches the tool's behavioral profile.

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 compact and front-loaded, opening with the core purpose, then adding billing, data-source, and legal context in three dense sentences. Each sentence provides distinct useful information with 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?

With five opaque parameters and no output schema, the description covers important operational context (hosting, payment, legal) but omits parameter meanings and the return structure of the 'Lista de Pedidos' result. This is adequate but has clear gaps that would require additional investigation by the agent.

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 compensate, but it does not explain any of the five parameters (email, senha, tipo_login, pkcs12_cert, pkcs12_pass). The phrase 'sem credenciais da plataforma' is ambiguous and does not clarify what credentials these parameters represent or how they should be used.

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 a query/list operation ('Lista de Pedidos, consulta em fonte oficial') for Registradores (ARISP) Matrícula, which distinguishes it from all sibling tools (authenticate, connect, marketplace, etc.). The verb and resource are specific and 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?

The description provides clear usage context: it is hosted by the platform, requires no platform credentials, uses prepaid credit per query, and queries official Brazilian sources. It does not explicitly name alternatives or state when not to use it, but it gives enough context for an agent to decide this is the correct tool for consulting registrar records.

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, destructiveHint false, and idempotentHint true, covering the safety profile. The description adds the instruction to include conversation but does not disclose further behavioral details like external transmission or response handling, which is acceptable given the annotation coverage.

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 concise sentences with front-loaded purpose and a direct instruction. No wasted words, appropriately sized for the tool's simplicity.

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 with 3 parameters and no output schema, but the description leaves the 'context' parameter unexplained and does not clarify the conversation parameter's format. For an agent to use it correctly, more detail would be helpful, though it is not severely incomplete.

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 coverage, the description must compensate but only partially does. It highlights the conversation parameter for reproduction but does not clarify that conversation is a string containing an array, nor does it explain the purpose of the 'context' parameter or provide any details about message beyond being required. The description adds nominal value over schema names.

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: reporting bugs, missing features, or feedback, with an explicit instruction to include the conversation array for reproduction. This is specific and distinguishes the tool from unrelated sibling tools like authenticate or 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?

Provides clear usage context by instructing the agent to include the conversation array for reproduction, which helps the agent know what to provide. It does not explicitly state when not to use the tool or compare to alternatives, but since the sibling tools are unrelated, no exclusions are necessary.

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, idempotentHint, and destructiveHint as safe, and the description adds that it displays versions. The description is consistent with annotations and provides sufficient behavioral context for a read-only operation.

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, clear sentence that conveys exactly what the tool does without any unnecessary 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 simplicity of the tool (no parameters, no output schema), the description is reasonably complete. It could specify what 'versions' entail (e.g., platform version, adapter version) but is adequate for a version-check 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?

The tool has no parameters, so the baseline is 4. The description adds no parameter details, but none 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 clearly states the tool shows current MCP platform and adapter versions, using a specific verb and resource. It is distinct from sibling tools like toolkit_info by explicitly focusing on 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?

No guidance is provided on when to use this tool versus alternatives such as toolkit_info. There are no context or usage scenarios described, leaving the agent without direction on selection.

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, covering the safety profile. The description adds value by detailing the specific data returned (installed MCPs, connection status, accounts, catalog tool counts), which is not present in the annotations. No contradictions found.

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 that front-loads the main purpose ('Returns the current toolkit state') and then lists the included details in a compact, readable enumeration. Every word earns its place with 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?

For a simple read-only info tool with no parameters and no output schema, the description sufficiently explains the return contents. It could be more precise about the exact structure (e.g., array vs object), but the listed categories give the agent enough context to understand what the tool provides.

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 is empty with 100% coverage, so the description has no parameter semantics to add. Per the rubric, a baseline of 4 is appropriate for a zero-parameter tool.

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 resource ('current toolkit state'), then enumerates the exact contents (installed MCPs, connection status, connected accounts, catalog tool counts). This clearly distinguishes it from sibling tools like authenticate, connect, and show_version, which serve 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?

The description clearly implies when to use the tool: when you need an overview of the toolkit's installed MCPs, their status, accounts, and catalog tool counts. It provides clear context but does not explicitly state exclusions or name alternative tools, so it falls short of a 5.

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