INPI: Processo de Registro de Marca (Resumida)

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

The description clarifies session-only vs. permanent non-expiring connection behavior, which goes beyond the annotations (idempotentHint=true, readOnlyHint=false). It does not contradict any annotation and adds meaningful behavioral context about two authentication paths.

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 reasonably concise and each sentence carries useful information, but the run-on style and inline asides make it slightly less scannable than ideal. It is still appropriately sized for the tool's complexity.

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 covers both invocation modes, the permanent vs. session distinction, and the link retrieval flow. Since there is no output schema, it would benefit from stating explicitly what happens after a successful token submission, but the overall picture is complete enough 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?

With 0% schema description coverage, the description fully compensates by explaining the token parameter's meaning (a JWT access token), its optionality, and the different outcomes when passed vs. omitted. This is essential guidance not present in the 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 identifies the tool's purpose: authenticating MCP.AI for IDE agents via browser login and access token. It provides a specific action (log in, copy token, authenticate) and distinguishes itself from sibling tools like connect by detailing the auth flow.

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 guidance on when to use each invocation mode: configure a permanent header token vs. paste a session-only token, and call with no args to get the link. It lacks an explicit comparison to sibling tools like connect, but the usage context 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 indicate a safe, read-only operation, and the description adds value by disclosing specific return states: authenticated:true with empty pending[], or connect_url for the toolkit and per-install URLs when credentials are missing. This exceeds the minimal annotation coverage and provides actionable context about what the user can expect, including non-obvious behavior regarding pending[].

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 concise sentences, front-loaded with the primary purpose and then detailing behavior. Every sentence delivers essential information without fluff, and the structure is clear and skimmable.

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 no parameters and no output schema, the description sufficiently covers the main use cases: both the fully connected and missing-credentials scenarios. It explains the return values and URLs, making it complete for the simplicity of the 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 zero parameters, and the schema is fully covered at 100% (no properties). Per the baseline rule for 0 params, a score of 4 is appropriate because there is no parameter information to add; the description focuses on output behavior rather than inputs, which is acceptable.

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: 'Returns connection status and URLs.' This is a specific verb+resource combination, distinguishing it from siblings like 'authenticate' which handles authentication flow. It explains the output in different states, making the purpose 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 explains behavioral outcomes ('When all providers are connected... When credentials are missing...') but does not explicitly state when to prefer this tool over alternatives like 'authenticate' or 'toolkit_info'. It implies usage for checking connection status but lacks clear guidance on when to use versus not use, or reference to sibling tools.

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 mark the tool read-only, idempotent, and non-destructive. The description adds useful context not in annotations: prepaid billing, absence of platform credentials, the official/non-confidential nature of the data, and LGPD data-controller responsibility. There is 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 purpose is front-loaded and the description is not excessively long, but it repeats 'fonte oficial' and spends multiple sentences on compliance and privacy context. The legal/billing details are relevant, but the description 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 single-parameter read-only query tool, the description provides adequate context: what it queries, from where, payment requirements, credential requirements, and privacy responsibilities. The lack of an output schema is not a major issue given the simple 'resumida' (summary) nature of the 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 schema has one required string parameter, numero_processo, but the description does not explain its expected format or provide examples. With schema description coverage at 0%, the description does not compensate for this gap; it only indirectly hints at the process via the tool 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 description clearly states the tool's purpose: 'consulta' (query) of an INPI trademark registration process summary from an official source. The verb and resource are specific and distinct from the generic sibling tools like authenticate and 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 gives clear usage context: it is hosted by the platform, requires no platform credentials, and is paid per query with prepaid credit. It does not explicitly name alternatives or exclusions, but the context is strong enough for an agent to know when to invoke it.

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 are sparse (only flags), so the description carries the burden. It discloses that writes require workspace owner/admin, invoke works even for uninstalled MCPs and runs one-off without adding to toolkit, and returns connect/checkout links for auth/payment needs. It doesn't mention idempotency or side effects beyond these, but the annotations already indicate non-idempotent and non-destructive, so no contradiction and adequate detail.

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 but logically organized: starts with purpose, then core flow, key invoke behavior, install distinction, writes permissions, and prompt library. No fluff; every sentence adds value. It's long but warranted given the tool's breadth. Slight loss for lack of visual structure (headings/bullets) but efficient overall.

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 23 parameters, multiple actions, and no output schema, the description covers the essential behavior comprehensively: discovery, invocation, installation, billing, authentication, permissions, and prompt library. It addresses key edge cases (auth/checkout links) and clearly explains the invoke-vs-install distinction. Complete enough for an agent to select and call 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?

Schema coverage is 0%, so the description should compensate. It explains the key action parameter by outlining each action in the flow (search, describe, invoke, install, etc.) and mentions tool_id for invoke. However, it doesn't systematically cover other parameters like limit, query, immediate, tier_slug, or prompt-specific fields, leaving gaps for less central params. Partial compensation but not full.

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 this is the official mcp.ai marketplace, functioning as both a catalog of all MCPs/tools and the mechanism to run them. It defines the core flow (search→describe→invoke) and distinguishes itself from sibling tools like authenticate and connect by focusing on discovery, invocation, and tool management.

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 explicitly explains when to use invoke vs install ('prefer invoke for a single/occasional use,' 'use install only to make an MCP PERMANENT'), mentions list_tools for currently callable tools, and states that search/describe are for discovery. It also clarifies the prompt library usage with search_prompts, get_prompt, and publish_prompt, giving clear guidance on 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 indicate the tool is not read-only, not destructive, and idempotent. The description adds the requirement to pass conversation history for reproduction, giving context on how the tool should be used. It does not contradict 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 short sentences, front-loaded with the verb 'Report' and the resource. Each sentence earns its place: the first states the purpose, the second gives essential usage guidance. No 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 relatively simple tool with no output schema/nested objects, the description covers the main purpose and the key parameter (conversation). It leaves a minor gap on the 'context' parameter, but it's optional and has a default. Overall, it is sufficiently complete for an agent to understand the tool's role and usage.

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 explicitly explains the 'conversation' parameter's purpose ('recent messages for reproduction'), but does not clarify 'context' beyond its default. Since the main actionable parameter is explained, this adds meaningful semantic value.

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 the action (report) and the target (bug, missing feature, or feedback). Also provides a usage hint about including conversation history, which differentiates it from sibling tools that perform other tasks like authentication or marketplace operations.

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 tells the user to include the conversation array for reproduction, which implies the intended use case. It does not explicitly list alternatives or exclusions, but the purpose is unambiguous and distinct from sibling tools.

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 (readOnlyHint: true, idempotentHint: true, destructiveHint: false) already convey the safe, read-only nature. The description is consistent with annotations but doesn't add behavioral context beyond stating what it does (e.g., no mention of latency, network calls, or error cases).

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?

One short, clear sentence with no wasted words. Front-loaded verb 'Show' immediately conveys action.

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, parameterless read-only tool with no output schema, the description fully explains what it does. Nothing more is needed for an agent to select and invoke 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?

Zero parameters and 100% schema coverage, so the description doesn't need to explain any. Per rubric, 0 params = baseline 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?

Uses specific verb 'Show' + resource 'MCP platform and adapter versions,' clearly stating the function. Sibling tools (authenticate, connect, marketplace, etc.) don't overlap with version display, so no explicit distinction needed.

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?

Usage is implied rather than explicit. The description doesn't state when to use this vs. alternatives, but the purpose is straightforward enough that a user can infer when to invoke it. No exclusions or alternatives mentioned.

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 readOnly, idempotent, and non-destructive behavior. The description adds valuable context about the exact content of the returned state (including account connections and catalog tool counts), going beyond mere 'state' and providing behavioral insight into what the caller can expect.

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. It is concise, well-structured, and contains no redundant or ambiguous wording.

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?

Since no output schema is provided, the description must explain the return value, and it does so comprehensively by listing all components. Combined with the annotations (readOnly, idempotent), the context is complete for the agent to understand the tool's function.

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 is nothing to describe. The description correctly focuses on the output. This fully covers the parameter semantics; no further clarification 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's purpose: it returns the current toolkit state, enumerating specific details (installed MCPs, connection status, accounts, and exposed catalog tools). This is a precise verb-resource pairing and distinguishes it from sibling tools like connect or authenticate.

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 no guidance on when to use this tool versus alternatives. It does not mention scenarios, prerequisites, or conditions under which this tool is preferred. This leaves the agent without contextual direction.

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