INPI: Patentes

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

The description discloses key behaviors beyond annotations: it returns a login link when called without arguments, accepts a token for session-only auth, and explains the difference between permanent and session connections. It aligns with idempotentHint=true and does not contradict any annotation.

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 well-structured, front-loading the core purpose, then providing best-practice guidance, and ending with exact invocation patterns. Every sentence adds value without 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 covers all essential aspects: usage context, argument handling, return behavior (getting a link), and persistence options. It is fully self-contained.

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?

Although the schema has no description for the token parameter, the description fully explains its semantics: it expects a JWT string for session-only login, and omitting it triggers the link generation. This compensates entirely for the 0% schema coverage.

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 authenticate the MCP.AI server via browser login and token capture. It distinguishes itself from siblings by focusing on the authentication flow, and it explains both permanent and session-only methods with specific instructions.

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 explicitly explains when to use the tool (to authenticate) and provides clear guidance on two usage modes: permanent setup via config header or session-only via token argument. It also directs the agent to call with no args to get the login link, making the usage unambiguous.

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 behavioral context about return values (authenticated:true, empty pending[], connect_url) which is useful, but does not disclose any side effects or additional behaviors beyond what annotations imply. 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?

Two sentences, front-loaded with the core purpose, and every clause adds value. No fluff or repetition.

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 zero parameters, no output schema, and clear annotations, the description is complete enough. It explains the two main output states and what URLs are returned. It could mention whether the tool requires prior authentication, but that is implied by the connection status context.

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 schema provides no parameter semantics. The description compensates by explaining the output states (all providers connected vs. missing credentials), which is the only relevant semantic context. Baseline 4 for zero-param tools 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 returns connection status and URLs, and distinguishes it from siblings like authenticate and toolkit_info by focusing on status/URLs rather than actions or general info. It could be more explicit about the resource being 'connection' but is specific enough.

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 when credentials are missing), but does not explicitly state when not to use it or mention alternatives like authenticate for establishing connections. The context is clear but exclusions are absent.

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, idempotentHint, destructiveHint=false, so the safety profile is covered. The description adds context about authentication (no platform credentials, paid per query with prepaid credit) and LGPD compliance, which goes beyond annotations. However, it does not detail what happens on failure or the exact nature of the data returned. It adds some value but not a high level of 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 paragraph with mixed information: it states purpose, hosting, payment model, and legal compliance. It is relatively concise but could be better structured with front-loaded purpose and separate notes. Some details (e.g., platform hosting) seem extraneous for tool selection.

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 is a simple query with no output schema and annotations cover safety, the description is fairly complete. It mentions the payment model and legal aspects, which are useful. However, it lacks detail on what constitutes a valid query (e.g., CPF vs CNPJ) and potential limitations, but given the simplicity, it is adequate.

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%, meaning the schema has minimal descriptions (just parameter names). The description does not elaborate on the parameters 'cpf' and 'cnpj' beyond what the names imply. It doesn't say whether both are needed, what format, or whether they are optional. With zero coverage, the description should compensate but does 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 states it consults INPI patent information in official sources, but the verb 'consultar' is specific enough. It does not explicitly differentiate from sibling tools, though siblings are unrelated (authentication, connection, marketplace, etc.), so the context implies it is a standalone query tool. Purpose is clear but could be sharper.

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 specify when to use this tool versus others. It mentions it is for official Brazilian sources, which gives some context, but no direct exclusions or alternatives. Usage context is implied but not explicit.

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 only provide readOnlyHint=false and destructiveHint=false, but the description adds substantial behavioral context: invoke runs one-off without installing, returns connect/checkout links when credentials or payment are missing, writes require workspace owner/admin, and search/describe flag installation status. No contradictions 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 dense but organized: core flow, key behavioral difference, usage preference, permission note, then prompt library. Each clause adds unique information, and the length is justified by the tool's 14-action surface. Slightly more structured formatting (e.g., bullets) would be easier to scan, but the current structure is logical.

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 hub tool with 14 actions and no output schema, the description covers discovery, invocation, installation, billing, bug reports, MCP requests, and prompt library, plus auth/payment edge cases and permission levels. It gives the agent enough context to select and invoke the right action in most scenarios without needing to guess.

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 and 23 parameters, the description carries the burden and does so well by narrating the action enum in context (search, describe, install, invoke, subscribe, cancel, etc.) and mentioning mcp_id/tool_id implicitly through 'every tool with its id + params'. However, several parameters (limit, immediate, tier_slug, prompt_vars, conversation) are left unexplained, so it doesn't fully compensate.

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 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them', immediately establishing both the resource and its dual role. It then enumerates capability requests and the search→describe→invoke flow, making it clearly distinct from sibling tools like authenticate or 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?

Explicitly contrasts when to use invoke vs install: 'prefer invoke for a single/occasional use; install only to make an MCP PERMANENT'. It also maps each action to a scenario (report_bug, request_mcp, prompt library), giving the agent concrete decision guidance and 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 indicate idempotent and non-destructive behavior, and the description mentions including the conversation array for reproduction. However, it does not clarify what happens after reporting or any side effects 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 is a single, succinct sentence with no redundant words, fully fitting the tool's simple nature.

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, the description lacks essential details about parameter usage and expected output format. It leaves 'context' and 'message' unexplained, making the tool insufficiently described for a user 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?

The description only hints at the 'conversation' parameter's purpose (for reproduction). 'Context' and 'message' are left undefined, and the 'conversation' parameter is a string but likely expects a JSON representation, which is not explained.

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 sending feedback. It is distinct from sibling tools which serve unrelated 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 description implicitly indicates when to use the tool (when a bug or feedback arises), but does not explicitly contrast with alternatives. Given the dissimilar sibling tools, 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 clear. The description adds only 'current' versions and does not disclose return format or additional behavioral details, but for a trivial read-only version query this is acceptable.

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 with no filler. Every word contributes to identifying the tool's purpose.

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-parameter, read-only utility with strong annotations, the description is mostly complete. It identifies the two things shown (platform and adapter versions), though it does not specify the output format; this is a minor gap 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, so there is no parameter documentation burden. The description correctly omits parameter details, matching the baseline of 4 for tools with no parameters.

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 and resource: 'Show the current MCP platform and adapter versions.' It clearly identifies exactly what the tool does and is sufficiently distinct from sibling tools like toolkit_info, which implies broader metadata rather than version specifics.

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 intended usage is implied: an agent would call this whenever current platform/adapter version information is needed. However, it does not explicitly mention when not to use it or name alternative tools, so the guidance is implicit rather than explicit.

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, destructiveHint=false, and idempotentHint=true, so the safety profile is covered. The description adds value by detailing exactly what information is returned, which goes beyond the annotations and clarifies the tool's read-only nature.

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, tightly written sentence that front-loads the core action and enumerates the key output elements. There is no wasted wording 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?

Given the tool has no output schema, the description fully explains what the state includes. It covers all relevant aspects (installed MCPs, connection status, accounts, catalog tool counts) and is complete for a simple informational 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 zero parameters and 100% schema coverage, the description doesn't need to elaborate on parameters. This matches the baseline for a parameterless tool, and the description correctly focuses on the output content instead.

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' with concrete details (installed MCPs, connection status, accounts, catalog tools). This differentiates it from sibling action tools like authenticate 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 purpose is clear and the tool's role as a status/inspection tool is evident from the phrasing. It doesn't explicitly state when not to use it or name alternatives, but the description implicitly covers the appropriate use case without ambiguity.

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