OFAC (Sanções EUA)

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

Beyond the annotations (idempotent, non-destructive), the description discloses the behavioral flow: calling with no args generates a login link, and calling with token performs session-only authentication. It also clarifies the permanence difference between the config header and the token input. This adds useful context not captured by annotations, though it doesn't describe the exact return value or failure modes.

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 information-dense and covers all necessary points in a single (albeit long) sentence. It is not as cleanly structured as it could be, but every clause adds value, and the length is appropriate for the content.

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 largely complete. It explains the login flow, token usage, and provides a best-practice alternative (config header). It doesn't cover error scenarios or post-auth behavior, but these are not critical given the tool's simplicity and the existing annotations.

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 defines `token` as a string with no description. The description compensates fully: it explains the token is a JWT obtained from the browser, that it is optional, and that omitting it yields a login link while providing it enables session authentication. This gives complete semantic meaning to the parameter.

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 authentication. It distinguishes itself from siblings by being the only authentication-related tool, and it details two usage modes (config header vs. token parameter). The verb 'log in' and resource (server authentication) 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 explicit when-to-use guidance: it recommends adding the token to the server config for permanent connection (alternative to using the tool) and using the tool for session-only login. It also specifies exactly when to pass `token` versus call with no args to get the link, covering both invocation paths and the alternative.

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 and destructiveHint, so the description adds value by describing conditional return states: authenticated:true with empty pending[], or connect_url when credentials are missing. This explains behavior beyond the annotation flags.

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, front-loaded with the main purpose. No redundancy or filler content.

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?

Simple tool with no parameters and no output schema; description adequately covers the two primary output states. Minor omission: does not explain the 'pending' array contents, but not critical for understanding 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?

Tool has 0 parameters, so the schema fully defines the input (none). Description does not need to explain parameters; baseline 4 applies.

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?

Description clearly states the tool returns connection status and URLs, with a specific verb 'returns' and a clear resource. This differentiates it from sibling 'authenticate' which likely initiates authentication.

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 on when to use this tool versus alternatives. The conditional output implicitly hints at checking authentication, but it does not directly state 'use this to verify connection' or contrast with 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?

Beyond the annotations (readOnlyHint=false, openWorldHint=true), the description adds valuable behavioral context: invoke runs tools even when not installed, returns connect/checkout links when credentials/payment are needed, and 'Writes require workspace owner/admin.' It also clarifies the distinction between permanent install and one-off invoke, and the prompt library's separate purpose. Minor gaps remain (e.g., no explicit disclosure of uninstall side effects), but overall it is highly transparent.

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 dense block of text (~200 words) but every sentence contributes meaningful information about core flow, edge cases, permissions, or the prompt library. It is front-loaded with the purpose and clearly organized, although bullet points or short sections would enhance scannability. It is appropriately sized for a tool with 14 actions.

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 this complexity and no output schema, the description covers the major workflows, permissions, and special link behaviors. However, it omits return values for several actions (search, describe, list_tools), does not explain parameters like immediate or conversation, and leaves out error handling and edge-case behaviors (e.g., resume). It is useful but not fully 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?

With 23 parameters and 0% schema description coverage, the description must compensate heavily. It explains the meaning of the action values and the key tool_id parameter, but many parameters (limit, immediate, tier_slug, conversation, prompt_vars, cancel_comment, etc.) are not semantically described. The description focuses on behavior and flow, leaving parameter mechanics largely to the schema, which has no 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 opens with 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' which clearly defines the tool's role. It also explicitly covers capability requests and describes the core search→describe→invoke flow, distinguishing it from sibling 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 description provides explicit usage guidance: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT.' It also explains when to use list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt library functions, offering clear alternatives and reasoning.

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 readOnly, idempotent, and non-destructive behavior. The description adds valuable context: no credentials required, cost per query via prepaid credit, data is public access, and LGPD responsibilities for the client. This goes beyond annotations and helps the agent understand the operational and legal aspects.

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, front-loading the purpose, then providing operational, access, and compliance details. Every sentence 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?

The description covers the tool's purpose, hosting, billing, public data nature, and LGPD context. However, it does not specify the return value format or any output, which would be helpful given the lack of an output schema. Still, for a simple read-only lookup, the description is nearly 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 description coverage is 0%, and the description does not explain the parameters ('Nome', 'Sobrenome', 'completo'). It only implies a name is checked, but does not clarify the required split between first and last name or the meaning of the 'completo' boolean. The description fails to compensate for the lack of schema documentation.

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 function: it checks whether a name appears on OFAC sanctions lists, including SDN and Non-SDN, for compliance and AML due diligence. This is a specific verb ('Verifica') and resource, and it distinguishes the tool from the unrelated sibling 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 provides clear context for when to use the tool: for compliance and AML due diligence of names against US sanctions lists. It also adds operational context (hosted by platform, no credentials, prepaid credit) but does not explicitly mention when not to use it or compare with alternatives. Since all siblings are unrelated, this is sufficient.

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 adds little behavioral context beyond the annotations. It instructs including the conversation array but does not disclose what happens after reporting, whether it creates a ticket, or any side effects. With only basic annotations (readOnlyHint, destructiveHint, idempotentHint), the description carries some burden but fails to provide meaningful behavioral 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 only two sentences, immediately stating the tool's purpose and the key usage instruction. It is front-loaded with the action, and every word earns its place with no fluff or repetition of 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?

For a simple reporting tool with no output schema, the description covers the main action and one key parameter. However, it omits explanation for the 'context' parameter and does not address what the user should expect after submission. It is minimally complete but leaves gaps in parameter semantics and behavioral outcomes.

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 for all parameter meanings. It explicitly mentions the 'conversation' parameter ('Include the conversation array') but does not describe 'message' (required) or 'context' (optional). The purpose of 'message' is implied via 'send feedback,' but 'context' remains unexplained, leaving significant 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's purpose: 'Report a bug, missing feature, or send feedback.' It uses a specific verb and resource, and the purpose is distinct from sibling tools like authenticate or connect, making it 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 implies usage by stating what the tool does and instructing to include the conversation array for reproduction. However, it does not explicitly mention when to use this tool versus alternatives or provide exclusions. No clear context beyond the action itself.

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 value by specifying exactly what is shown (MCP platform and adapter versions) and that they are 'current,' providing context beyond the annotations about the tool's output focus.

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 immediately communicates the tool's purpose. No unnecessary words or redundancy. It is perfectly sized 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 (zero parameters, safe read operation), the description sufficiently covers the necessary context. It explains what the tool returns (the versions), and with no output schema, this is adequate. The presence of sibling tools like toolkit_info does not create ambiguity that requires further elaboration.

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, the input schema fully covers parameter semantics (coverage 100%). The baseline for no parameters is 4, and the description does not need to add parameter details. It effectively communicates that the tool takes no arguments.

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' with a clear resource: 'the current MCP platform and adapter versions.' This unambiguously defines the tool's function and distinguishes it from sibling tools like authenticate, connect, and marketplace, which serve entirely 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 usage guidance is provided, but the purpose strongly implies this tool is for checking version information. There are no alternatives mentioned, and the context of sibling tools suggests when to use it is evident, but the instruction does not explicitly state when/when-not to use 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 already declare readOnlyHint=true and destructiveHint=false, and the description's 'Returns' is consistent with this. The description adds valuable context about the content of the state (installed MCPs, connection statuses, accounts, catalog counts), enriching the agent's understanding of the response without contradicting 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 sentence that immediately states the action ('Returns') and lists specific data categories, with no redundant phrases. It is front-loaded and concise, earning full marks.

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 parameterless info tool with annotations providing safety cues, the description sufficiently covers the return content. It does not need to explain return format or side effects because there are none, and the description is complete for its 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 takes zero parameters and the input schema is empty, so the description does not need to explain parameters. The baseline for 0 params is 4; the description adequately conveys the tool's interface.

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 identifies the resource 'current toolkit state,' enumerating exact data categories (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from sibling tools like authenticate or connect, which perform actions rather than report state.

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 indicates the tool provides state information, so an agent would use it when needing an overview of the toolkit. It does not explicitly name alternatives or exclusions, but the context of sibling tools (auth, connecting, marketplace) implies a distinct informational role, earning a 4 rather than a 5.

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