Sanções Suíça (SECO)

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

The description adds useful behavioral context beyond annotations, such as 'permanent, non-expiring' vs 'session-only' login. It does not contradict the idempotentHint or other annotations, though it does not describe all edge behaviors (e.g., 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?

The description is somewhat dense but front-loaded with the purpose and login flow. Every sentence carries essential information, though the 'MCP.AI for IDE agents' prefix could be clearer for general context.

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 no output schema, the description sufficiently explains the authentication flow, token handling, and connection persistence. It covers all key aspects needed for correct invocation.

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 only 'token' with no description, but the description explains its meaning ('jwt'), optionality (call without args to get link), and usage scenarios. This fully compensates 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 IDE agents via browser login and token. It distinguishes the tool from siblings like 'connect' and 'marketplace' by specifying the login flow and token handling.

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?

Explicit guidance is provided: when to use (for IDE agents), how to use (no args to get link, or with token), and alternatives (config header vs session-only paste). This fully covers when and how to invoke the tool.

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, idempotentHint, and destructiveHint. The description adds behavioral detail beyond these: what happens when all providers are connected (authenticated:true, empty pending[]) and when credentials are missing (returns connect_url and per-install URLs). This is valuable context with 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 only two sentences. The first sentence front-loads the core purpose ('Returns connection status and URLs'), and the second sentence efficiently covers the two main behavioral states. 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?

The description covers the two primary states and provides relevant URLs. It does not explicitly describe a partial-connection state or define what pending[] means, but given the tool's simplicity, rich annotations, no output schema, and zero parameters, it is sufficiently 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?

The tool has zero parameters, and the input schema confirms this with an empty properties object. The description doesn't need to add parameter information; the baseline for a no-parameter tool is 4, and the description meets that baseline.

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 it returns connection status and URLs, and clarifies the two distinct scenarios (all providers connected vs credentials missing). This clearly differentiates it from sibling tools like authenticate and show_version, 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 provides clear context on when to use the tool by describing the two possible outcomes, implying it should be used to check connection status. However, it doesn't explicitly name alternatives or state when not to use it, so it lacks explicit 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?

It discloses that invoke works even for uninstalled MCPs, returns connect links for auth and checkout links for payment, notes that writes require owner/admin, and explains that search/describe flag installation status. These details go well beyond the generic annotations (readOnlyHint=false, destructiveHint=false) and provide essential operational context.

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 that covers many distinct topics (marketplace, invoke behavior, install vs invoke, prompts). Although each sentence adds information, the lack of structure makes it harder to parse. It could be split into sections or bullets for better readability.

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 and 23 parameters, the description gives a strong high-level overview and covers the main flow, but it does not specify return values for all actions (e.g., search, list_tools, subscribe) or explain all parameters. It is helpful but not fully complete for a tool of this complexity.

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 explains the core action, mcp_id, tool_id, and arguments through the flow, and touches on prompt-related parameters. However, many parameters (immediate, conversation, tier_slug, request_details, etc.) remain unexplained. With 0% schema description coverage, it only partially compensates for the lack of formal parameter 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 clearly identifies the tool as the official mcp.ai marketplace for discovering and running MCPs, and explicitly covers capability requests like 'find an MCP that does X'. It outlines the core flow (search → describe → invoke) and distinguishes this aggregate tool from sibling tools such as authenticate, connect, and toolkit_info by focusing on catalog exploration and execution.

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 decision guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT'. It also clarifies when to use list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt library actions, giving clear context for when this tool is appropriate versus 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 idempotentHint=true, readOnlyHint=false, and destructiveHint=false. The description adds the requirement to include a conversation array for reproduction, which is useful but does not disclose e.g. side effects like data being sent to a server. With annotations present, 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?

A single, front-loaded sentence that perfectly communicates the tool's purpose and a key instruction. No filler words or 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 simple feedback tool with no output schema, the description covers purpose and a usage hint. It could mention the context parameter or what happens after reporting, but overall it is complete enough for the tool's straightforward nature.

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 must compensate. It explains the 'conversation' parameter ('Include the conversation array with recent messages for reproduction'), and 'message' is implied as the bug/feedback text. However, the 'context' parameter is not explained at all, leaving a 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: 'Report a bug, missing feature, or send feedback.' This is a specific verb and resource, and it distinguishes the tool from unrelated siblings 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?

The description gives explicit context for when to use the tool (for bugs, features, feedback) and even includes a usage hint about including the conversation array. It does not explicitly exclude alternatives, but none of the sibling tools are similar, so clear context 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?

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds substantial behavioral context: no credentials required, prepaid credit payment, access to public official information, and LGPD data-controller responsibilities. This enriches the agent's understanding of cost, auth, and legal implications 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 three sentences long, with the core purpose front-loaded in the first sentence. The additional sentences about hosting, payment, and LGPD are relevant to a compliance tool but could be perceived as slightly verbose. It remains concise and well-structured.

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 no output schema, so the description should describe return values or response behavior. It does not mention what the tool returns (e.g., boolean, list of matches) or the semantics of 'completo'. While the core purpose and context are covered, this missing functional detail leaves the description 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?

Schema description coverage is 0%, so the description must compensate. It clarifies 'Nome' implicitly ('verifica se um nome') but leaves the boolean 'completo' completely unexplained. With two parameters, one is undocumented, and the description does not fully compensate for the schema's lack of parameter details.

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: 'Verifica se um nome consta na lista de sanções internacionais da Suíça (SECO)', with a specific verb (verifica) and resource (sanctions list). It also specifies the use case (compliance and AML due diligence), distinguishing it 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 ('para diligência de compliance e AML') and mentions the pay-per-query model, but it does not explicitly exclude alternatives or state when not to use it. However, siblings are unrelated platform utilities, so no direct alternative is available.

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, idempotentHint, and destructiveHint. The description adds no extra behavioral context beyond the verb 'show,' which is consistent with the read-only, non-destructive nature. No additional disclosure is necessary 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?

The description is a single concise sentence containing only the essential information. It is front-loaded and contains no unnecessary words 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 the tool's simplicity, no parameters, and comprehensive annotations covering safety, the description is fully complete. No output schema exists, so explaining return values is not required.

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 an empty input schema, so there is no parameter information to explain. The description correctly implies no inputs are needed, earning the baseline of 4 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 clearly states a specific verb (Show) and resource (current MCP platform and adapter versions), distinguishing it from sibling tools like authenticate or report_bug. The scope is unambiguous and directly reflects the tool name.

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 when-to-use guidance or alternative comparisons are provided. Usage is implied by the self-descriptive name and description, but the description does not explicitly differentiate from potentially overlapping tools like toolkit_info.

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 valuable detail about the exact contents of the returned state, going beyond the annotations without contradicting them.

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?

Single sentence, front-loaded with the key verb and object, and efficiently enumerates the included information without any wasted words. Every element earns its place.

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 status tool with no parameters and no output schema, the description fully captures what is returned and is sufficient for an agent to decide when to call it. The read-only annotations complement the description well.

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 baseline is 4. The description adds no parameter details because none exist, and no parameter documentation is needed. It appropriately describes what the tool will return.

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 a specific verb ('Returns') and clearly identifies the resource ('current toolkit state') with enumerated contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from siblings like show_version, connect, 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 makes the informational purpose clear, implying use when one needs to inspect toolkit state, but it does not explicitly state when to use this tool versus alternatives or list exclusions. Usage is implied rather than explicitly guided.

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