Sanções União Europeia

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

With annotations already marking idempotent/non-destructive, description adds nuance about permanent non-expiring vs session-only login and the no-arg behavior returning a link. 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?

Content is dense and useful, but the description is a long run-on sentence with several instructional clauses; could be broken into clearer steps without losing 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?

Covers both invocation paths (with token and without), auth modes, and configuration recommendation. Missing explicit return details, but the 'get the link' phrase partially addresses it, and no output schema exists.

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 only parameter, token, is fully explained in prose as an optional JWT to paste, and no-args is described as yielding the link. This compensates for zero schema description 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?

Description clearly states the tool's role: obtaining and applying an MCP.AI access token for IDE agents. It distinguishes session-only vs permanent auth modes, though it doesn't explicitly contrast with sibling '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?

It gives explicit usage contexts: permanent config header vs session-only token paste, and explains when to call with token vs no arguments. No exclusions or alternative tool guidance are provided.

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, so the description does not need to restate safety traits. It adds value by detailing conditional return behavior: authenticated:true with empty pending[] when all providers are connected, and connect_url plus per-install URLs when credentials are missing. This provides context beyond the annotations, though it does not cover partial connection states or error conditions.

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 long, front-loaded with the core purpose in the first sentence, then conditional details in the second. Every sentence provides useful information, with no wasted words or redundancy. The structure is clear and efficient.

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, no output schema), the description adequately covers the key return values and conditions. It explains what happens when all providers are connected and when credentials are missing. However, it does not mention behavior for partial connection states or potential errors, which would make it 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?

The tool has zero parameters, and the schema coverage is 100% (empty properties). Per the rubric, a 0-parameter tool gets a baseline of 4. The description adds no parameter-specific info, but none is needed since there are no parameters to document.

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: 'Returns connection status and URLs.' This specific verb+resource phrasing distinguishes it from siblings like authenticate (which initiates authentication) and show_version (which displays version info), making the purpose immediately apparent.

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 explicitly state when to use this tool versus alternatives. It describes the tool's behavior under different conditions but provides no guidance on when a user should prefer connect over authenticate or other sibling tools. There are no explicit alternatives or exclusions 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?

Beyond annotations (readOnlyHint=false, etc.), the description reveals key behaviors: invoke runs one-off without adding the MCP to the toolkit, auth/payment issues result in connect/checkout links with a retry mechanism, and writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin. It also clarifies that search/describe flag installation status, providing rich behavioral 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 long, but justifiably so for a 23-parameter, multi-purpose tool. It is front-loaded with the core purpose and flow, uses arrows and emphasis ('KEY:') to structure key points, and avoids redundancy. Every sentence adds value, though it could be tightened slightly by omitting minor details like the full list of billing actions, which are already in the schema enum.

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 and 23 parameters, the description is remarkably complete. It covers the primary MCP discovery/execution flow, the one-off invoke exception, auth and payment edge cases, permission requirements, the prompt library, and even notes installed_in_toolkit vs installed_in_workspace. Minor omissions like the 'resume' action and detailed return formats are acceptable given the overall comprehensiveness.

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 parameter coverage, the description compensates thoroughly. It explains the meaning of each action enum value: search discovers, describe returns full profile (including tool id and params), invoke runs the tool, install makes permanent, list_tools shows callable tools, and prompt actions (search_prompts, get_prompt, publish_prompt) are all semantically described. It also ties key parameters like tool_id and prompt_vars to their roles in the flow.

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 is the official mcp.ai marketplace, defining its scope as the catalog of every MCP/tool and the way to run them. It enumerates specific capabilities (search, describe, invoke, install, prompt library) with distinct verbs and resources, and it naturally distinguishes itself from sibling tools by being the central hub for MCP discovery 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 explicitly lays out the core flow (search → describe → invoke) and provides direct comparisons: 'invoke works even when the MCP is NOT installed' vs 'Use install only to make an MCP PERMANENT', and 'prefer invoke for a single/occasional use'. It also names alternatives for specific needs: 'list_tools lists what is callable right now', 'subscribe/cancel handle per-MCP billing', 'report_bug sends feedback', and 'request_mcp asks us to build a NEW MCP when nothing fits'.

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 instructs the user to include the conversation array with recent messages, adding practical behavioral context beyond the annotations. The annotations already declare idempotency and non-destructiveness, and the description complements 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?

The description is a single, focused sentence that directly conveys the tool's purpose and a key usage detail. It is appropriately sized and front-loaded with no waste.

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 few parameters and no output schema, the description, combined with annotations and schema defaults, provides sufficient context for correct invocation. A note about post-report behavior could improve completeness, but it is not essential.

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 must compensate for parameter meanings. It clarifies the 'conversation' parameter's purpose, but 'message' and 'context' are left implied. This provides partial, but not complete, compensation.

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 the tool's function with a specific verb ('report') and resources (bug, missing feature, feedback). This clearly distinguishes it from sibling tools like authenticate and marketplace, 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 ('report a bug, missing feature, or send feedback') and provides context for invocation. It does not explicitly exclude alternatives, but the distinct purpose makes exclusions unnecessary.

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=true, destructiveHint=false, and idempotentHint=true, so the safety profile is known. The description adds valuable context beyond these: it discloses the pay-per-query billing, that the data is from public official sources, and the LGPD legal responsibility of the client. This is meaningful beyond the annotations, though it stops short of describing runtime behavior like response format or hit/miss handling.

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, consisting of four sentences that cover purpose, billing, data nature, and legal responsibility. It front-loads the core functionality. Some wording is slightly verbose (e.g., the parenthetical about citizen accessibility), but overall it is efficient and every sentence adds meaningful 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?

The tool is a simple lookup with two parameters and no output schema, so the description should explain return values or result behavior, but it does not. It also fails to explain the 'completo' parameter. While it covers purpose, payment, and data source, these gaps prevent it from being fully complete for a tool with minimal schema support.

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 two parameters (Nome, completo) with no descriptions, and the tool description provides no parameter details. While 'Nome' is implicitly the name to check, the optional 'completo' parameter is entirely ambiguous. With 0% schema description coverage, the description fails to compensate, leaving the agent guessing about parameter semantics.

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: 'Verifica se um nome consta na lista de sanções financeiras da União Europeia' (Checks if a name appears on the EU financial sanctions list). It clearly states the function and its context ('para diligência de compliance e AML'). No sibling tool is similar, so no further differentiation is 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?

The description provides clear usage context: it is for compliance and AML due diligence. It also notes that it is hosted by the platform, requires no credentials, and is paid per query with prepaid credit, which sets expectations. However, it does not explicitly say when not to use it or mention 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.

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is established. The description adds the specific content (platform and adapter versions) but no further behavioral traits (e.g., no network calls, response shape). This meets the baseline for annotation-supported tools without adding extra 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 clear sentence with no redundant words or repetition. It is perfectly front-loaded and concise.

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?

A simple tool with no parameters, full annotation coverage, and clear purpose. The description fully explains what the tool does, and no output schema is necessary for a read-only version query. Sibling tools are unrelated, so no further context is needed.

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, and the description adds nothing about parameters because none exist. According to the rubric, 0 parameters yields a baseline of 4, which is appropriate here.

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'). It fully defines the tool's scope and is distinct from all sibling tools, which cover authentication, connection, marketplace, bug reporting, and EU sanctions.

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 use when version information is needed, but gives no explicit when-to-use or when-not-to-use guidance. Since none of the sibling tools overlap with version display, the context is implicitly clear, but the lack of explicit direction prevents a higher score.

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 provide readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds context about what data is returned (state details), which aligns with the read-only nature. No side effects are expected, and no contradiction exists.

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, well-structured sentence that front-loads the action ('Returns') and then enumerates the returned components. Every word contributes value with no 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?

For a simple read-only informational tool with no parameters and no output schema, the description provides sufficient context by listing what the state includes. It does not define the exact return format, but that level of detail may not be necessary for this simple 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, so the schema coverage is trivially 100%. The baseline for 0 parameters is 4, and the description does not need to compensate for any 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 uses a specific verb ('Returns') and clearly identifies the resource ('current toolkit state'). It enumerates exactly what is returned (installed MCPs, connection status, accounts, catalog tool counts), which differentiates 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 implies usage: the tool is for querying toolkit state. However, there is no explicit guidance on when to use it versus alternatives, nor any exclusions or prerequisites. The context is clear but not fully developed.

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