Sanções Reino Unido (HM Treasury)

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

Annotations already indicate idempotent and non-destructive, and the description adds context about session-only login and the two modes (token vs no args). It could disclose how the session token is stored or what happens on invalid token, but it adds meaningful behavioral context beyond 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, dense sentence that packs a lot of information. It front-loads the purpose and then covers the permanent vs session distinction. Slightly convoluted with the 'Best' phrase, but still efficient and readable.

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 one-param optional tool, the description covers the main flows well: getting a link and submitting a token. It does not describe the output schema, but no output schema is provided. It also doesn't mention error cases, but for an auth tool this is reasonably 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 schema has no description for the `token` parameter (0% coverage). The description compensates fully by specifying it as a JWT, explaining that it is optional (call with or without args), and how to obtain it. This adds significant meaning beyond the bare 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 states that the tool handles authentication by accepting a JWT token or returning a login link. It distinguishes from siblings by specifying MCP.AI for IDE agents, and the verb 'authenticate' plus resource 'access token' makes 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?

It explicitly explains when to use the config header (permanent) versus the tool (session-only), and that calling with no args starts the login flow. This gives clear context and alternatives, which is exactly what is needed.

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 conditional return behavior (all connected vs missing credentials), which is valuable context beyond annotations. No contradictions noted.

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 primary purpose, followed by concise conditional details. No fluff 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 zero-parameter, no-output-schema tool, the description covers the main behavior in two states, which is sufficient. It could mention partial connection states, but the given coverage is adequate. Annotations cover safety, so the description doesn't need to repeat that.

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 schema coverage is trivially 100%. The description adds no parameter info, but none is needed. Baseline for 0 params is 4, and the description provides useful context about return values 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 clearly states the tool returns connection status and URLs, with specific behaviors (authenticated:true, empty pending[], connect_url). This distinguishes it from siblings like authenticate (which likely initiates auth) and 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?

The description provides clear context: it is a read-only status check. It implies when to use it (to check connection status) but does not explicitly exclude alternatives like authenticate. No explicit when-not-to-use, but the 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?

Annotations are minimal (readOnlyHint=false, destructiveHint=false), but the description adds rich behavioral context: invoke works on non-installed MCPs, returns connect/checkout links for auth/payment, retry semantics, install makes tool permanent, and writes require owner/admin. This is exactly the kind of disclosure beyond annotations that helps an agent.

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 long single paragraph, but each sentence adds non-redundant information about core flow, alternatives, auth/payment handling, or permission requirements. It is dense but not bloated; a bulleted structure would improve scannability, but the length is justified by the tool's multi-action 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?

Despite no output schema and 23 parameters, the description covers the tool's overall functionality, edge cases (credential/payment links), permission requirements, and the prompt library subsystem. It lacks systematic parameter coverage but is otherwise complete for an agent to understand the tool's role and major behaviors.

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 carry parameter meaning. It explains key params (action, query, mcp_id, tool_id, arguments, prompt_*), but many of the 23 params (limit, immediate, tier_slug, cancel_reason, etc.) are left unexplained. The description gives a strong high-level flow but doesn't sufficiently compensate for the lack of schema descriptions across all 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 clearly defines the tool as the official mcp.ai marketplace and the way to run MCPs, covering catalog search, profiles, and execution. It distinguishes itself from sibling tools by detailing its unique capabilities (invoke, install, subscribe) and even references report_bug as a sub-command, reducing ambiguity.

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?

Provides explicit usage guidance: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'. Also explains the core search→describe→invoke flow and mentions the prompt library alternative, giving clear when-to-use vs. alternative paths.

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 annotations already indicate readOnlyHint=false and destructiveHint=false, and idempotentHint=true. The description adds no behavioral detail beyond the purpose, such as what happens after reporting or any side effects. It does not contradict annotations, so a neutral score is appropriate.

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 convey purpose and a key usage instruction with no redundant wording. The structure is front-loaded with the main verb and resource.

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 3 simple parameters and no output schema, the description covers the core purpose and the non-obvious conversation parameter. It does not mention return values, but that is arguably unnecessary for a report tool. Overall, adequate for an agent to 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?

Schema description coverage is 0%, so the description carries the burden. It specifically explains the 'conversation' parameter's purpose ('for reproduction'), but leaves 'message' and 'context' implicit. The message's role is inferable from context, but context is unexplained, 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 with a specific verb ('Report') and resource ('a bug, missing feature, or send feedback'). It distinguishes from sibling tools by being the only one focused on user feedback/reporting, making its role 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 guidance to include the conversation array for reproduction, which is a specific usage condition. It does not explicitly exclude alternatives, but given the sibling list, no other tool is for reporting bugs, so context implies when 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 declare readOnlyHint, idempotentHint, and destructiveHint, but the description adds substantial behavioral context: payment model (prepaid credit), no credentials required, data is public and not private/confidential, and LGPD compliance responsibilities. This goes well beyond the structured 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 first sentence is direct and front-loaded with the core purpose. The following sentences add valuable context about hosting, payment, and data privacy, though the LGPD clause is somewhat verbose. Overall, it is concise enough and each sentence 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?

The description covers purpose, data source, access method, and legal considerations, but it does not describe the return format or what the output looks like. Since there is no output schema, this is a notable gap. The 'completo' parameter semantics are also missing, making the description incomplete for a simple query 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 two parameters (Nome and completo) with no descriptions, and schema coverage is 0%. The description implicitly explains Nome via 'verifica se um nome', but it gives no meaning for 'completo' (boolean). The description does not compensate for the low schema coverage, leaving parameter semantics incomplete.

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 financeiras do Reino Unido (HM Treasury)' with a specific verb (Verifica) and resource (sanctions list). It also specifies the purpose (compliance and AML due diligence), making it distinct 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 usage context: use for compliance/AML checks, hosted by the platform, no credentials, pay-per-query with prepaid credit. It also notes that the data is public access. However, it does not explicitly state when not to use the tool or mention alternative sanctions-list tools, so it stops short of a full 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=true and idempotentHint=true, so the safety profile is covered. The description adds no additional behavioral context beyond stating what it shows, which is acceptable given the strong 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 sentence, directly states the purpose, and contains no extraneous information. It is perfectly concise 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?

For a simple version-checking tool with no parameters, no output schema, and strong annotations, the description is complete. It conveys everything 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 tool has zero parameters, so the baseline is 4. The description correctly explains the function without needing 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 ('Show') and a clear resource ('current MCP platform and adapter versions'). It is distinct from sibling tools like authenticate, 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 implies usage context: use when you need to check current versions. It doesn't explicitly mention alternatives or exclusions, but the clear purpose makes it easy for an agent to decide when to call 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, idempotentHint=true, and destructiveHint=false. The description adds meaningful context beyond those annotations by detailing the exact contents of the returned state (installed MCPs, statuses, accounts, tool counts). No side effects are disclosed, but none are expected given the read-only and idempotent hints.

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 core action ('Returns the current toolkit state') and then lists the included details. Every word earns its place; there is 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?

Given the tool's simplicity (zero parameters, no output schema), the description provides a complete picture of what the tool does and what it returns. It lists all relevant output categories and leaves no ambiguity about the tool's behavior.

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, so the baseline is 4. The description does not need to explain parameters, and the schema confirms there are none. No additional parameter semantics are required.

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 as 'current toolkit state', enumerating exactly what is included (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from siblings like show_version (version info) and authenticate (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 states what the tool returns but does not explicitly say when to use it or contrast it with alternatives. Usage context is implied—use when you need toolkit state—but there is no explicit guidance on when not to use it or which sibling might be more appropriate for specific scenarios.

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