Sanções Austrália (DFAT)

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

Adds meaningful context beyond the annotations: explains that adding to config creates a permanent non-expiring connection, while pasting a token is session-only. Also clarifies that calling with no args yields a login link. This complements the idempotentHint and readOnlyHint annotations without 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 packs useful instructions into a few sentences, front-loading the core purpose. It is somewhat dense and run-on, but every part contributes necessary information, so it remains reasonably 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?

Covers the two main usage modes well, but does not describe the response format, potential errors, or what the agent should expect after calling. With no output schema, this missing return-value information leaves an important gap for the agent to handle the auth flow confidently.

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 only lists 'token' as a string with no description (schema coverage 0%). The description fully compensates by explaining that the token is a JWT pasted by the user for session login, and that omitting it retrieves a login link, thus giving complete semantic meaning.

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 specifies the tool's purpose: authenticating to MCP.AI for IDE agents via browser login and token exchange. It enumerates two distinct usage modes (permanent config header vs session token), making it distinguishable from potential sibling tools like '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?

Provides clear instructions for both permanent configuration and session-only login, including when to pass a token and when to call with no args to get a link. However, it does not explicitly compare to alternative tools or state when not to use authentication, 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=true and destructiveHint=false, so the description adds value by explaining conditional behaviors: it returns 'authenticated:true and empty pending[]' when all providers are connected, and provides 'connect_url for the toolkit and per-install URLs' when credentials are missing. This clarifies response structure beyond what annotations convey.

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, front-loaded with the primary function, and contains no filler. Every word contributes to explaining behavior and output.

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 status tool with no parameters and rich annotations, the description covers the key states (all connected vs. missing credentials) and the output in both cases. It does not describe partial connection states, but the mention of 'pending[]' hints at intermediate scenarios, and the description is largely adequate for an agent to understand 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 has zero parameters and the schema is empty, so the description does not need to explain parameter meanings. The baseline for 0 params is 4, and the description correctly focuses on behavior rather than 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 states the tool's function: 'Returns connection status and URLs.' It uses a specific verb ('returns') and resource ('connection status'), and distinguishes it from siblings like authenticate by focusing on status rather than performing 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?

The description implies when to use the tool—to check connection status or obtain URLs when credentials are missing—but it does not explicitly name alternatives or state when not to use it. The mention of connect_url when credentials are missing hints at using authenticate, but this is implicit rather than explicit guidance.

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 substantial context beyond the annotations: it explains that invoke works even when the MCP is not installed, returns connect/checkout links for auth/payment, that install makes an MCP permanent, and that writes require workspace owner/admin. This goes far beyond the minimal readOnlyHint/openWorldHint annotations and provides actionable behavioral disclosure.

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 and dense, but it covers 14 distinct actions and their interrelationships, so its length is justified. It front-loads the core purpose and flow, but would benefit from bullet points or clearer segmentation to improve scannability.

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 high complexity with 14 actions and no output schema, the description is remarkably complete. It covers search, describe, invoke, install lifecycle, billing/subscription, permissions, prompt library, and even error/retry behavior (connect/checkout links). No output schema is needed because the description sets expectations for what each action returns.

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 carries the burden of explaining parameters. It explains the central action/mcp_id/tool_id/arguments flow and the prompt-related actions, which gives meaning to many parameters. However, 23 parameters exist and several (limit, immediate, tier_slug, cancel_reason, etc.) are not explicitly explained, so it does not 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 clearly states the tool is the official mcp.ai marketplace and catalog, and outlines a core flow (search → describe → invoke) that distinguishes its function from generic tools. It specifies the resource (MCPs/tools) and the actions (search, describe, invoke, install, etc.), making its purpose unmistakable.

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 when-to-use guidance: prefer invoke for single/occasional use, use install only to make an MCP permanent, and list_tools for what is callable now. It also gives alternatives and conditions, such as 'if the MCP needs a credential/login, invoke returns a connect link' and that writes require owner/admin, helping the agent decide between actions.

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=false, destructiveHint=false, and idempotentHint=true. The description adds the conversational context requirement for reproduction, which is useful. However, it doesn't disclose what happens after submission (e.g., acknowledgment, where the report goes), so it doesn't go beyond annotation coverage significantly.

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 consists of two concise sentences. It conveys the purpose and the key usage instruction without any superfluous words, earning high marks for efficiency.

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 simple with no output schema, and the description covers the main purpose and a vital reproduction detail. However, the schema shows 'conversation' as a string while the description calls it an 'array', which could confuse agents about the expected type. Additionally, the 'context' parameter is not addressed, leaving a gap in completeness for a tool with three parameters.

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. The description explains the purpose of the conversation parameter ('Include the conversation array with recent messages for reproduction') but does not explain the required 'message' parameter (though its purpose is implicitly tied to the tool's function) and leaves 'context' completely unexplained. This is insufficient for full parameter understanding.

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 with a specific verb 'Report' and objects 'bug, missing feature, or send feedback'. It is immediately distinguishable from sibling tools like authenticate, marketplace, and show_version, 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 explicitly lists when to use the tool: to report a bug, missing feature, or feedback. It also provides a concrete guideline to include the conversation array with recent messages for reproduction. It doesn't mention alternatives, but no sibling tool is relevant to bug reporting, so 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 already declare read-only and idempotent behavior. The description adds meaningful context: the tool is hosted by the platform, requires no credentials, has a pay-per-query cost with prepaid credit, and accesses only public data. It also clarifies the client's LGPD data controller responsibility. These go 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 paragraph with four sentences, each providing a distinct piece of information: purpose, hosting/payment, public data nature, and LGPD. It's appropriately sized, though slightly dense. No redundant 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 tool with no output schema, the description gives a clear overview and important operational details. However, the missing explanation for the 'completo' parameter and any indication of the result format leave gaps. Overall adequate but not 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 two parameters with no descriptions, and the description only implicitly clarifies 'Nome' as the name to check. The purpose of 'completo' is not explained, leaving the agent unsure whether it means full match, complete name, or something else. With 0% schema coverage, the description should compensate but doesn't fully.

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 checks whether a name appears on Australia's international sanctions list (DFAT), with a specific verb and resource. It also mentions the context of compliance and AML. This distinguishes it from generic sibling tools, though no direct alternatives exist.

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 context for use (compliance and AML due diligence) and notes it's for public information, but does not explicitly state when not to use it or name alternatives. Since siblings are unrelated, this is acceptable.

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 read-only, idempotent, and non-destructive behavior. The description adds specific detail about what versions are shown (platform and adapter), which is useful 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?

A single, direct sentence that avoids any filler. It is front-loaded with the action and object.

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, read-only version tool, the description is complete. No output schema exists, but the nature of the tool makes the return value obvious.

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 no parameters, so the baseline score of 4 applies. No description needed to clarify 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 clearly states the specific action ('Show') and object ('current MCP platform and adapter versions'), which is distinct from sibling tools. It leaves no doubt about what the tool does.

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 usage context is clear: use it whenever you need version information. There are no explicit alternatives or exclusions, but given the simplicity of the tool, the implied usage 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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful context by breaking down exactly what 'toolkit state' includes, which aligns with the safety profile and provides value 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 sentence, front-loaded with the main purpose ('Returns the current toolkit state'), and each clause adds specific, non-redundant detail. No wasted 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?

For a zero-parameter, read-only info tool with strong annotations and no output schema, the description is fully adequate. It explicitly enumerates the returned components and requires no further clarification.

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 nothing to explain. The baseline for no parameters is 4, and the description does not need to compensate for missing schema details, as none exist.

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 specifies the resource ('current toolkit state'), enumerating the exact information included: installed MCPs, connection status, accounts, and catalog tool counts. This distinguishes 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 gives no guidance on when to use this tool versus alternatives. It only states what it does; there is no mention of use cases, prerequisites, or exclusions, leaving the agent to infer when this info would be relevant.

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