FinCEN (EUA)

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

Discloses that calling with no args returns a login link, while providing a token gives session-only authentication. Adds context beyond the idempotentHint annotation by describing the side-effect-free nature of returning a link. Could mention failure cases but overall 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 compact yet comprehensive, using 'Best' and 'Or' to structure alternatives. Every sentence adds value, and the critical info (login method) is 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 an auth tool with no output schema, the description explains the return behavior (get a link) and the two use cases. It lacks explicit error handling details but is sufficiently complete for an agent to invoke 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 has 0% description coverage for the 'token' parameter, but the description fully explains it as a JWT access token and clarifies it is optional. Provides concrete examples: '{ token: "<jwt>" }' and 'no args to get the link', making the parameter semantics unmistakable.

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 authenticates the user to the MCP server by logging in via browser and copying a token. It distinguishes from siblings by describing the auth flow for IDE agents, though it doesn't explicitly differentiate from '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 explicit guidance on two usage modes: permanent config header vs session-only token paste, and explains when to call with/without the 'token' argument. Clearly tells the agent when to use this tool and how to handle both scenarios.

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 readOnly, non-destructive, and idempotent. The description adds valuable context about the response states (authenticated:true with empty pending[], or connect_url when credentials are missing), which is beyond what annotations provide.

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 purpose and then providing conditional details. Every word earns its place 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 status-check tool with no parameters and no output schema, the description is complete. It explains both possible states (connected vs. missing credentials) and what the return values will be, so the agent knows exactly what to expect.

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?

There are zero parameters, so the baseline is 4. The description doesn't need to add parameter details, and the schema coverage is vacuously 100%.

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 response conditions. It distinguishes itself from siblings like authenticate (which likely initiates auth) by focusing on status checking.

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 conditional context by explaining behavior when providers are connected versus when credentials are missing. It doesn't explicitly name alternatives, but the sibling list and the nature of the tool imply it's for checking status rather than performing authentication.

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 (readOnly, idempotent, non-destructive), the description adds valuable context: hosted by the platform, no credentials, prepaid credit cost, public-source data, and LGPD responsibilities. This gives the agent a well-rounded understanding of the tool's operational and legal behavior.

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 front-loaded with the core purpose, and every sentence adds relevant information. The three sentences are concise and cover purpose, access method, cost, data source, and legal context without unnecessary verbosity.

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 lookup tool, the description covers most critical aspects: what it does, when to use it, cost, authentication, data nature, and legal responsibility. However, the missing semantics of the 'completo' parameter is a notable gap, as is the lack of any indication of the return format (though 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?

Schema description coverage is 0%, so the description must compensate by explaining parameters. It implicitly covers 'Nome' through the main purpose, but the 'completo' boolean parameter is completely undocumented, leaving the agent without guidance on whether it means full-name matching, exhaustive search, or something else.

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+resource structure: 'Verifica se um nome consta nas listas do FinCEN'. This clearly distinguishes it from the unrelated sibling tools and leaves no ambiguity about the tool's function.

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 states the intended use context ('para diligência de compliance e AML'), which is clear guidance for when to use this tool. It does not mention exclusions or alternatives, but no similar sibling tools exist, so the lack of explicit comparison is not a significant gap.

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 goes well beyond annotations by detailing the invoke-once behavior, connectivity links for credentials, checkout/top-up links, installed_in_toolkit vs installed_in_workspace flags, and owner/admin permission requirements. It also explains the prompt library's sharing behavior.

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 with no section breaks or bullet points, making it harder to scan. Every sentence adds value, but the structure is poor and the length is substantial, though justified by the tool's 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?

The description covers most of the 14 actions, explains core flows, authentication, payment, permissions, and the prompt library. However, the 'resume' action is never mentioned, and some parameters like 'conversation' and 'immediate' are not addressed, leaving minor gaps.

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 coverage, the description adds high-level meaning to many parameters through the action flow (action, mcp_id, tool_id, arguments, prompt_*). However, some parameters like conversation, resume, immediate, and limit remain unexplained, leaving a few 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 identifies the tool as the official mcp.ai marketplace — a catalog and execution platform for MCPs/tools. It specifies the core flow (search → describe → invoke) and distinguishes it from sibling tools like report_bug by encompassing them as sub-actions.

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 provides explicit guidance on when to use invoke vs install ('prefer invoke for a single/occasional use'), how to handle auth/payment links, and when to use request_mcp ('when nothing fits'). It also clarifies that writes require owner/admin.

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 useful behavioral guidance by instructing users to 'Include the conversation array with recent messages for reproduction,' which supplements the schema. However, it doesn't disclose whether the report is sent, stored, or if there are any side effects beyond what annotations (idempotentHint, destructiveHint) already 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 concise sentences with the core purpose stated first and the key usage detail about the conversation array second. No filler or 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?

This is a simple tool with three string parameters and no output schema, so deep behavioral documentation is unnecessary. The description covers the purpose and one parameter but omits the required message and any expected result, leaving some gaps.

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 for parameter meaning. It explains the 'conversation' parameter but leaves the required 'message' parameter and the optional 'context' parameter undocumented, limiting its value for 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 explicitly states the tool's purpose: 'Report a bug, missing feature, or send feedback.' This is a specific verb + resource combination and clearly differentiates the tool from unrelated sibling tools like authenticate 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 when to use the tool—whenever a user needs to report a bug, missing feature, or provide feedback. It doesn't explicitly list alternatives or exclusions, but given the sibling tools serve unrelated purposes, the usage context is clear enough.

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 false, covering the safety profile. The description adds value by clarifying that the tool returns *current* versions, indicating live data, and specifying that it covers both platform and adapter versions—context 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, well-structured sentence with no wasted words. It front-loads the action ('Show') and immediately names the resources (platform and adapter versions).

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 no-parameter, read-only tool with strong annotations, the description fully covers what the tool returns. It names both version categories and implies a lightweight operation, which is sufficient 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?

The tool takes 0 parameters, so the schema coverage is 100% and the baseline is 4. The description doesn't need to explain parameter semantics since there are none, and it correctly avoids inventing 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 with a specific verb ('Show') and resource ('current MCP platform and adapter versions'). This distinguishes it from sibling tools like `authenticate` or `report_bug`, which have 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?

The description implies usage when version information is needed, but it does not explicitly state when to use this tool over alternatives or provide exclusions. Given the sibling tools, it is obvious this is the version-checking tool, but the guidance remains implicit.

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, covering the safety profile. The description adds valuable context on what the returned state includes, which goes beyond the annotations and clarifies the tool's output scope.

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 lists the key components of the returned state without wordiness. Every element earns its place, making it easy to scan and understand.

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 low complexity, rich annotations, and no parameters, the description fully captures what the tool returns. It is complete for an agent to select and invoke the tool correctly without needing additional details.

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 empty input schema makes this obvious. Per the rubric, a baseline of 4 is appropriate; the description need not explain parameters and instead focuses on the output, which is sufficient.

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 resource ('current toolkit state') and enumerates the content (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from siblings like show_version or authenticate, making the 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?

The description implies usage for checking overall toolkit state but does not explicitly state when to use it versus alternatives like show_version. No exclusions or alternative tool names are mentioned, so guidance is only implied.

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