door_73ca37dbbd10

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

No annotations are provided, so the description must disclose behavior. It mentions what the tool covers (platform overview and visitor rules) but does not state whether it is a read-only operation, what output format to expect, or whether it has any side effects. This is a significant gap for an unannotated tool.

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 that is front-loaded with the core purpose. There is no wasted content, and it is easily scannable.

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 informational tool with no parameters and no output schema, the description covers the basic question of what it does. However, it does not specify the response format or depth, and it could benefit from a hint about how to interpret the returned information. Given the minimal tool, a 3 is appropriate.

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 is empty (0 parameters), so baseline 4 applies. The description adds nothing about parameters, but none exist, so this is acceptable.

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 purpose: it explains the platform and what visiting agents may do. This is a specific verb/resource combination and distinguishes it from the sibling 'ask' tool, which is likely for asking questions.

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 phrase 'visiting agents' implies it is for when an agent first arrives, but there is no explicit statement about when to use this vs. the 'ask' tool, nor any exclusion criteria. The usage context is implied rather than stated.

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?

No annotations are provided, so the description carries full behavioral transparency burden. It does disclose that answers are 'grounded in the platform's own knowledge with cited sources', which is a useful behavioral trait. However, it does not disclose other aspects like read-only nature, latency, or failure modes, leaving some ambiguity.

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, immediately states the primary function, and provides key behavioral notes (grounding and citations) without redundancy. It wastes no words and front-loads the most critical 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 query tool with a single parameter and no output schema, the description is nearly complete. It explains what the tool does, the scope of questions, and the nature of answers. One might wish for an explicit statement about return format, but the simplicity of the tool makes this minor gap acceptable.

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 fully describes the single parameter 'question' with a clear description and character limit. The tool description adds contextual meaning by specifying the type of questions (capabilities, pricing, policies), which helps the agent formulate appropriate queries beyond the schema's literal definition.

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 ('ask') and resource ('this platform') and enumerates the subject areas (capabilities, pricing, policies). It does not explicitly differentiate it from the sibling tool 'about', but the description is clear on its own.

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 the sibling 'about' tool, nor does it mention any exclusions or alternative tools. There is no explicit 'when' or 'when not to use' context, leaving usage decisions to the agent's inference.

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