getPendingUserMessages

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool returns messages 'the user has typed from inside the 3D environment' and should be called 'at the start of every turn,' which adds useful context about its role in a turn-based system. However, it doesn't describe potential side effects, error conditions, or what happens if no messages are pending, leaving some behavioral aspects unclear.

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 that are front-loaded with the core purpose and followed by specific usage instructions. Every word contributes to understanding the tool's function and when to use it, with no wasted text or unnecessary details.

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 has no annotations, no output schema, and 0 parameters, the description does a decent job by explaining what it returns and when to call it. However, it lacks details on the return format (e.g., structure of messages) and error handling, which could be important for an AI agent to use it effectively in a 3D environment context.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on usage context. A baseline of 4 is applied since it avoids redundancy while adding value through usage guidance.

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: 'Return any in-world chat messages the user has typed from inside the 3D environment.' This specifies the verb ('return') and resource ('in-world chat messages'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'sendChatMessage' or 'clearPendingMessages', which prevents a perfect score.

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 on when to use this tool: 'Call this at the start of every turn to check for user input from the canvas.' This gives clear context for usage frequency and timing, which is helpful for an AI agent in determining when to invoke it versus alternatives.

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