wm_predict

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

With no annotations present, the description must fully disclose behavioral traits. It only states the purpose, failing to mention side effects, safety (e.g., reads vs writes), return characteristics, or dependency on prior state. This is insufficient for an agent to understand implications of invocation.

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 extremely short (4 words, no sentence structure). While concise, it lacks a proper sentence (starting with a verb in imperative form would be better). It is not verbose, but the terseness reduces clarity and structure.

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 has no output schema and the description does not explain what the prediction result contains (e.g., state representation, probability distribution). Given complexity (world model prediction) and many sibling tools, the description is too sparse to enable correct invocation and interpretation.

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 100% description coverage for all parameters (action and steps), including nested fields. The description adds no additional meaning beyond the schema, so it meets the baseline. It does not clarify format or constraints further, which is acceptable given schema completeness.

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 action of predicting the next SNN state in latent space, which is a specific verb and resource. However, it does not mention that the prediction is conditioned on an action input (visible in schema), nor does it explicitly distinguish from sibling tools like wm_plan or wm_encode, but the distinct resource term 'Next SNN State' differentiates somewhat.

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?

No guidance is provided on when to use this tool versus alternatives (e.g., wm_plan, wm_encode). The description does not indicate prerequisites, typical inputs, or when not to use it, leaving the agent without decision support for tool selection.

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