step_env

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

No annotations are provided, so the description must convey behavioral traits. It discloses return values but fails to mention side effects (e.g., environment state mutation), safety concerns, or requirements (e.g., prior reset). For a step function, critical behavioral context is missing.

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?

Two sentences with no filler. The first sentence states the core action, the second lists the return values. Information is front-loaded and every sentence adds value.

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 the return values, but lacks details about the environment's state, action effects, and termination conditions beyond 'agent reached the goal'. Given no output schema, more context (e.g., observation structure) would improve completeness.

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 coverage is 0%, so the description must compensate. It adds meaning by specifying '2D acceleration action', suggesting the action array has two numeric components. However, it does not specify the exact dimensions, allowed ranges, or semantics of the acceleration, leaving some ambiguity.

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 that the tool applies a 2D acceleration action and advances one timestep, and lists return values. This distinguishes it from siblings (reset_env, encode_observation, etc.) by specifying the verb 'apply' and the resource 'environment', making the purpose unambiguous.

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 stepping the environment, but does not provide explicit guidance on when to use this tool versus alternatives like predict_rollout or when not to use it. No exclusions or prerequisites are mentioned.

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