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

No annotations are provided, so the description carries the full burden. It says 'compute' which implies a non-mutating pure calculation, but it does not explicitly state whether there are side effects, permissions required, or what happens to inputs. The behavioral profile is under-specified.

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 front-loads the action and resource. It lists the components efficiently without extra content or wasted words.

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 6 parameters (1 required), nested objects, and an output schema, the description is insufficient. It fails to explain what each parameter means, how the inputs relate, or what behavioral expectations exist. The output schema helps with returns, but input semantics are almost entirely unaddressed.

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% and the description does not explicitly map terms to parameters. Some hints exist (novelty/surprise to actual/predicted_state, empowerment to reachable_states, learning progress to skill_success), but these are vague and require inference. The description does not meaningfully compensate for the lack of schema documentation.

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 computes intrinsic drives and lists specific components (novelty, prediction surprise curiosity, empowerment, learning progress). It uses a specific verb and resource, and the rich list distinguishes it from most sibling tools, though it doesn't explicitly name an alternative.

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?

There is no guidance on when to use this tool versus alternatives, nor any conditions or exclusions. The description only states what it computes, leaving the agent to infer when it is appropriate. No sibling comparisons or usage context are provided.

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