tcai_active_inference

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

No annotations provided, so description must disclose behavior. It enumerates returned quantities but does not state side effects, permissions, or cost. Being a data retrieval tool with 0 parameters, the risk is low, but the description could be more explicit about read-only nature.

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 sentence that packs significant detail without redundancy. However, it lacks paragraph structure or explicit front-loading of key actions. Appropriate for the technical content.

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 tool with no parameters and no output schema, the description covers the main return values and cites relevant literature. It could mention typical use cases within the active inference loop or whether it is safe/side-effect-free, but overall it is sufficiently complete.

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?

No parameters exist; baseline 4. The description adds high value by explaining what the tool returns, compensating for missing output schema. It lists specific quantities that the schema (empty) does not convey.

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 returns active-inference core telemetry including free energy, expected free energy, task quality, model entropy, and Dirichlet action. It distinguishes itself from siblings as the principled quantity for halting criterion.

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 on when to use this tool vs alternatives like tcai_metrics or tcai_curiosity. The description does not mention contexts, prerequisites, or exclusions.

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