tcai_curiosity

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

Without annotations, the description explains the internal computation (prediction error, random target, online predictor) and defaults to GNW broadcast. However, it does not specify the output format or side effects, leaving a minor gap.

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, front-loading the core function and defaults. Every phrase is informative with no redundancy.

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?

While the description explains the mechanism and defaults, it does not explicitly state the return value (e.g., curiosity score) or provide usage context among siblings. Given no output schema, this is a notable gap.

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 parameter 'embedding' is fully described in the schema. The description adds value by explaining its default (current GNW broadcast) and role in curiosity computation, enhancing understanding.

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 curiosity as prediction error between a frozen random target and an online predictor, referencing RNDCuriosity port and epistemic value. It distinguishes itself from sibling tools by specifying the unique mechanism.

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 like tcai_active_inference or tcai_metaconsciousness. The description lacks context for tool selection.

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