tcai_metaconsciousness

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

With no annotations provided, the description carries full burden for behavioral disclosure. It describes the output (weighted score) and its proxy nature, but does not mention side effects, state dependencies, cost, or limitations. Agents are left uninformed about potential impacts or required state.

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 brief (two sentences) with no superfluous words. However, the use of jargon like 'MetaconsciousnessEvaluator port' and 'meta-representation capacity' may reduce clarity for less specialized agents.

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's conceptual complexity, the description is somewhat incomplete. It does not explain the output format (e.g., numeric range), how to interpret the score, or what state (if any) it queries. For a simple parameterless tool, it covers the basics but lacks essential interpretability details.

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 zero parameters, so there is nothing to document. The description does not add parameter meaning because none exist. Baseline 4 is appropriate given no parameters and full schema coverage.

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 it provides a 'weighted score over confidence calibration, learning awareness, self-continuity and error monitoring', and distinguishes it as a 'PROXY of meta-representation capacity, not a measurement'. This gives a specific verb-resource relationship and sets it apart from sibling tools like tcai_curiosity or tcai_emotion_appraise.

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 versus alternatives. It does not specify prerequisites, context, or conditions under which it should be invoked. The description merely states what it is, not when to use it.

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