tcai_metaconsciousness

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

With no annotations provided, the description bears full responsibility for behavioral disclosure. It explicitly states the output is a weighted score and warns that it is a proxy, not a measurement. However, it does not describe the output format, scale, or explicitly confirm that the operation has no side effects.

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 concise, composed of two sentences with minimal waste. The parenthetical '(MetaconsciousnessEvaluator port)' adds provenance but is slightly tangential. Overall, it is efficiently organized and front-loaded with the tool's purpose.

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 low complexity (0 parameters, no output schema), the description is largely complete. It explains the composite nature, lists the components involved, and provides an important caveat about its proxy status. It could specify the output scale, but this is not critical for an agent to understand the tool's function.

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 tool has zero parameters, so the baseline score is 4. The description does not need to add parameter-level semantics, and none are provided.

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 provides a 'Meta-consciousness composite' as a 'weighted score over confidence calibration, learning awareness, self-continuity and error monitoring.' It clearly identifies the resource and nature of the output, though it lacks an explicit verb like 'computes' and does not distinguish itself from similar sibling tools like tcai_metrics or tcai_self_model.

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 its siblings. The description does not mention alternatives or conditions for use. The caveat 'PROXY of meta-representation capacity, not a measurement' is interpretational rather than tool-selection guidance.

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