tcai_workspace_state

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

No annotations are present, so the description carries full burden. It lists included state components but discloses no behavioral traits such as read-only nature, side effects, or destructive potential. The agent gains little understanding of the tool's operational characteristics.

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 one short sentence, making it concise. However, it is a list without a verb, which could be improved for clarity. Still, it avoids unnecessary words and is front-loaded.

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?

The description lists relevant state components but does not explain their meanings, formats, or how to interpret the output. Given the complexity of the cognitive architecture domain and the absence of an output schema, more detail is needed for completeness.

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 no parameter documentation is needed. The description adds no parameter information, but with 100% schema coverage and no parameters, the baseline of 4 is appropriate.

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 states the tool provides 'Global Neuronal Workspace state' listing several sub-states (ignition, focus, qualia, etc.), which indicates what it does. However, it lacks a verb and does not differentiate from siblings like tcai_metrics or tcai_self_model that might also return state information.

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 usage guidance is provided. The description does not specify when to use this tool versus alternatives or mention any prerequisites or exclusions, which is insufficient given the large set of sibling tools.

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