tcai_cycle

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

Without annotations, the description provides good behavioral detail: the pipeline stages, early stopping via stopWhenSatisfied, and description of threshold parameters. It does not explicitly state whether the operation modifies internal state, but the pipeline implies changes to memory and self-model.

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?

Two sentences, highly efficient. First sentence lists the pipeline steps, second explains the early stopping. No extraneous information. Front-loaded with the core action.

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 pipeline and stopping criteria are explained, the description lacks information about return values, side effects (e.g., memory writes), and prerequisites. Given 15 parameters and no output schema, more guidance on results would improve 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?

Schema coverage is 80%, so baseline is 3. The description adds context by explaining the stopWhenSatisfied mechanism and how threshold parameters (epsFreeEnergy, relFreeEnergy, etc.) relate to convergence. This adds value beyond the parameter descriptions in the schema.

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?

Description clearly states the tool runs ACM cycles and lists the full pipeline (SNN signals through second-order loop). The verb 'Run' with the specific resource 'ACM cycles' differentiates it from sibling tools like tcai_active_inference or tcai_curiosity.

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?

Implied usage: run cycles when you want to simulate the consciousness pipeline. However, no explicit guidance on when to use this tool vs alternatives (e.g., tcai_active_inference, tcai_self_model). No exclusions or prerequisites mentioned.

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