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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the loop stages (Perceive -> Model -> Decide -> Act -> Reflect -> Learn), which gives some sense of process, but it does not disclose side effects, whether the agent modifies environment or persistent state, how learning is applied, or what the tool returns. This is a significant gap for a complex orchestration tool.

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 a single, readable sentence that front-loads the verb and the resource. It contains no fluff, but it is also minimal enough that it leaves substantial semantic gaps for a tool of this complexity.

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?

Despite having an output schema, the tool is a high-complexity orchestration method with four optional parameters that are completely unexplained. The description does not cover how the loop interacts with the environment, what env_type values are valid, how max_steps bounds behavior, or what the actions array represents. This is insufficient for an agent to invoke the tool correctly.

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 description coverage is 0%, and the description adds nothing about any of the four parameters (env_id, actions, env_type, max_steps). An agent cannot tell from the description how these inputs influence the closed loop or which ones are required for meaningful execution.

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's function with a specific verb ('Run') and a well-defined resource ('end-to-end cognitive agent closed loop'), and it enumerates the pipeline stages. It is easily distinguishable from single-stage sibling tools like cognitive.infer or cognitive.learn_from_mistake, though it does not explicitly contrast itself with a specific sibling such as cognitive.run_multi_agent_simulation.

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?

The description offers no explicit guidance about when to use this tool versus alternatives, no prerequisites, and no exclusions. The only signal is the implied purpose of running the full loop, which is not enough to help an agent decide between this and related orchestration tools like cognitive.execute_task or cognitive.run_multi_agent_simulation.

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