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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Perform,' implying a computational action, but does not disclose whether it mutates state, requires specific inputs, has side effects, or how the result is returned. The lack of any behavioral detail is a significant gap for a potentially expensive search operation.

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 concise sentence with no fluff, front-loading the algorithm name and objective. However, conciseness is achieved at the expense of essential details, so it is not an ideal balance—still, the structure itself is clean and direct.

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 description is too minimal for a complex algorithm like MCTS. It does not explain the expected output format, how iterations affect the search, or how to interpret the 'optimal trajectory.' Given the tool's complexity, the description lacks the necessary context for an agent to use it correctly and confidently.

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 does not mention any of the three parameters (initial_state, valid_actions, max_iterations). The description's reference to 'action sequences' hints at valid_actions but does not explain the format, defaults, or interaction between parameters. The tool description provides no additional meaning beyond the parameter names, which are insufficient for correct invocation.

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 algorithm (Monte Carlo Tree Search with UCT) and its goal (find optimal trajectory over action sequences). This distinguishes it from simpler tree_search or other cognitive tools, though it could be more explicit about what constitutes an 'optimal trajectory' in the context of cognitive planning.

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 like cognitive.tree_search or cognitive.hierarchical_plan. The description does not mention any preconditions, constraints, or scenarios where this search is preferred, leaving the agent to infer usage from the name alone.

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