Choose names that clearly convey purpose and intent rather than generic or ambiguous terms. Names should be specific enough to understand functionality without requiring additional context. **Avoid generic names:** - Don't use generic terms like `utils`, `helpers`, or `base` when more specific alternatives exist - Instead of `class Executor`, use `class ConcurrentExecutor` or `class SequentialExecutor` - Replace generic file names like `utils.py` with specific names like `validation.py` or `formatting.py` **Use semantically meaningful names:** - Method names should clearly indicate their action: `serialize_state()` and `deserialize_state()` instead of ambiguous alternatives - Variable names should reflect their content: `next_nodes_to_execute` (plural) instead of `next_node_to_execute` when referring to multiple items - Parameter names should be self-documenting: `timeout` instead of `timeout_seconds` when accepting a `timedelta` object **Choose appropriate specificity:** - Be specific enough to avoid confusion: `get_agent_card()` instead of the vague `_discover_agent_card()` - Balance verbosity with clarity: `name_override` instead of the verbose `agent_facing_tool_name` - Use domain-specific terminology: `output_type` instead of `structured_output_type` when the context makes "structured" redundant **Example:** ```python # Avoid generic names class Executor: # Too generic pass # Use descriptive names class ConcurrentToolExecutor: # Clear purpose and scope def serialize_state(self) -> dict: # Clear action pass def get_next_nodes(self) -> list[str]: # Clear return type pass ``` This approach improves code readability and reduces the need for additional documentation to understand component purposes.