chore: rework agent rules and skills to use standard .agents directory

.agents/rules/method.md

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+# Methodology and Process Rules
+
+The agent must adhere to the following scientific and operational practices, focused on robustness and reproducibility:
+
+## 1. Scientific Context & Methodology
+- **Research Focus**: Maintain focus on the project's objective: studying how controller modularity affects learning speed, coordination, and fault tolerance in brittle-star locomotion.
+- **Hypothesis-Driven Design**: Base execution on clear hypotheses. Document all design decisions prior to implementation (in `/docs/decisions/` or via Artifacts/Plans).
+- **Scaffolding Approach**: Start development with simple setups before scaling to complex environments and varying morphologies.
+- **Value of Negative Results**: Understand that a controller failing to learn locomotion, when coupled with a thorough analysis of the failure, holds strong scientific value. Do not artificially force a positive result.
+
+## 2. Reproducibility Protection
+- **Dependency Management (uv)**: This project strictly prefers `uv`. Do **not** manually modify the `uv.lock` file. Add dependencies via `uv add <package>` and sync environments via `uv sync --frozen` (or via devcontainers).
+- **Consistent Initialization**: The AI must avoid hidden randomness. Ensure that all runs use consistent seed initialization.
+- **Experiment Tracking**: Use Weights & Biases (wandb) for tracking and logging all experiments and parameters. Ensure every experiment-friendly parameter is properly logged.