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PR #26 added a MiniMax chat backend but left three loose ends that silently dropped any YAML / CLI configuration of minimax_* keys: only the environment-variable path worked. - skillopt/config.py: add 6 model.minimax_* entries to _FLATTEN_MAP so the keys declared in configs/_base_/default.yaml actually survive flatten_config() (mirroring the existing model.qwen_chat_* block). - skillopt/engine/trainer.py: import configure_minimax_chat and call it alongside configure_qwen_chat, so cfg-supplied credentials, temperature, max_tokens, and enable_thinking reach the backend. Also apply cfg["minimax_model"] via set_target_deployment when the active target backend is minimax_chat. - scripts/train.py: add 6 --minimax_* CLI flags + the corresponding _CLI_TO_YAML entries, add 'minimax' / 'minimax_chat' to the --backend choices, auto-route to target_backend=minimax_chat, and pick the right default target_model for the new backend. Default behavior on existing backends (openai, claude, qwen, codex, claude_code_exec) is unchanged; all 8 shipped configs continue to load with gate_metric falling back to 'hard' for paper reproduction.