diff --git a/toolcall-rl/retool_qwen35_27b_4nodes_rl.sh b/toolcall-rl/retool_qwen35_27b_4nodes_rl.sh
new file mode 100644
index 0000000..bd3905f
--- /dev/null
+++ b/toolcall-rl/retool_qwen35_27b_4nodes_rl.sh
@@ -0,0 +1,232 @@
+#!/bin/bash
+
+pkill -9 sglang || true
+sleep 3
+ray stop --force || true
+pkill -9 ray || true
+pkill -9 python || true
+sleep 3
+pkill -9 ray || true
+pkill -9 python || true
+
+set -ex
+
+export PYTHONUNBUFFERED=1
+export PYTHONFAULTHANDLER=1
+export FLASHINFER_WORKSPACE_BASE="${FLASHINFER_WORKSPACE_BASE:-/tmp}"
+
+NUM_NODES=${NUM_NODES:-4}
+NUM_GPUS_PER_NODE=${NUM_GPUS_PER_NODE:-8}
+ACTOR_GPUS_PER_NODE=${ACTOR_GPUS_PER_NODE:-4}
+ROLLOUT_GPUS_PER_NODE=${ROLLOUT_GPUS_PER_NODE:-4}
+ROLLOUT_GPUS_TOTAL=${ROLLOUT_GPUS_TOTAL:-$((NUM_NODES * ROLLOUT_GPUS_PER_NODE))}
+SGLANG_GPUS_PER_ENGINE=${SGLANG_GPUS_PER_ENGINE:-8}
+
+if (( ACTOR_GPUS_PER_NODE + ROLLOUT_GPUS_PER_NODE > NUM_GPUS_PER_NODE )); then
+    echo "ACTOR_GPUS_PER_NODE + ROLLOUT_GPUS_PER_NODE must be <= NUM_GPUS_PER_NODE"
+    echo "ACTOR_GPUS_PER_NODE=${ACTOR_GPUS_PER_NODE}, ROLLOUT_GPUS_PER_NODE=${ROLLOUT_GPUS_PER_NODE}, NUM_GPUS_PER_NODE=${NUM_GPUS_PER_NODE}"
+    exit 1
+fi
+
+export RAY_health_check_failure_threshold=20
+export RAY_health_check_period_ms=5000
+export RAY_health_check_timeout_ms=30000
+export RAY_num_heartbeats_timeout=60
+
+NVLINK_COUNT=$(nvidia-smi topo -m 2>/dev/null | grep -o 'NV[0-9][0-9]*' | wc -l)
+if [ "${NVLINK_COUNT}" -gt 0 ]; then
+    HAS_NVLINK=1
+else
+    HAS_NVLINK=0
+fi
+echo "HAS_NVLINK: $HAS_NVLINK (detected $NVLINK_COUNT NVLink references)"
+
+SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" &>/dev/null && pwd)"
+ROOT_DIR="$(cd -- "${SCRIPT_DIR}/.." &>/dev/null && pwd)"
+SLIME_DIR="${ROOT_DIR}/slime"
+MEGATRON_LM_PATH=${MEGATRON_LM_PATH:-"${ROOT_DIR}/Megatron-LM"}
+if [[ ! -d "${MEGATRON_LM_PATH}" ]]; then
+    echo "MEGATRON_LM_PATH does not exist: ${MEGATRON_LM_PATH}"
+    exit 1
+fi
+
+# Do not mix the bridge checkout's bundled Megatron with this script.
+# For text-only retool we intentionally use the repo's Megatron-LM tree.
+source "${SLIME_DIR}/scripts/models/qwen3.5-27B.sh"
+
+HF_CKPT=${HF_CKPT:-/data_storage/wyj/systems/huggingface/hub/Qwen35-27B}
+REF_LOAD=${REF_LOAD:-${HF_CKPT}}
+SAVE_CKPT=${SAVE_CKPT:-/data_storage/wyj/OpenClaw-RL/ckpt/qwen35-27b-retool-rl/}
+RESUME_LOAD=${RESUME_LOAD:-${SAVE_CKPT}}
+PROMPT_DATA=${PROMPT_DATA:-/data_storage/wyj/OpenClaw-RL1/data/dapo-math-17k/dapo-math-17k.jsonl}
+EVAL_DATA=${EVAL_DATA:-/data_storage/wyj/OpenClaw-RL1/data/aime-2024/aime-2024.jsonl}
+ROLLOUT_MAX_RESPONSE_LEN=${ROLLOUT_MAX_RESPONSE_LEN:-8192}
+ROLLOUT_MAX_CONTEXT_LEN=${ROLLOUT_MAX_CONTEXT_LEN:-16384}
+EVAL_MAX_RESPONSE_LEN=${EVAL_MAX_RESPONSE_LEN:-16384}
+EVAL_MAX_CONTEXT_LEN=${EVAL_MAX_CONTEXT_LEN:-16384}
+
+export SGLANG_LANGUAGE_ONLY="${SGLANG_LANGUAGE_ONLY:-1}"
+export SLIME_QWEN35_TEXT_ONLY_BRIDGE="${SLIME_QWEN35_TEXT_ONLY_BRIDGE:-1}"
+
+CKPT_ARGS=(
+   --megatron-to-hf-mode bridge
+   --hf-checkpoint "${HF_CKPT}"
+   --ref-load "${REF_LOAD}"
+   --save "${SAVE_CKPT}"
+   --save-interval 20
+   --rotary-base 10000000
+)
+
+ROLLOUT_ARGS=(
+   --prompt-data "${PROMPT_DATA}"
+   --input-key prompt
+   --label-key label
+   --apply-chat-template
+   --rollout-shuffle
+   --reward-key score
+   --num-rollout 3000
+   --rollout-batch-size 32
+   --n-samples-per-prompt 8
+   --rollout-max-response-len "${ROLLOUT_MAX_RESPONSE_LEN}"
+   --rollout-max-context-len "${ROLLOUT_MAX_CONTEXT_LEN}"
+   --rollout-temperature 1
+   --num-steps-per-rollout 2
+   --balance-data
+)
+
+EVAL_ARGS=(
+   --eval-interval 20
+   --eval-prompt-data aime "${EVAL_DATA}"
+   --n-samples-per-eval-prompt 16
+   --eval-max-response-len "${EVAL_MAX_RESPONSE_LEN}"
+   --eval-max-context-len "${EVAL_MAX_CONTEXT_LEN}"
+   --eval-top-p 1
+   --eval-reward-key acc
+)
+
+PERF_ARGS=(
+   --tensor-model-parallel-size 4
+   --pipeline-model-parallel-size 1
+   --context-parallel-size 1
+   --expert-model-parallel-size 1
+   --expert-tensor-parallel-size 1
+   --recompute-granularity full
+   --recompute-method uniform
+   --recompute-num-layers 1
+   --use-dynamic-batch-size
+   --max-tokens-per-gpu 2048
+   --log-probs-chunk-size 512
+)
+
+GRPO_ARGS=(
+   --advantage-estimator grpo
+   --use-kl-loss
+   --kl-loss-coef 0.01
+   --kl-loss-type k3
+   --entropy-coef 0.00
+   --eps-clip 0.2
+   --eps-clip-high 0.28
+)
+
+OPTIMIZER_ARGS=(
+   --optimizer adam
+   --lr 1e-6
+   --lr-decay-style constant
+   --weight-decay 0.1
+   --adam-beta1 0.9
+   --adam-beta2 0.98
+   --optimizer-cpu-offload
+   --overlap-cpu-optimizer-d2h-h2d
+   --use-precision-aware-optimizer
+)
+
+if [[ -n "${WANDB_KEY:-}" ]]; then
+   WANDB_ARGS=(
+      --use-wandb
+      --wandb-project "${WANDB_PROJECT:-slime_retool}"
+      --wandb-group "${WANDB_GROUP:-qwen35-27B-rl_retool-4nodes}"
+      --wandb-key "${WANDB_KEY}"
+   )
+else
+   WANDB_ARGS=()
+fi
+
+SGLANG_ARGS=(
+   --rollout-num-gpus-per-engine "${SGLANG_GPUS_PER_ENGINE}"
+   --sglang-mem-fraction-static 0.8
+)
+
+if [[ "${SGLANG_LANGUAGE_ONLY}" == "1" ]]; then
+  SGLANG_ARGS+=(--sglang-language-only)
+fi
+
+MISC_ARGS=(
+   --attention-dropout 0.0
+   --hidden-dropout 0.0
+   --accumulate-allreduce-grads-in-fp32
+   --attention-softmax-in-fp32
+   --attention-backend flash
+)
+
+CUSTOM_ARGS=(
+   --custom-generate-function-path generate_with_retool.generate
+   --custom-rm-path generate_with_retool.reward_func
+)
+
+export PYTORCH_CUDA_ALLOC_CONF=${PYTORCH_CUDA_ALLOC_CONF:-"max_split_size_mb:2048,expandable_segments:True"}
+
+MLP_ROLE_INDEX=${MLP_ROLE_INDEX:-0}
+MASTER_ADDR="${MLP_WORKER_0_HOST:-${MASTER_ADDR:-$(hostname -I | awk '{print $1}')}}"
+_WORKER_IP_VAR="MLP_WORKER_${MLP_ROLE_INDEX}_HOST"
+NODE_IP="${!_WORKER_IP_VAR:-${WORKER_IP:-$(hostname -I | awk '{print $1}')}}"
+
+export MASTER_ADDR
+export no_proxy="127.0.0.1,${MASTER_ADDR}"
+echo "MLP_ROLE_INDEX=${MLP_ROLE_INDEX}, MASTER_ADDR=${MASTER_ADDR}, NODE_IP=${NODE_IP}"
+
+if [[ ${MLP_ROLE_INDEX} -eq 0 ]]; then
+  ray start --head --node-ip-address "${NODE_IP}" --num-gpus "${NUM_GPUS_PER_NODE}" --disable-usage-stats --dashboard-host=0.0.0.0 --dashboard-port=8265
+else
+  sleep 30
+  ray start --address="${MASTER_ADDR}:6379" --num-gpus "${NUM_GPUS_PER_NODE}" --node-ip-address "${NODE_IP}"
+fi
+
+RUNTIME_ENV_JSON="{
+  \"env_vars\": {
+    \"PYTHONPATH\": \"${MEGATRON_LM_PATH}:${SCRIPT_DIR}:${SLIME_DIR}\",
+    \"CUDA_DEVICE_MAX_CONNECTIONS\": \"1\",
+    \"NCCL_NVLS_ENABLE\": \"${HAS_NVLINK}\",
+    \"FLASHINFER_WORKSPACE_BASE\": \"${FLASHINFER_WORKSPACE_BASE}\",
+    \"PYTORCH_CUDA_ALLOC_CONF\": \"${PYTORCH_CUDA_ALLOC_CONF}\",
+    \"SLIME_QWEN35_TEXT_ONLY_BRIDGE\": \"${SLIME_QWEN35_TEXT_ONLY_BRIDGE}\",
+    \"MEGATRON_LM_PATH\": \"${MEGATRON_LM_PATH}\",
+    \"HF_CKPT\": \"${HF_CKPT}\",
+    \"MASTER_ADDR\": \"${MASTER_ADDR}\"
+  }
+}"
+
+if [[ ${MLP_ROLE_INDEX} -eq 0 ]]; then
+  ray job submit --address="http://${MASTER_ADDR}:8265" \
+     --runtime-env-json="${RUNTIME_ENV_JSON}" \
+     -- python3 "${SLIME_DIR}/train_async.py" \
+     --actor-num-nodes "${NUM_NODES}" \
+     --actor-num-gpus-per-node "${ACTOR_GPUS_PER_NODE}" \
+     --rollout-num-gpus "${ROLLOUT_GPUS_TOTAL}" \
+     ${MODEL_ARGS[@]} \
+     ${CKPT_ARGS[@]} \
+     ${ROLLOUT_ARGS[@]} \
+     ${OPTIMIZER_ARGS[@]} \
+     ${GRPO_ARGS[@]} \
+     ${WANDB_ARGS[@]} \
+     ${PERF_ARGS[@]} \
+     ${EVAL_ARGS[@]} \
+     ${SGLANG_ARGS[@]} \
+     ${MISC_ARGS[@]} \
+     ${CUSTOM_ARGS[@]}
+else
+  echo "Worker node ${MLP_ROLE_INDEX} joined the cluster. Waiting for job to finish..."
+  while ray status > /dev/null 2>&1; do
+    sleep 60
+  done
+  echo "Ray cluster stopped. Worker node ${MLP_ROLE_INDEX} exiting."
+fi
diff --git a/toolcall-rl/retool_qwen35_4b_rl.sh b/toolcall-rl/retool_qwen35_4b_rl.sh
new file mode 100644
index 0000000..9775976
--- /dev/null
+++ b/toolcall-rl/retool_qwen35_4b_rl.sh
@@ -0,0 +1,202 @@
+#!/bin/bash
+
+pkill -9 sglang || true
+sleep 3
+ray stop --force || true
+pkill -9 ray || true
+pkill -9 python || true
+sleep 3
+pkill -9 ray || true
+pkill -9 python || true
+
+set -ex
+
+export PYTHONUNBUFFERED=1
+export PYTHONFAULTHANDLER=1
+export FLASHINFER_WORKSPACE_BASE="${FLASHINFER_WORKSPACE_BASE:-/tmp}"
+
+NUM_GPUS=${NUM_GPUS:-8}
+ACTOR_GPUS=${ACTOR_GPUS:-4}
+ROLLOUT_GPUS=${ROLLOUT_GPUS:-4}
+
+if (( ACTOR_GPUS + ROLLOUT_GPUS > NUM_GPUS )); then
+    echo "ACTOR_GPUS + ROLLOUT_GPUS must be <= NUM_GPUS"
+    echo "ACTOR_GPUS=${ACTOR_GPUS}, ROLLOUT_GPUS=${ROLLOUT_GPUS}, NUM_GPUS=${NUM_GPUS}"
+    exit 1
+fi
+
+export RAY_health_check_failure_threshold=20
+export RAY_health_check_period_ms=5000
+export RAY_health_check_timeout_ms=30000
+export RAY_num_heartbeats_timeout=60
+
+NVLINK_COUNT=$(nvidia-smi topo -m 2>/dev/null | grep -o 'NV[0-9][0-9]*' | wc -l)
+if [ "${NVLINK_COUNT}" -gt 0 ]; then
+    HAS_NVLINK=1
+else
+    HAS_NVLINK=0
+fi
+echo "HAS_NVLINK: $HAS_NVLINK (detected $NVLINK_COUNT NVLink references)"
+
+SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" &>/dev/null && pwd)"
+ROOT_DIR="$(cd -- "${SCRIPT_DIR}/.." &>/dev/null && pwd)"
+SLIME_DIR="${ROOT_DIR}/slime"
+MEGATRON_LM_PATH=${MEGATRON_LM_PATH:-"${ROOT_DIR}/Megatron-LM"}
+if [[ ! -d "${MEGATRON_LM_PATH}" ]]; then
+    echo "MEGATRON_LM_PATH does not exist: ${MEGATRON_LM_PATH}"
+    exit 1
+fi
+
+# Do not mix the bridge checkout's bundled Megatron with this script.
+# For text-only retool we intentionally use the repo's Megatron-LM tree.
+source "${SLIME_DIR}/scripts/models/qwen3.5-4B.sh"
+
+HF_CKPT=${HF_CKPT:-/data_storage/wyj/systems/huggingface/hub/Qwen35-4B}
+REF_LOAD=${REF_LOAD:-${HF_CKPT}}
+SAVE_CKPT=${SAVE_CKPT:-/data_storage/wyj/OpenClaw-RL/ckpt/qwen35-4b-retool-rl/}
+RESUME_LOAD=${RESUME_LOAD:-${SAVE_CKPT}}
+
+export SGLANG_LANGUAGE_ONLY="${SGLANG_LANGUAGE_ONLY:-1}"
+export SLIME_QWEN35_TEXT_ONLY_BRIDGE="${SLIME_QWEN35_TEXT_ONLY_BRIDGE:-1}"
+
+CKPT_ARGS=(
+   --megatron-to-hf-mode bridge
+   --hf-checkpoint "${HF_CKPT}"
+   --ref-load "${REF_LOAD}"
+   --save "${SAVE_CKPT}"
+   --save-interval 20
+   --rotary-base 10000000
+)
+
+ROLLOUT_ARGS=(
+   --prompt-data /data_storage/wyj/OpenClaw-RL1/data/dapo-math-17k/dapo-math-17k.jsonl
+   --input-key prompt
+   --label-key label
+   --apply-chat-template
+   --rollout-shuffle
+   --reward-key score
+   --num-rollout 3000
+   --rollout-batch-size 32
+   --n-samples-per-prompt 8
+   --rollout-max-response-len 8192
+   --rollout-max-context-len 16384
+   --rollout-temperature 1
+   --num-steps-per-rollout 2
+   --balance-data
+)
+
+EVAL_ARGS=(
+   --eval-interval 20
+   --eval-prompt-data aime /data_storage/wyj/OpenClaw-RL1/data/aime-2024/aime-2024.jsonl
+   --n-samples-per-eval-prompt 16
+   --eval-max-response-len 16384
+   --eval-max-context-len 32768
+   --eval-top-p 1
+   --eval-reward-key acc
+)
+
+PERF_ARGS=(
+   --tensor-model-parallel-size 4
+   --sequence-parallel
+   --pipeline-model-parallel-size 1
+   --context-parallel-size 1
+   --expert-model-parallel-size 1
+   --expert-tensor-parallel-size 1
+   --recompute-granularity full
+   --recompute-method uniform
+   --recompute-num-layers 1
+   --use-dynamic-batch-size
+   --max-tokens-per-gpu 16384
+   --log-probs-chunk-size 1024
+)
+
+GRPO_ARGS=(
+   --advantage-estimator grpo
+   --use-kl-loss
+   --kl-loss-coef 0.01
+   --kl-loss-type k3
+   --entropy-coef 0.00
+   --eps-clip 0.2
+   --eps-clip-high 0.28
+)
+
+OPTIMIZER_ARGS=(
+   --optimizer adam
+   --lr 1e-6
+   --lr-decay-style constant
+   --weight-decay 0.1
+   --adam-beta1 0.9
+   --adam-beta2 0.98
+   --optimizer-cpu-offload
+   --overlap-cpu-optimizer-d2h-h2d
+   --use-precision-aware-optimizer
+)
+
+if [[ -n "${WANDB_KEY:-}" ]]; then
+   WANDB_ARGS=(
+      --use-wandb
+      --wandb-project "${WANDB_PROJECT:-slime_retool}"
+      --wandb-group "${WANDB_GROUP:-qwen35-4B-rl_retool}"
+      --wandb-key "${WANDB_KEY}"
+   )
+else
+   WANDB_ARGS=()
+fi
+
+SGLANG_ARGS=(
+   --rollout-num-gpus-per-engine 2
+   --sglang-mem-fraction-static 0.6
+)
+
+if [[ "${SGLANG_LANGUAGE_ONLY}" == "1" ]]; then
+  SGLANG_ARGS+=(--sglang-language-only)
+fi
+
+MISC_ARGS=(
+   --attention-dropout 0.0
+   --hidden-dropout 0.0
+   --accumulate-allreduce-grads-in-fp32
+   --attention-softmax-in-fp32
+   --attention-backend flash
+)
+
+CUSTOM_ARGS=(
+   --custom-generate-function-path generate_with_retool.generate
+   --custom-rm-path generate_with_retool.reward_func
+)
+
+export PYTORCH_CUDA_ALLOC_CONF=${PYTORCH_CUDA_ALLOC_CONF:-"max_split_size_mb:2048,expandable_segments:True"}
+
+export MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}
+ray start --head --node-ip-address "${MASTER_ADDR}" --num-gpus "${NUM_GPUS}" --disable-usage-stats --dashboard-host=0.0.0.0 --dashboard-port=8265
+
+RUNTIME_ENV_JSON="{
+  \"env_vars\": {
+    \"PYTHONPATH\": \"${MEGATRON_LM_PATH}:${SCRIPT_DIR}:${SLIME_DIR}\",
+    \"CUDA_DEVICE_MAX_CONNECTIONS\": \"1\",
+    \"NCCL_NVLS_ENABLE\": \"${HAS_NVLINK}\",
+    \"FLASHINFER_WORKSPACE_BASE\": \"${FLASHINFER_WORKSPACE_BASE}\",
+    \"PYTORCH_CUDA_ALLOC_CONF\": \"${PYTORCH_CUDA_ALLOC_CONF}\",
+    \"SLIME_QWEN35_TEXT_ONLY_BRIDGE\": \"${SLIME_QWEN35_TEXT_ONLY_BRIDGE}\",
+    \"MEGATRON_LM_PATH\": \"${MEGATRON_LM_PATH}\",
+    \"HF_CKPT\": \"${HF_CKPT}\"
+  }
+}"
+
+ray job submit --address="http://127.0.0.1:8265" \
+   --runtime-env-json="${RUNTIME_ENV_JSON}" \
+   -- python3 "${SLIME_DIR}/train_async.py" \
+   --actor-num-nodes 1 \
+   --actor-num-gpus-per-node "${ACTOR_GPUS}" \
+   --rollout-num-gpus "${ROLLOUT_GPUS}" \
+   ${MODEL_ARGS[@]} \
+   ${CKPT_ARGS[@]} \
+   ${ROLLOUT_ARGS[@]} \
+   ${OPTIMIZER_ARGS[@]} \
+   ${GRPO_ARGS[@]} \
+   ${WANDB_ARGS[@]} \
+   ${PERF_ARGS[@]} \
+   ${EVAL_ARGS[@]} \
+   ${SGLANG_ARGS[@]} \
+   ${MISC_ARGS[@]} \
+   ${CUSTOM_ARGS[@]}