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README.md

@@ -153,12 +153,16 @@ from datasets import load_dataset
 dataset = load_dataset("MiniMaxAI/OctoCodingBench")
 
 # Filter by category
-skill_tasks = [d for d in dataset["test"] if d["category"] == "Skill"]
+skill_tasks = [d for d in dataset["train"] if d["category"] == "Skill"]
 
 # Filter by scaffold
-claudecode_tasks = [d for d in dataset["test"] if d["scaffold"]["name"] == "claudecode"]
+claudecode_tasks = [d for d in dataset["train"] if d["scaffold"]["name"] == "claudecode"]
 ```
 
+### 🔧 Evaluation Toolkit
+
+The evaluation toolkit (trajectory collection + LLM-as-a-judge scoring) will be open-sourced soon. Stay tuned!
+
 ## ⚖️ Evaluation Metrics
 
 | Metric | Definition | What it measures |

README_CN.md

@@ -153,12 +153,16 @@ from datasets import load_dataset
 dataset = load_dataset("MiniMaxAI/OctoCodingBench")
 
 # 按类别筛选
-skill_tasks = [d for d in dataset["test"] if d["category"] == "Skill"]
+skill_tasks = [d for d in dataset["train"] if d["category"] == "Skill"]
 
 # 按脚手架筛选
-claudecode_tasks = [d for d in dataset["test"] if d["scaffold"]["name"] == "claudecode"]
+claudecode_tasks = [d for d in dataset["train"] if d["scaffold"]["name"] == "claudecode"]
 ```
 
+### 🔧 评测工具
+
+评测工具（轨迹收集 + LLM-as-a-judge 评分）即将开源，敬请期待！
+
 ## ⚖️ 评估指标
 
 | 指标 | 定义 | 衡量内容 |