diff --git a/skills/logic-planner/SKILL.md b/skills/logic-planner/SKILL.md
index 3ffe6ed..a1dcdaf 100644
--- a/skills/logic-planner/SKILL.md
+++ b/skills/logic-planner/SKILL.md
@@ -113,7 +113,7 @@ logic_plan:
       right: { alias: c, table: customer_info }
       keys: ["o.customer_id = c.customer_id"]
       type: left
-      cardinality_assumption: 1:N   # 已知时填;否则写 "unknown"
+      cardinality_assumption: 1:N   # if known; else state "unknown"
     - kind: transform
       alias: o
       expressions:
diff --git a/skills/pyspark-sql-guardrails/SKILL.md b/skills/pyspark-sql-guardrails/SKILL.md
index dafc8da..b5f8cc2 100644
--- a/skills/pyspark-sql-guardrails/SKILL.md
+++ b/skills/pyspark-sql-guardrails/SKILL.md
@@ -12,13 +12,13 @@ description: 在编写或评审 PySpark 脚本、Spark SQL 字符串、`spark.sq
 整条流程就是两条命令 + 一个条件:
 
 ```bash
-# 第 1 步 — 生成 SQL(脑中起草 / 写出来)
-# 第 2 步 — 立即把 SQL 喂给校验器(在同一轮里跑)
+# Step 1 — Generate the SQL (do this in your head / draft)
+# Step 2 — Run the validator on it (do this IMMEDIATELY, in the same turn)
 echo "<the SQL you just wrote>" | python3 skills/pyspark-sql-guardrails/scripts/validate_sql.py
 
-# 第 3 步 — 读输出:
-#   PASS - first keyword: select, body length: N   → 可以把 SQL 给用户看了
-#   FAIL - <reason>                                → 停下,修 SQL,再跑一次
+# Step 3 — Read the output:
+#   PASS - first keyword: select, body length: N   → you may now show the SQL
+#   FAIL - <reason>                                → STOP. Fix the SQL. Re-run.
 ```
 
 **如果你还没把 `PASS -` 这一行贴到对话里,就不允许贴 SQL。** 校验器就是关口,SQL 站在关口的另一边,绝不能空着手闯关。
@@ -46,21 +46,21 @@ echo "<the SQL you just wrote>" | python3 skills/pyspark-sql-guardrails/scripts/
 唯一可接受的调用形式:
 
 ```python
-# 推荐:封装函数,校验+执行一步到位
+# Preferred: wrapper that validates + executes atomically
 safe_spark_sql(spark, sql)
 
-# 或者:先校验,再显式执行
-assert_select_or_insert(sql)        # 违规即抛错
+# Or: validate first, then execute explicitly
+assert_select_or_insert(sql)        # raises on violation
 spark.sql(sql)
 ```
 
 **禁止的调用形式(出现即视为流水线失败):**
 
 ```python
-spark.sql(sql)                                # 直接调用,未校验
-spark.sql(f"SELECT ... {user_input} ...")     # f-string 直接进 spark.sql
-spark.sql(config["sql"])                      # 配置驱动的 SQL 未校验
-spark.sql(open("queries/xxx.sql").read())     # 从文件加载的 SQL 未校验
+spark.sql(sql)                                # direct, no validation
+spark.sql(f"SELECT ... {user_input} ...")     # f-string into spark.sql
+spark.sql(config["sql"])                      # config-driven without validation
+spark.sql(open("queries/xxx.sql").read())     # file-loaded without validation
 ```
 
 如果 `assert_select_or_insert()` 抛错,流水线立即停止。**不要**削弱规则,**不要**用正则去剥除禁用关键字,**不要**把 SQL"改写"成看似安全的样子。要么拒绝,要么重新生成。
@@ -115,7 +115,7 @@ def assert_select_or_insert(sql: str) -> str:
     if not text:
         raise ValueError("SQL is empty")
 
-    # 允许一个可选的尾随分号,但拒绝多条堆叠的语句
+    # Allow one optional trailing semicolon, but reject stacked statements.
     body = text[:-1].strip() if text.endswith(";") else text
     if ";" in body:
         raise ValueError("Multiple SQL statements are not allowed")
@@ -138,13 +138,13 @@ def assert_select_or_insert(sql: str) -> str:
 def safe_spark_sql(spark, sql: str):
     return spark.sql(assert_select_or_insert(sql))
 
-# 正确
+# Good
 safe_spark_sql(spark, """
 INSERT INTO analytics.daily_customer_snapshot
 SELECT * FROM staging.daily_customer_snapshot
 """)
 
-# 错误:在 Spark 看到 SQL 之前就抛错
+# Bad: raises before Spark sees it
 safe_spark_sql(spark, "ALTER TABLE analytics.daily_customer_snapshot DROP PARTITION (dt='2026-06-10')")
 ```
 
@@ -158,11 +158,11 @@ safe_spark_sql(spark, "ALTER TABLE analytics.daily_customer_snapshot DROP PARTIT
 
 ```
 skills/pyspark-sql-guardrails/
-├── SKILL.md           ← 本文件
+├── SKILL.md           ← this file
 └── scripts/
-    ├── sql_guard.py       ← 权威校验器(assert_select_or_insert + safe_spark_sql)
-    ├── validate_sql.py    ← 一行 CLI:管道喂 SQL,输出 PASS/FAIL
-    └── test_sql_guard.py  ← 18 用例的标准测试集
+    ├── sql_guard.py       ← canonical validator (assert_select_or_insert + safe_spark_sql)
+    ├── validate_sql.py    ← one-line CLI: pipe SQL in, get PASS/FAIL out
+    └── test_sql_guard.py  ← 18-case standard test set
 ```
 
 ### 第 1 步 — 用内置校验器(不复制、不重写)
@@ -172,7 +172,7 @@ skill 自带一个一行 CLI:`validate_sql.py`。用它。不要写不同的调
 **两种把 SQL 喂给校验器的方法:**
 
 ```bash
-# 方法 A(推荐,适合多行):走 stdin
+# Way A (preferred for multi-line): pipe via stdin
 cat <<'EOF' | python3 skills/pyspark-sql-guardrails/scripts/validate_sql.py
 SELECT
     c.city AS city,
@@ -183,7 +183,7 @@ WHERE o.status = 'SUCCESS'
 GROUP BY c.city
 EOF
 
-# 方法 B(仅适合单行):作为第一个参数传入
+# Way B (single-line only): pass as first argument
 python3 skills/pyspark-sql-guardrails/scripts/validate_sql.py "SELECT 1 FROM dual"
 ```
 
@@ -195,7 +195,7 @@ python3 skills/pyspark-sql-guardrails/scripts/validate_sql.py "SELECT 1 FROM dua
 内置的 `sql_guard.py` 和 `validate_sql.py` 一并展示:
 
 ```python
-# sql_guard.py  (内置)
+# sql_guard.py  (bundled)
 import re
 
 _FORBIDDEN_SQL = re.compile(
@@ -227,7 +227,7 @@ def safe_spark_sql(spark, sql: str):
     return spark.sql(assert_select_or_insert(sql))
 
 
-# validate_sql.py  (内置,精简版)
+# validate_sql.py  (bundled, abridged)
 import sys, os
 SKILL_DIR = os.path.dirname(os.path.abspath(__file__))
 sys.path.insert(0, SKILL_DIR)
@@ -265,10 +265,10 @@ PASS - first keyword: select, body length: 420
 skill 自带 `test_sql_guard.py`,含 6 个 EXPECT_OK + 12 个 EXPECT_RAISE 用例。每次校验器改动,以及在 CI 中,都要在 skill 目录下跑一遍:
 
 ```bash
-# 在项目根目录
+# From project root
 python3 skills/pyspark-sql-guardrails/scripts/test_sql_guard.py
 
-# 或在 scripts/ 目录下
+# Or from the scripts/ directory
 cd skills/pyspark-sql-guardrails/scripts
 python3 test_sql_guard.py
 ```
diff --git a/skills/pyspark-sql-pipeline/SKILL.md b/skills/pyspark-sql-pipeline/SKILL.md
index 6e23f0f..edb88f2 100644
--- a/skills/pyspark-sql-pipeline/SKILL.md
+++ b/skills/pyspark-sql-pipeline/SKILL.md
@@ -32,15 +32,15 @@ digraph pipeline {
     "2. metadata-validator" [shape=box];
     "3. logic-planner" [shape=box];
     "4. sql-context-builder" [shape=box];
-    "5. SQL 生成" [shape=box];
+    "5. SQL generation" [shape=box];
     "6. pyspark-sql-guardrails" [shape=box];
     "7. sql-review" [shape=box];
 
     "1. requirements-analysis" -> "2. metadata-validator" [label="status=READY_FOR_VALIDATION"];
     "2. metadata-validator" -> "3. logic-planner" [label="status=VALIDATED"];
     "3. logic-planner" -> "4. sql-context-builder" [label="status=PLANNED"];
-    "4. sql-context-builder" -> "5. SQL 生成" [label="status=READY"];
-    "5. SQL 生成" -> "6. pyspark-sql-guardrails" [label="SQL 字符串"];
+    "4. sql-context-builder" -> "5. SQL generation" [label="status=READY"];
+    "5. SQL generation" -> "6. pyspark-sql-guardrails" [label="SQL 字符串"];
     "6. pyspark-sql-guardrails" -> "7. sql-review" [label="guardrail pass"];
 }
 ```
@@ -84,13 +84,13 @@ digraph pipeline {
 每个关口应产出一条结构化消息,格式如下:
 
 ```markdown
-## Pipeline paused at: <阶段名>
+## Pipeline paused at: <stage name>
 **Status:** NEED_USER_CONFIRMATION
 **Open questions:**
-1. <问题 1>
-2. <问题 2>
+1. <question 1>
+2. <question 2>
 **Pending options:** A / B / C / other
-**To resume:** 回答以上问题后,说"继续"。
+**To resume:** answer the questions above, then say "继续" (continue).
 ```
 
 不要把某个阶段的输出当作最终结果,如果它的状态是停止状态。不要把 `pending_questions` 埋在冗长叙述里。