fix: address code review issues from Claude and GPT-5.2

- report/SKILL.md: add AskUserQuestion to allowed-tools
- validate_json.py: remove unused imports (List, Any)
- validate_json.py: sort output lists for deterministic order
- validate_json.py: limit recursion to category level only
- validate_json.py: add list-of-dict handling
- EN validate_json.py: remove Chinese from CATEGORY_MAPPING
- EN deep/SKILL.md: change output language from Chinese to English
- deep/SKILL.md: add slug handling for filenames
- report/SKILL.md: fix uncertain_fields -> uncertain naming
- README: add PyYAML dependency note

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

README.md

@@ -24,6 +24,9 @@ cp -r skills/research-zh ~/.claude/skills/research
 
 # Required: Install agent
 cp agents/web-search-agent.md ~/.claude/agents/
+
+# Required: Install Python dependency
+pip install pyyaml
 ```
 
 ## Commands

README.zh.md

@@ -24,6 +24,9 @@ cp -r skills/research-en ~/.claude/skills/research
 
 # 必需：安装agent
 cp agents/web-search-agent.md ~/.claude/agents/
+
+# 必需：安装Python依赖
+pip install pyyaml
 ```
 
 ## 命令

skills/research-en/deep/SKILL.md

@@ -28,7 +28,7 @@ Find `*/outline.yaml` file in current working directory, read items list, execut
 - `{item_related_info}`: item's complete yaml content (name + category + description etc.)
 - `{output_dir}`: execution.output_dir from outline.yaml (default: ./results)
 - `{fields_path}`: absolute path to {topic}/fields.yaml
-- `{output_path}`: absolute path to {output_dir}/{item_name}.json
+- `{output_path}`: absolute path to {output_dir}/{item_name_slug}.json (slugify item_name: replace spaces with _, remove special chars)
 
 **Hard Constraint**: The following prompt must be strictly reproduced, only replacing variables in {xxx}, do not modify structure or wording.
 
@@ -44,7 +44,7 @@ Read {fields_path} to get all field definitions
 1. Output JSON according to fields defined in fields.yaml
 2. Mark uncertain field values with [uncertain]
 3. Add uncertain array at the end of JSON, listing all uncertain field names
-4. All field values must be in Chinese (research can be in English, but final JSON values in Chinese)
+4. All field values must be in English
 
 ## Output Path
 {output_path}
@@ -70,7 +70,7 @@ Read /home/weizhena/AIcoding/aicoding-history/fields.yaml to get all field defin
 1. Output JSON according to fields defined in fields.yaml
 2. Mark uncertain field values with [uncertain]
 3. Add uncertain array at the end of JSON, listing all uncertain field names
-4. All field values must be in Chinese (research can be in English, but final JSON values in Chinese)
+4. All field values must be in English
 
 ## Output Path
 /home/weizhena/AIcoding/aicoding-history/results/GitHub_Copilot.json

skills/research-en/report/SKILL.md

@@ -1,6 +1,6 @@
 ---
 description: Summarize deep research results into markdown report, cover all fields, skip uncertain values.
-allowed-tools: Read, Write, Glob, Bash
+allowed-tools: Read, Write, Glob, Bash, AskUserQuestion
 ---
 
 # Research Report - Summary Report
@@ -75,7 +75,7 @@ CATEGORY_MAPPING = {
 Collect fields that exist in JSON but not defined in fields.yaml, put in "Other Info" category. Note to filter:
 - Internal fields: `_source_file`, `uncertain`
 - Nested structure top-level keys: `basic_info`, `technical_features` etc.
-- `uncertain_fields` list: Display each field name on separate line, don't compress into one line
+- `uncertain` array: Display each field name on separate line, don't compress into one line
 
 **5. Uncertain Value Skipping**
 Skip conditions:

skills/research-en/validate_json.py

@@ -9,18 +9,18 @@ import json
 import yaml
 import sys
 from pathlib import Path
-from typing import Dict, List, Set, Any, Tuple
+from typing import Dict, Set, Tuple
 
-# Category mapping (supports both Chinese and English keys)
+# Category mapping (English keys only)
 CATEGORY_MAPPING = {
-    "basic_info": ["basic_info", "基本信息"],
+    "basic_info": ["basic_info", "Basic Info"],
-    "technical_features": ["technical_features", "technical_characteristics", "技术特性"],
+    "technical_features": ["technical_features", "technical_characteristics", "Technical Features"],
-    "performance_metrics": ["performance_metrics", "performance", "性能指标"],
+    "performance_metrics": ["performance_metrics", "performance", "Performance Metrics"],
-    "milestone_significance": ["milestone_significance", "milestones", "里程碑意义"],
+    "milestone_significance": ["milestone_significance", "milestones", "Milestone Significance"],
-    "business_info": ["business_info", "commercial_info", "商业信息"],
+    "business_info": ["business_info", "commercial_info", "Business Info"],
-    "competition_ecosystem": ["competition_ecosystem", "competition", "竞争与生态"],
+    "competition_ecosystem": ["competition_ecosystem", "competition", "Competition Ecosystem"],
-    "history": ["history", "历史沿革"],
+    "history": ["history", "History"],
-    "market_positioning": ["market_positioning", "market", "市场定位"],
+    "market_positioning": ["market_positioning", "market", "Market Positioning"],
 }
 
 
@@ -53,30 +53,41 @@ def load_fields_yaml(fields_path: Path) -> Tuple[Set[str], Set[str], Dict[str, s
 def extract_json_fields(data: Dict, category_mapping: Dict = None) -> Set[str]:
     """
     Extract all field names from JSON (supports both flat and nested structures)
+    Only extracts field names at category level, not nested dict/list values
     """
     if category_mapping is None:
         category_mapping = CATEGORY_MAPPING
 
-    # Get all possible nested keys
+    # Get all possible nested keys (category containers)
     nested_keys = set()
     for keys in category_mapping.values():
         nested_keys.update(keys)
 
     fields = set()
 
-    def collect_fields(d: Dict, is_top_level: bool = True):
+    def collect_fields(d, is_category_level: bool = True):
-        for k, v in d.items():
+        """
-            # Skip internal fields
+        Collect fields from dict or list structures
-            if k in {"_source_file", "uncertain"}:
+        is_category_level: True if we're at top level or inside a category container
-                continue
+        """
-            # If it's a top-level nested key, recurse into it
+        if isinstance(d, dict):
-            if is_top_level and k in nested_keys:
+            for k, v in d.items():
-                if isinstance(v, dict):
+                # Skip internal fields
-                    collect_fields(v, is_top_level=False)
+                if k in {"_source_file", "uncertain"}:
-            else:
+                    continue
-                fields.add(k)
+                # If it's a category container key, recurse into it
-                if isinstance(v, dict):
+                if is_category_level and k in nested_keys:
-                    collect_fields(v, is_top_level=False)
+                    if isinstance(v, dict):
+                        collect_fields(v, is_category_level=True)
+                else:
+                    # This is a field name, add it
+                    fields.add(k)
+                    # Don't recurse into field values (avoid counting nested keys as fields)
+        elif isinstance(d, list):
+            # Handle list-of-dict structures at category level
+            for item in d:
+                if isinstance(item, dict):
+                    collect_fields(item, is_category_level=is_category_level)
 
     collect_fields(data)
     return fields
@@ -110,6 +121,10 @@ def validate_json(json_path: Path, all_fields: Set[str], required_fields: Set[st
             missing_by_category[cat] = []
         missing_by_category[cat].append(field)
 
+    # Sort lists within categories for deterministic output
+    for cat in missing_by_category:
+        missing_by_category[cat].sort()
+
     return {
         "file": json_path.name,
         "total_defined": len(all_fields),
@@ -117,10 +132,10 @@ def validate_json(json_path: Path, all_fields: Set[str], required_fields: Set[st
         "missing": len(missing),
         "extra": len(extra),
         "coverage_rate": len(covered) / len(all_fields) * 100 if all_fields else 100,
-        "missing_required": list(missing_required),
+        "missing_required": sorted(missing_required),
-        "missing_optional": list(missing_optional),
+        "missing_optional": sorted(missing_optional),
         "missing_by_category": missing_by_category,
-        "extra_fields": list(extra),
+        "extra_fields": sorted(extra),
         "valid": len(missing_required) == 0,  # Valid if all required fields are covered
     }
 
@@ -140,7 +155,8 @@ def print_result(result: Dict, verbose: bool = True):
 
     if verbose and result["missing_optional"]:
         print(f"\n[WARN] Missing optional fields ({len(result['missing_optional'])}):")
-        for cat, fields in result["missing_by_category"].items():
+        for cat in sorted(result["missing_by_category"].keys()):
+            fields = result["missing_by_category"][cat]
             optional_fields = [f for f in fields if f not in result["missing_required"]]
             if optional_fields:
                 print(f"  [{cat}]: {', '.join(optional_fields)}")

skills/research-zh/deep/SKILL.md

@@ -28,7 +28,7 @@ allowed-tools: Bash, Read, Write, Glob, WebSearch, Task
 - `{item_related_info}`: item的完整yaml内容（name + category + description等）
 - `{output_dir}`: outline.yaml中execution.output_dir（默认./results）
 - `{fields_path}`: {topic}/fields.yaml的绝对路径
-- `{output_path}`: {output_dir}/{item_name}.json的绝对路径
+- `{output_path}`: {output_dir}/{item_name_slug}.json的绝对路径（slugify处理item_name：空格替换为_，移除特殊字符）
 
 **硬约束**：以下prompt必须严格复述，仅替换{xxx}中的变量，禁止改写结构或措辞。
 

skills/research-zh/report/SKILL.md

@@ -1,6 +1,6 @@
 ---
 description: 将deep调研结果汇总为markdown报告，覆盖所有字段，跳过不确定值。
-allowed-tools: Read, Write, Glob, Bash
+allowed-tools: Read, Write, Glob, Bash, AskUserQuestion
 ---
 
 # Research Report - 汇总报告
@@ -75,7 +75,7 @@ CATEGORY_MAPPING = {
 收集JSON中有但fields.yaml中没定义的字段，放入"其他信息"分类。注意过滤：
 - 内部字段：`_source_file`, `uncertain`
 - 嵌套结构顶级key：`basic_info`, `technical_features`等
-- `uncertain_fields`列表：需要逐行显示每个字段名，不要压缩成一行
+- `uncertain`数组：需要逐行显示每个字段名，不要压缩成一行
 
 **5. 不确定值跳过**
 跳过条件：

skills/research-zh/validate_json.py

@@ -9,7 +9,7 @@ import json
 import yaml
 import sys
 from pathlib import Path
-from typing import Dict, List, Set, Any, Tuple
+from typing import Dict, Set, Tuple
 
 # Category中英文映射
 CATEGORY_MAPPING = {
@@ -53,30 +53,41 @@ def load_fields_yaml(fields_path: Path) -> Tuple[Set[str], Set[str], Dict[str, s
 def extract_json_fields(data: Dict, category_mapping: Dict = None) -> Set[str]:
     """
     从JSON中提取所有字段名（支持扁平和嵌套结构）
+    只提取category级别的字段名，不递归到字段值的dict/list中
     """
     if category_mapping is None:
         category_mapping = CATEGORY_MAPPING
 
-    # 获取所有可能的嵌套key
+    # 获取所有可能的嵌套key（category容器）
     nested_keys = set()
     for keys in category_mapping.values():
         nested_keys.update(keys)
 
     fields = set()
 
-    def collect_fields(d: Dict, is_top_level: bool = True):
+    def collect_fields(d, is_category_level: bool = True):
-        for k, v in d.items():
+        """
-            # 跳过内部字段
+        从dict或list结构中收集字段
-            if k in {"_source_file", "uncertain"}:
+        is_category_level: True表示在顶层或category容器内部
-                continue
+        """
-            # 如果是嵌套结构的顶级key，递归进入
+        if isinstance(d, dict):
-            if is_top_level and k in nested_keys:
+            for k, v in d.items():
-                if isinstance(v, dict):
+                # 跳过内部字段
-                    collect_fields(v, is_top_level=False)
+                if k in {"_source_file", "uncertain"}:
-            else:
+                    continue
-                fields.add(k)
+                # 如果是category容器key，递归进入
-                if isinstance(v, dict):
+                if is_category_level and k in nested_keys:
-                    collect_fields(v, is_top_level=False)
+                    if isinstance(v, dict):
+                        collect_fields(v, is_category_level=True)
+                else:
+                    # 这是一个字段名，添加它
+                    fields.add(k)
+                    # 不递归到字段值中（避免将嵌套key误计为字段）
+        elif isinstance(d, list):
+            # 处理category级别的list-of-dict结构
+            for item in d:
+                if isinstance(item, dict):
+                    collect_fields(item, is_category_level=is_category_level)
 
     collect_fields(data)
     return fields
@@ -110,6 +121,10 @@ def validate_json(json_path: Path, all_fields: Set[str], required_fields: Set[st
             missing_by_category[cat] = []
         missing_by_category[cat].append(field)
 
+    # 对category内的列表排序，确保输出确定性
+    for cat in missing_by_category:
+        missing_by_category[cat].sort()
+
     return {
         "file": json_path.name,
         "total_defined": len(all_fields),
@@ -117,10 +132,10 @@ def validate_json(json_path: Path, all_fields: Set[str], required_fields: Set[st
         "missing": len(missing),
         "extra": len(extra),
         "coverage_rate": len(covered) / len(all_fields) * 100 if all_fields else 100,
-        "missing_required": list(missing_required),
+        "missing_required": sorted(missing_required),
-        "missing_optional": list(missing_optional),
+        "missing_optional": sorted(missing_optional),
         "missing_by_category": missing_by_category,
-        "extra_fields": list(extra),
+        "extra_fields": sorted(extra),
         "valid": len(missing_required) == 0,  # required字段全覆盖则valid
     }
 
@@ -140,7 +155,8 @@ def print_result(result: Dict, verbose: bool = True):
 
     if verbose and result["missing_optional"]:
         print(f"\n[WARN] 缺失可选字段 ({len(result['missing_optional'])}):")
-        for cat, fields in result["missing_by_category"].items():
+        for cat in sorted(result["missing_by_category"].keys()):
+            fields = result["missing_by_category"][cat]
             optional_fields = [f for f in fields if f not in result["missing_required"]]
             if optional_fields:
                 print(f"  [{cat}]: {', '.join(optional_fields)}")