feat: 添加 Linux/Windows 双平台测试套件（云南省界叠加分析）

- test-linux: platform=linux, docker + python3
- test-windows: platform=windows, arcpy + python3
- 附示例 GeoJSON: 云南/昆明/大理/百色

Ref: SuiteHub/agent-profiles#22

suites/test-linux/data/baise.geojson

@@ -0,0 +1,17 @@
+{
+  "type": "FeatureCollection",
+  "features": [
+    {
+      "type": "Feature",
+      "properties": { "name": "百色市", "code": "451000", "population": 3600000 },
+      "geometry": {
+        "type": "Polygon",
+        "coordinates": [[
+          [105.5, 24.5], [105.8, 24.3], [106.2, 24.0], [106.8, 23.8],
+          [107.3, 23.5], [107.5, 23.2], [107.3, 23.0], [107.0, 23.2],
+          [106.5, 23.5], [106.0, 23.8], [105.7, 24.0], [105.5, 24.5]
+        ]]
+      }
+    }
+  ]
+}

suites/test-linux/data/dali.geojson

@@ -0,0 +1,17 @@
+{
+  "type": "FeatureCollection",
+  "features": [
+    {
+      "type": "Feature",
+      "properties": { "name": "大理州", "code": "532900", "population": 3300000 },
+      "geometry": {
+        "type": "Polygon",
+        "coordinates": [[
+          [99.5, 26.5], [99.8, 26.3], [100.0, 26.2], [100.3, 26.0],
+          [100.5, 25.8], [100.4, 25.5], [100.3, 25.3], [100.1, 25.1],
+          [99.9, 25.0], [99.7, 25.1], [99.5, 25.3], [99.5, 26.5]
+        ]]
+      }
+    }
+  ]
+}

suites/test-linux/data/kunming.geojson

@@ -0,0 +1,18 @@
+{
+  "type": "FeatureCollection",
+  "features": [
+    {
+      "type": "Feature",
+      "properties": { "name": "昆明市", "code": "530100", "population": 8500000 },
+      "geometry": {
+        "type": "Polygon",
+        "coordinates": [[
+          [102.4, 25.7], [102.6, 25.6], [102.9, 25.5], [103.1, 25.4],
+          [103.4, 25.2], [103.3, 24.9], [103.2, 24.7], [103.0, 24.5],
+          [102.8, 24.4], [102.6, 24.5], [102.5, 24.7], [102.4, 24.9],
+          [102.4, 25.7]
+        ]]
+      }
+    }
+  ]
+}

suites/test-linux/data/yunnan.geojson

@@ -0,0 +1,19 @@
+{
+  "type": "FeatureCollection",
+  "features": [
+    {
+      "type": "Feature",
+      "properties": { "name": "云南省", "code": "530000" },
+      "geometry": {
+        "type": "Polygon",
+        "coordinates": [[
+          [97.5, 27.5], [98.5, 28.8], [100.0, 29.3], [101.5, 28.5],
+          [103.0, 28.0], [104.5, 27.5], [105.5, 26.5], [106.2, 25.5],
+          [106.0, 24.0], [105.5, 23.0], [104.5, 22.2], [103.5, 22.0],
+          [102.5, 21.5], [101.5, 21.1], [100.5, 21.8], [99.5, 22.5],
+          [98.5, 23.5], [97.8, 24.5], [97.5, 25.5], [97.5, 27.5]
+        ]]
+      }
+    }
+  ]
+}

suites/test-linux/scripts/convert.py

@@ -0,0 +1,58 @@
+#!/usr/bin/env python3
+"""
+Step 1: GeoJSON → SHP
+将省界和城市 GeoJSON 文件转换为 Shapefile
+"""
+import sys
+import json
+import os
+import geopandas as gpd
+
+
+def main():
+    province_path = os.environ.get("PARAM_PROVINCE", "")
+    cities_param = os.environ.get("PARAM_CITIES", "")
+    output_dir = os.environ.get("PARAM_OUTPUT_DIR", "/tmp/output/shp")
+
+    if not province_path:
+        print(json.dumps({"error": "缺少 province 参数", "success": False}))
+        sys.exit(1)
+    if not cities_param:
+        print(json.dumps({"error": "缺少 cities 参数", "success": False}))
+        sys.exit(1)
+
+    os.makedirs(output_dir, exist_ok=True)
+
+    # 读取并转换省界
+    print(json.dumps({"msg": f"读取省界: {province_path}"}))
+    province_gdf = gpd.read_file(province_path)
+    province_shp = os.path.join(output_dir, "province.shp")
+    province_gdf.to_file(province_shp, driver="ESRI Shapefile")
+    print(json.dumps({"msg": f"省界已转为 SHP: {province_shp}", "count": len(province_gdf)}))
+
+    # 读取并转换每个城市 GeoJSON
+    city_files = [c.strip() for c in cities_param.split(",") if c.strip()]
+    converted = []
+    for cf in city_files:
+        if not os.path.isfile(cf):
+            print(json.dumps({"warn": f"文件不存在，跳过: {cf}"}))
+            continue
+        print(json.dumps({"msg": f"读取城市: {cf}"}))
+        gdf = gpd.read_file(cf)
+        base = os.path.splitext(os.path.basename(cf))[0]
+        shp_path = os.path.join(output_dir, f"{base}.shp")
+        gdf.to_file(shp_path, driver="ESRI Shapefile")
+        converted.append(base)
+        print(json.dumps({"msg": f"已转换: {cf} → {shp_path}", "count": len(gdf)}))
+
+    result = {
+        "success": True,
+        "province_shp": province_shp,
+        "city_count": len(converted),
+        "cities": converted
+    }
+    print(json.dumps(result))
+
+
+if __name__ == "__main__":
+    main()

suites/test-linux/scripts/excel.py

@@ -0,0 +1,90 @@
+#!/usr/bin/env python3
+"""
+Step 3: 输出 Excel
+将叠加分析结果写入 Excel 文件
+"""
+import sys
+import json
+import os
+from openpyxl import Workbook
+from openpyxl.styles import Font, Alignment, PatternFill
+
+
+def main():
+    result_dir = os.environ.get("PARAM_RESULT_DIR", "/tmp/output/result")
+    output_path = os.environ.get("PARAM_OUTPUT_PATH", "")
+
+    if not output_path:
+        print(json.dumps({"error": "缺少 output_path 参数", "success": False}))
+        sys.exit(1)
+
+    # 读取分析结果
+    result_json = os.path.join(result_dir, "overlay_results.json")
+    if not os.path.isfile(result_json):
+        print(json.dumps({"error": f"结果文件不存在: {result_json}", "success": False}))
+        sys.exit(1)
+
+    with open(result_json, "r", encoding="utf-8") as f:
+        results = json.load(f)
+
+    # 创建工作簿
+    wb = Workbook()
+    ws = wb.active
+    ws.title = "叠加分析结果"
+
+    # 标题样式
+    header_font = Font(bold=True, size=12, color="FFFFFF")
+    header_fill = PatternFill(start_color="4472C4", end_color="4472C4", fill_type="solid")
+    header_align = Alignment(horizontal="center", vertical="center")
+
+    # 表头
+    headers = ["城市", "城市代码", "城市名称", "人口", "在省内", "相交", "状态"]
+    for col, h in enumerate(headers, 1):
+        cell = ws.cell(row=1, column=col, value=h)
+        cell.font = header_font
+        cell.fill = header_fill
+        cell.alignment = header_align
+
+    # 数据行
+    pass_fill = PatternFill(start_color="E2EFDA", end_color="E2EFDA", fill_type="solid")
+    fail_fill = PatternFill(start_color="FCE4EC", end_color="FCE4EC", fill_type="solid")
+
+    for row_idx, r in enumerate(results, 2):
+        ws.cell(row=row_idx, column=1, value=r.get("city", ""))
+        ws.cell(row=row_idx, column=2, value=r.get("city_code", ""))
+        ws.cell(row=row_idx, column=3, value=r.get("city_name", ""))
+        ws.cell(row=row_idx, column=4, value=r.get("population", 0))
+        ws.cell(row=row_idx, column=5, value="是" if r.get("in_province") else "否")
+        ws.cell(row=row_idx, column=6, value="是" if r.get("intersects") else "否")
+        ws.cell(row=row_idx, column=7, value=r.get("status", ""))
+
+        # 条件高亮
+        fill = pass_fill if r.get("in_province") else fail_fill
+        for col in range(1, 8):
+            ws.cell(row=row_idx, column=col).fill = fill
+
+    # 调整列宽
+    ws.column_dimensions["A"].width = 15
+    ws.column_dimensions["B"].width = 12
+    ws.column_dimensions["C"].width = 15
+    ws.column_dimensions["D"].width = 12
+    ws.column_dimensions["E"].width = 10
+    ws.column_dimensions["F"].width = 10
+    ws.column_dimensions["G"].width = 15
+
+    # 确保输出目录存在
+    out_dir = os.path.dirname(output_path)
+    if out_dir:
+        os.makedirs(out_dir, exist_ok=True)
+
+    wb.save(output_path)
+    print(json.dumps({
+        "success": True,
+        "output_path": output_path,
+        "total": len(results),
+        "msg": f"Excel 已输出到: {output_path}"
+    }))
+
+
+if __name__ == "__main__":
+    main()

suites/test-linux/scripts/overlay.py

@@ -0,0 +1,100 @@
+#!/usr/bin/env python3
+"""
+Step 2: 叠加分析
+判断各城市是否在省界内（spatial join），输出分析结果
+"""
+import sys
+import json
+import os
+import glob
+import geopandas as gpd
+
+
+def main():
+    province_shp = os.environ.get("PARAM_PROVINCE_SHP", "")
+    cities_dir = os.environ.get("PARAM_CITIES_DIR", "/tmp/output/shp")
+    output_dir = os.environ.get("PARAM_OUTPUT_DIR", "/tmp/output/result")
+
+    if not province_shp or not os.path.isfile(province_shp):
+        print(json.dumps({"error": f"省界 SHP 文件不存在: {province_shp}", "success": False}))
+        sys.exit(1)
+
+    os.makedirs(output_dir, exist_ok=True)
+
+    # 读取省界
+    print(json.dumps({"msg": f"读取省界 SHP: {province_shp}"}))
+    province = gpd.read_file(province_shp)
+
+    if province.empty:
+        print(json.dumps({"error": "省界数据为空", "success": False}))
+        sys.exit(1)
+
+    # 确保坐标系一致
+    target_crs = province.crs or "EPSG:4326"
+    province = province.to_crs(target_crs)
+
+    # 查找所有城市 SHP
+    city_shp_files = glob.glob(os.path.join(cities_dir, "*.shp"))
+    city_shp_files = [f for f in city_shp_files
+                      if os.path.basename(f) != "province.shp"]
+
+    if not city_shp_files:
+        print(json.dumps({"error": "未找到城市 SHP 文件", "success": False}))
+        sys.exit(1)
+
+    results = []
+
+    for shp in city_shp_files:
+        city_name = os.path.splitext(os.path.basename(shp))[0]
+        print(json.dumps({"msg": f"分析城市: {city_name}"}))
+        city = gpd.read_file(shp)
+
+        if city.empty:
+            results.append({"city": city_name, "in_province": False,
+                            "reason": "数据为空", "status": "跳过"})
+            continue
+
+        city = city.to_crs(target_crs)
+
+        # 空间判断：城市中心点是否在省界内
+        city_centroid = city.geometry.centroid.iloc[0]
+        in_province = province.geometry.contains(city_centroid).any()
+
+        # 也检查 intersect 作为辅助判断
+        intersects = province.geometry.intersects(city.geometry).any()
+
+        status = "通过 ✅" if in_province else "不通过 ❌"
+
+        city_name_prop = city.iloc[0].get("name", city_name)
+        city_code = city.iloc[0].get("code", "")
+        city_pop = city.iloc[0].get("population", 0)
+
+        results.append({
+            "city": city_name,
+            "city_code": str(city_code),
+            "city_name": str(city_name_prop),
+            "population": int(city_pop) if city_pop else 0,
+            "in_province": bool(in_province),
+            "intersects": bool(intersects),
+            "status": status
+        })
+        print(json.dumps({"msg": f"{city_name}: {status}"}))
+
+    # 输出分析结果 JSON
+    result_path = os.path.join(output_dir, "overlay_results.json")
+    with open(result_path, "w", encoding="utf-8") as f:
+        json.dump(results, f, ensure_ascii=False, indent=2)
+
+    summary = {
+        "success": True,
+        "total_cities": len(results),
+        "in_province": sum(1 for r in results if r["in_province"]),
+        "not_in_province": sum(1 for r in results if not r["in_province"]),
+        "results": results,
+        "result_json": result_path
+    }
+    print(json.dumps(summary))
+
+
+if __name__ == "__main__":
+    main()

suites/test-linux/workflow.yaml

@@ -0,0 +1,53 @@
+name: 云南省界叠加分析（Linux 测试）
+description: 验证 GIS Actions 4.0 Linux 双平台执行链路的测试套件。将示例 GeoJSON 转为 SHP → 叠加分析（判断城市是否在省内）→ 输出 Excel
+version: 1.0.0
+author: SuiteForge
+platform: linux
+slug: test-yunnan-overlay-linux
+tags: [测试, 叠加分析, Linux, 云南省]
+category: 测试验证
+
+params:
+  province:
+    type: string
+    required: true
+    desc: 省界 GeoJSON 文件路径
+  cities:
+    type: string
+    required: true
+    desc: 待分析城市 GeoJSON 文件路径，多个文件用逗号分隔
+  output_path:
+    type: string
+    required: true
+    desc: 输出 Excel 文件路径（.xlsx）
+
+base_image: gis-base:latest
+
+steps:
+  - id: geojson_to_shp
+    name: 转为 SHP
+    runtime: docker
+    script_id: convert
+    params:
+      province: $params.province
+      cities: $params.cities
+      output_dir: /tmp/output/shp
+
+  - id: overlay
+    name: 叠加分析
+    runtime: docker
+    script_id: overlay
+    depends_on: [geojson_to_shp]
+    params:
+      province_shp: /tmp/output/shp/province.shp
+      cities_dir: /tmp/output/shp
+      output_dir: /tmp/output/result
+
+  - id: export_excel
+    name: 输出 Excel
+    runtime: python3
+    script_id: excel
+    depends_on: [overlay]
+    params:
+      result_dir: /tmp/output/result
+      output_path: $params.output_path

suites/test-windows/data/baise.geojson

@@ -0,0 +1,17 @@
+{
+  "type": "FeatureCollection",
+  "features": [
+    {
+      "type": "Feature",
+      "properties": { "name": "百色市", "code": "451000", "population": 3600000 },
+      "geometry": {
+        "type": "Polygon",
+        "coordinates": [[
+          [105.5, 24.5], [105.8, 24.3], [106.2, 24.0], [106.8, 23.8],
+          [107.3, 23.5], [107.5, 23.2], [107.3, 23.0], [107.0, 23.2],
+          [106.5, 23.5], [106.0, 23.8], [105.7, 24.0], [105.5, 24.5]
+        ]]
+      }
+    }
+  ]
+}

suites/test-windows/data/dali.geojson

@@ -0,0 +1,17 @@
+{
+  "type": "FeatureCollection",
+  "features": [
+    {
+      "type": "Feature",
+      "properties": { "name": "大理州", "code": "532900", "population": 3300000 },
+      "geometry": {
+        "type": "Polygon",
+        "coordinates": [[
+          [99.5, 26.5], [99.8, 26.3], [100.0, 26.2], [100.3, 26.0],
+          [100.5, 25.8], [100.4, 25.5], [100.3, 25.3], [100.1, 25.1],
+          [99.9, 25.0], [99.7, 25.1], [99.5, 25.3], [99.5, 26.5]
+        ]]
+      }
+    }
+  ]
+}

suites/test-windows/data/kunming.geojson

@@ -0,0 +1,18 @@
+{
+  "type": "FeatureCollection",
+  "features": [
+    {
+      "type": "Feature",
+      "properties": { "name": "昆明市", "code": "530100", "population": 8500000 },
+      "geometry": {
+        "type": "Polygon",
+        "coordinates": [[
+          [102.4, 25.7], [102.6, 25.6], [102.9, 25.5], [103.1, 25.4],
+          [103.4, 25.2], [103.3, 24.9], [103.2, 24.7], [103.0, 24.5],
+          [102.8, 24.4], [102.6, 24.5], [102.5, 24.7], [102.4, 24.9],
+          [102.4, 25.7]
+        ]]
+      }
+    }
+  ]
+}

suites/test-windows/data/yunnan.geojson

@@ -0,0 +1,19 @@
+{
+  "type": "FeatureCollection",
+  "features": [
+    {
+      "type": "Feature",
+      "properties": { "name": "云南省", "code": "530000" },
+      "geometry": {
+        "type": "Polygon",
+        "coordinates": [[
+          [97.5, 27.5], [98.5, 28.8], [100.0, 29.3], [101.5, 28.5],
+          [103.0, 28.0], [104.5, 27.5], [105.5, 26.5], [106.2, 25.5],
+          [106.0, 24.0], [105.5, 23.0], [104.5, 22.2], [103.5, 22.0],
+          [102.5, 21.5], [101.5, 21.1], [100.5, 21.8], [99.5, 22.5],
+          [98.5, 23.5], [97.8, 24.5], [97.5, 25.5], [97.5, 27.5]
+        ]]
+      }
+    }
+  ]
+}

suites/test-windows/scripts/arcpy_convert.py

@@ -0,0 +1,63 @@
+#!/usr/bin/env python
+"""
+Step 1: GeoJSON → SHP (arcpy)
+将省界和城市 GeoJSON 文件转换为 Shapefile
+使用 arcpy 的 JSON To Feature Class 工具
+"""
+import sys
+import json
+import os
+import arcpy
+
+# 允许覆写输出
+arcpy.env.overwriteOutput = True
+
+
+def main():
+    province_path = os.environ.get("PARAM_PROVINCE", "")
+    cities_param = os.environ.get("PARAM_CITIES", "")
+    output_dir = os.environ.get("PARAM_OUTPUT_DIR", r"C:\temp\output\shp")
+
+    if not province_path:
+        print json.dumps({"error": "缺少 province 参数", "success": False})
+        sys.exit(1)
+    if not cities_param:
+        print json.dumps({"error": "缺少 cities 参数", "success": False})
+        sys.exit(1)
+
+    if not os.path.isdir(output_dir):
+        os.makedirs(output_dir)
+
+    # 转换省界
+    print json.dumps({"msg": "转换省界: " + province_path})
+    province_name = os.path.splitext(os.path.basename(province_path))[0]
+    province_shp = os.path.join(output_dir, "province.shp")
+    # GeoJSON → Feature Class → Shapefile
+    arcpy.JSONToFeatures_conversion(province_path, province_shp)
+    print json.dumps({"msg": "省界已转为 SHP: " + province_shp})
+
+    # 转换每个城市
+    city_files = [c.strip() for c in cities_param.split(",") if c.strip()]
+    converted = []
+    for cf in city_files:
+        if not os.path.isfile(cf):
+            print json.dumps({"warn": "文件不存在，跳过: " + cf})
+            continue
+        print json.dumps({"msg": "转换城市: " + cf})
+        base = os.path.splitext(os.path.basename(cf))[0]
+        shp_path = os.path.join(output_dir, base + ".shp")
+        arcpy.JSONToFeatures_conversion(cf, shp_path)
+        converted.append(base)
+        print json.dumps({"msg": "已转换: " + cf + " -> " + shp_path})
+
+    result = {
+        "success": True,
+        "province_shp": province_shp,
+        "city_count": len(converted),
+        "cities": converted
+    }
+    print json.dumps(result)
+
+
+if __name__ == "__main__":
+    main()

suites/test-windows/scripts/arcpy_overlay.py

@@ -0,0 +1,119 @@
+#!/usr/bin/env python
+"""
+Step 2: 叠加分析 (arcpy)
+判断各城市是否在省界内，输出分析结果 JSON
+"""
+import sys
+import json
+import os
+import glob
+import arcpy
+
+arcpy.env.overwriteOutput = True
+
+
+def main():
+    province_shp = os.environ.get("PARAM_PROVINCE_SHP", "")
+    cities_dir = os.environ.get("PARAM_CITIES_DIR", r"C:\temp\output\shp")
+    output_dir = os.environ.get("PARAM_OUTPUT_DIR", r"C:\temp\output\result")
+
+    if not province_shp or not os.path.isfile(province_shp):
+        print json.dumps({"error": "省界 SHP 文件不存在: " + str(province_shp), "success": False})
+        sys.exit(1)
+
+    if not os.path.isdir(output_dir):
+        os.makedirs(output_dir)
+
+    # 查找所有城市 SHP
+    city_shp_files = glob.glob(os.path.join(cities_dir, "*.shp"))
+    city_shp_files = [f for f in city_shp_files
+                      if os.path.basename(f) != "province.shp"]
+
+    if not city_shp_files:
+        print json.dumps({"error": "未找到城市 SHP 文件", "success": False})
+        sys.exit(1)
+
+    # 创建省界图层
+    province_lyr = "province_layer"
+    arcpy.MakeFeatureLayer_management(province_shp, province_lyr)
+
+    results = []
+    desc = arcpy.Describe(province_shp)
+    sr = desc.spatialReference
+
+    for shp in city_shp_files:
+        city_name = os.path.splitext(os.path.basename(shp))[0]
+        print json.dumps({"msg": "分析城市: " + city_name})
+
+        # 创建城市图层
+        city_lyr = "city_layer_" + city_name
+        arcpy.MakeFeatureLayer_management(shp, city_lyr)
+
+        # 空间选择：城市中心点在省界内
+        # 先获取城市几何中心
+        city_centroid_shp = os.path.join(output_dir, city_name + "_centroid.shp")
+        arcpy.FeatureToPoint_management(shp, city_centroid_shp, "INSIDE")
+
+        centroid_lyr = "centroid_layer_" + city_name
+        arcpy.MakeFeatureLayer_management(city_centroid_shp, centroid_lyr)
+
+        # Select by location: 中心点在省界内
+        arcpy.SelectLayerByLocation_management(centroid_lyr, "WITHIN", province_lyr)
+        count = int(arcpy.GetCount_management(centroid_lyr).getOutput(0))
+        in_province = count > 0
+
+        # 获取属性
+        city_name_prop = city_name
+        city_code = ""
+        population = 0
+        try:
+            with arcpy.da.SearchCursor(shp, ["name", "code", "population"]) as cursor:
+                for row in cursor:
+                    if row[0]:
+                        city_name_prop = str(row[0])
+                    if row[1]:
+                        city_code = str(row[1])
+                    if row[2]:
+                        population = int(row[2])
+                    break
+        except Exception:
+            pass
+
+        status = u"通过 \u2705" if in_province else u"不通过 \u274c"
+
+        results.append({
+            "city": city_name,
+            "city_code": city_code,
+            "city_name": city_name_prop,
+            "population": population,
+            "in_province": in_province,
+            "intersects": in_province,
+            "status": status
+        })
+        print json.dumps({"msg": city_name + ": " + status})
+
+        # 清理
+        arcpy.Delete_management(city_lyr)
+        arcpy.Delete_management(centroid_lyr)
+        arcpy.Delete_management(city_centroid_shp)
+
+    arcpy.Delete_management(province_lyr)
+
+    # 输出 JSON
+    result_json = os.path.join(output_dir, "overlay_results.json")
+    with open(result_json, "w") as f:
+        json.dump(results, f, indent=2)
+
+    summary = {
+        "success": True,
+        "total_cities": len(results),
+        "in_province": sum(1 for r in results if r["in_province"]),
+        "not_in_province": sum(1 for r in results if not r["in_province"]),
+        "results": results,
+        "result_json": result_json
+    }
+    print json.dumps(summary)
+
+
+if __name__ == "__main__":
+    main()

suites/test-windows/scripts/excel.py

@@ -0,0 +1,90 @@
+#!/usr/bin/env python3
+"""
+Step 3: 输出 Excel
+将叠加分析结果写入 Excel 文件
+"""
+import sys
+import json
+import os
+from openpyxl import Workbook
+from openpyxl.styles import Font, Alignment, PatternFill
+
+
+def main():
+    result_dir = os.environ.get("PARAM_RESULT_DIR", "/tmp/output/result")
+    output_path = os.environ.get("PARAM_OUTPUT_PATH", "")
+
+    if not output_path:
+        print(json.dumps({"error": "缺少 output_path 参数", "success": False}))
+        sys.exit(1)
+
+    # 读取分析结果
+    result_json = os.path.join(result_dir, "overlay_results.json")
+    if not os.path.isfile(result_json):
+        print(json.dumps({"error": f"结果文件不存在: {result_json}", "success": False}))
+        sys.exit(1)
+
+    with open(result_json, "r", encoding="utf-8") as f:
+        results = json.load(f)
+
+    # 创建工作簿
+    wb = Workbook()
+    ws = wb.active
+    ws.title = "叠加分析结果"
+
+    # 标题样式
+    header_font = Font(bold=True, size=12, color="FFFFFF")
+    header_fill = PatternFill(start_color="4472C4", end_color="4472C4", fill_type="solid")
+    header_align = Alignment(horizontal="center", vertical="center")
+
+    # 表头
+    headers = ["城市", "城市代码", "城市名称", "人口", "在省内", "相交", "状态"]
+    for col, h in enumerate(headers, 1):
+        cell = ws.cell(row=1, column=col, value=h)
+        cell.font = header_font
+        cell.fill = header_fill
+        cell.alignment = header_align
+
+    # 数据行
+    pass_fill = PatternFill(start_color="E2EFDA", end_color="E2EFDA", fill_type="solid")
+    fail_fill = PatternFill(start_color="FCE4EC", end_color="FCE4EC", fill_type="solid")
+
+    for row_idx, r in enumerate(results, 2):
+        ws.cell(row=row_idx, column=1, value=r.get("city", ""))
+        ws.cell(row=row_idx, column=2, value=r.get("city_code", ""))
+        ws.cell(row=row_idx, column=3, value=r.get("city_name", ""))
+        ws.cell(row=row_idx, column=4, value=r.get("population", 0))
+        ws.cell(row=row_idx, column=5, value="是" if r.get("in_province") else "否")
+        ws.cell(row=row_idx, column=6, value="是" if r.get("intersects") else "否")
+        ws.cell(row=row_idx, column=7, value=r.get("status", ""))
+
+        # 条件高亮
+        fill = pass_fill if r.get("in_province") else fail_fill
+        for col in range(1, 8):
+            ws.cell(row=row_idx, column=col).fill = fill
+
+    # 调整列宽
+    ws.column_dimensions["A"].width = 15
+    ws.column_dimensions["B"].width = 12
+    ws.column_dimensions["C"].width = 15
+    ws.column_dimensions["D"].width = 12
+    ws.column_dimensions["E"].width = 10
+    ws.column_dimensions["F"].width = 10
+    ws.column_dimensions["G"].width = 15
+
+    # 确保输出目录存在
+    out_dir = os.path.dirname(output_path)
+    if out_dir:
+        os.makedirs(out_dir, exist_ok=True)
+
+    wb.save(output_path)
+    print(json.dumps({
+        "success": True,
+        "output_path": output_path,
+        "total": len(results),
+        "msg": f"Excel 已输出到: {output_path}"
+    }))
+
+
+if __name__ == "__main__":
+    main()

suites/test-windows/workflow.yaml

@@ -0,0 +1,51 @@
+name: 云南省界叠加分析（Windows 测试）
+description: 验证 GIS Actions 4.0 Windows 执行链路的测试套件。将示例 GeoJSON 转为 SHP → 叠加分析（arcpy）→ 输出 Excel
+version: 1.0.0
+author: SuiteForge
+platform: windows
+slug: test-yunnan-overlay-windows
+tags: [测试, 叠加分析, Windows, 云南省]
+category: 测试验证
+
+params:
+  province:
+    type: string
+    required: true
+    desc: 省界 GeoJSON 文件路径
+  cities:
+    type: string
+    required: true
+    desc: 待分析城市 GeoJSON 文件路径，多个文件用逗号分隔
+  output_path:
+    type: string
+    required: true
+    desc: 输出 Excel 文件路径（.xlsx）
+
+steps:
+  - id: geojson_to_shp
+    name: 转为 SHP
+    runtime: arcpy
+    script_id: arcpy_convert
+    params:
+      province: $params.province
+      cities: $params.cities
+      output_dir: /tmp/output/shp
+
+  - id: overlay
+    name: 叠加分析
+    runtime: arcpy
+    script_id: arcpy_overlay
+    depends_on: [geojson_to_shp]
+    params:
+      province_shp: /tmp/output/shp/province.shp
+      cities_dir: /tmp/output/shp
+      output_dir: /tmp/output/result
+
+  - id: export_excel
+    name: 输出 Excel
+    runtime: python3
+    script_id: excel
+    depends_on: [overlay]
+    params:
+      result_dir: /tmp/output/result
+      output_path: $params.output_path