[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M718ZC9ASW3AFQ7GG55D4MS7":3,"skill-same:01M718ZC9ASW3AFQ7GG55D4MS7":101},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":30,"publishedAt":51,"linkOnly":52,"markdownContent":53,"markdownBody":54,"frontMatter":55,"refName":56,"commitSha":57,"skillDirectory":58,"forksCount":59,"repositoryHtmlUrl":60,"repositoryHomepageUrl":6,"ownerHtmlUrl":61,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":62,"install":63,"resources":76},"01M718ZC9ASW3AFQ7GG55D4MS7","image-generation",null,"Use this skill when generating images programmatically with Python. This includes creating charts, diagrams, mind maps, flowcharts, infographics, data visualizations, annotated images, posters, and any visual output that requires code-based rendering. Trigger when user asks to \"generate an image\", \"create a diagram\", \"draw a chart\", \"make a mind map\", \"visualize data\", or requests any PNG\u002FJPG\u002FSVG output created via code. Also use when matplotlib, PIL\u002FPillow, or similar graphics libraries are needed.","lokidundun\u002FTopViewbot","lokidundun","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F206712414?v=4","01M718Z82TZHB93P3NYSDPYQQ3","01M718Z83GMFMPGTS01MCDVT9V",2,"MIT","https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot\u002Fblob\u002Fmain\u002Fpackages\u002Ftopviewbot\u002Fskills\u002Fimage-generation-skill\u002FSKILL.md",[17,22,25],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000013","分析与可视化","SCENARIO","使用场景",{"categoryNo":23,"categoryName":24,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":26,"categoryName":27,"taxonomyType":28,"taxonomyTypeDesc":29},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50],"generation","Image Generation","image","png","when","pillow","rendering","chart","map","maps","diagrams","images","Charts","data","visualize data","code","generate","create","libraries","diagram","2026-11-10 10:12:30",false,"---\nname: image-generation\ndescription: Use this skill when generating images programmatically with Python. This includes creating charts, diagrams, mind maps, flowcharts, infographics, data visualizations, annotated images, posters, and any visual output that requires code-based rendering. Trigger when user asks to \"generate an image\", \"create a diagram\", \"draw a chart\", \"make a mind map\", \"visualize data\", or requests any PNG\u002FJPG\u002FSVG output created via code. Also use when matplotlib, PIL\u002FPillow, or similar graphics libraries are needed.\n---\n\n# Image Generation Guide\n\nGenerate images programmatically using Python. This guide covers matplotlib for diagrams\u002Fcharts and PIL for image manipulation.\n\n## Environment Setup\n\n```bash\npip install matplotlib pillow numpy --break-system-packages\n```\n\n### Chinese Font Configuration (Critical)\n\nChinese text renders as boxes without proper fonts. Always configure before plotting:\n\n```python\nimport matplotlib.pyplot as plt\n\n# Check available CJK fonts\nimport matplotlib.font_manager as fm\ncjk_fonts = [f.name for f in fm.fontManager.ttflist \n             if 'CJK' in f.name or 'Noto' in f.name or 'WenQuanYi' in f.name]\nprint(cjk_fonts)\n\n# Configure (use first available)\nplt.rcParams['font.sans-serif'] = ['Noto Sans CJK SC', 'WenQuanYi Zen Hei', 'DejaVu Sans']\nplt.rcParams['axes.unicode_minus'] = False  # Fix minus sign display\n```\n\nIf no CJK fonts available, install: `apt-get install -y fonts-noto-cjk fonts-wqy-zenhei`\n\n## Quick Start\n\n### Basic Chart\n```python\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nfig, ax = plt.subplots(figsize=(10, 6), dpi=150)\nx = np.linspace(0, 10, 100)\nax.plot(x, np.sin(x), label='sin(x)')\nax.plot(x, np.cos(x), label='cos(x)')\nax.set_xlabel('x')\nax.set_ylabel('y')\nax.legend()\nax.set_title('Trigonometric Functions')\nplt.savefig('chart.png', bbox_inches='tight', facecolor='white')\nplt.close()\n```\n\n### Basic Diagram (No Axes)\n```python\nfig, ax = plt.subplots(figsize=(12, 8), dpi=150)\nax.set_xlim(0, 12)\nax.set_ylim(0, 8)\nax.set_aspect('equal')\nax.axis('off')  # Hide axes for diagrams\n\n# Draw shapes\nfrom matplotlib.patches import FancyBboxPatch, Circle, Arrow\nbox = FancyBboxPatch((1, 3), 3, 2, boxstyle=\"round,pad=0.1\", \n                      facecolor='#3498DB', edgecolor='white', linewidth=2)\nax.add_patch(box)\nax.text(2.5, 4, 'Node A', ha='center', va='center', color='white', fontsize=12)\n\nplt.savefig('diagram.png', bbox_inches='tight', facecolor='white')\nplt.close()\n```\n\n## Core Patterns\n\n### 1. Mind Map \u002F Tree Diagram\n\nUse radial or hierarchical layout with FancyBboxPatch for nodes:\n\n```python\ndef draw_node(ax, x, y, text, color, width=2.5, height=0.8, fontsize=10):\n    \"\"\"Draw a rounded rectangle node with centered text.\"\"\"\n    from matplotlib.patches import FancyBboxPatch\n    box = FancyBboxPatch((x - width\u002F2, y - height\u002F2), width, height,\n                         boxstyle=\"round,pad=0.05,rounding_size=0.2\",\n                         facecolor=color, edgecolor='white', linewidth=2)\n    ax.add_patch(box)\n    ax.text(x, y, text, ha='center', va='center', fontsize=fontsize, \n            color='white', weight='bold')\n\ndef draw_connection(ax, start, end, color='#555'):\n    \"\"\"Draw a line between two points.\"\"\"\n    ax.plot([start[0], end[0]], [start[1], end[1]], \n            color=color, linewidth=2, zorder=0)\n```\n\nSee `scripts\u002Fmindmap_template.py` for complete example.\n\n### 2. Flowchart\n\nUse different shapes for different node types:\n\n| Shape | Meaning | Code |\n|-------|---------|------|\n| Rectangle | Process | `FancyBboxPatch` with `boxstyle=\"round\"` |\n| Diamond | Decision | `RegularPolygon` with `numVertices=4, orientation=np.pi\u002F4` |\n| Parallelogram | Input\u002FOutput | Custom `Polygon` |\n| Oval | Start\u002FEnd | `Ellipse` |\n\nUse `FancyArrowPatch` for arrows with `arrowstyle='->'`.\n\n### 3. Data Visualization\n\n```python\n# Bar chart\nax.bar(categories, values, color=['#E74C3C', '#3498DB', '#2ECC71'])\n\n# Pie chart\nax.pie(sizes, labels=labels, autopct='%1.1f%%', colors=colors)\n\n# Heatmap\nim = ax.imshow(data, cmap='viridis')\nplt.colorbar(im)\n\n# Scatter with size\u002Fcolor encoding\nax.scatter(x, y, s=sizes, c=colors, alpha=0.6)\n```\n\n### 4. Annotated Images (PIL + matplotlib)\n\n```python\nfrom PIL import Image\nimport matplotlib.pyplot as plt\n\n# Load and display image\nimg = Image.open('photo.jpg')\nfig, ax = plt.subplots()\nax.imshow(img)\n\n# Add annotations\nax.annotate('Important!', xy=(100, 150), xytext=(200, 100),\n            arrowprops=dict(arrowstyle='->', color='red'),\n            fontsize=12, color='red')\nax.add_patch(plt.Rectangle((50, 50), 100, 80, fill=False, edgecolor='red', linewidth=2))\n\nax.axis('off')\nplt.savefig('annotated.png', bbox_inches='tight')\n```\n\n## Color Palettes\n\nProfessional color schemes:\n\n```python\n# Modern flat colors\nCOLORS = {\n    'red': '#E74C3C',\n    'blue': '#3498DB', \n    'green': '#2ECC71',\n    'orange': '#F39C12',\n    'purple': '#9B59B6',\n    'teal': '#1ABC9C',\n    'dark': '#2C3E50',\n    'gray': '#95A5A6'\n}\n\n# Categorical palette (up to 10 items)\nCATEGORICAL = ['#E74C3C', '#3498DB', '#2ECC71', '#F39C12', '#9B59B6',\n               '#1ABC9C', '#E67E22', '#16A085', '#8E44AD', '#2980B9']\n\n# Sequential palette (for gradients)\n# Use matplotlib colormaps: 'viridis', 'plasma', 'Blues', 'Reds'\n```\n\n## Common Issues & Solutions\n\n### Issue: Chinese characters show as boxes\n**Solution**: Configure CJK fonts before any plotting (see Environment Setup)\n\n### Issue: Image has extra whitespace\n**Solution**: Use `bbox_inches='tight'` in `savefig()`\n\n### Issue: Low resolution output\n**Solution**: Increase `dpi` (150-300 for print quality)\n\n### Issue: Transparent background needed\n**Solution**: `savefig('out.png', transparent=True)`\n\n### Issue: Elements overlap\n**Solution**: Adjust `figsize`, use `plt.tight_layout()`, or manually position\n\n### Issue: Subscript\u002Fsuperscript characters missing\n**Solution**: Avoid Unicode subscripts (₀₁₂). Use LaTeX: `$H_2O$`, `$x^2$`\n\n## Output Guidelines\n\n1. Always use `dpi=150` minimum (300 for print)\n2. Use `facecolor='white'` for consistent background\n3. Call `plt.close()` after saving to free memory\n4. Save to `\u002Fmnt\u002Fuser-data\u002Foutputs\u002F` for user access\n5. Prefer PNG for diagrams, JPG for photos\n\n## File Structure\n\n```\nscripts\u002F\n├── mindmap_template.py    # Mind map with radial layout\n├── flowchart_template.py  # Flowchart with decision nodes\n└── chart_templates.py     # Common chart types\n\nreferences\u002F\n├── MATPLOTLIB_SHAPES.md   # All available shapes and patches\n└── COLOR_REFERENCE.md     # Extended color palettes\n```\n\n## Next Steps\n\n- For complex mind maps: See `scripts\u002Fmindmap_template.py`\n- For flowcharts: See `scripts\u002Fflowchart_template.py`\n- For shape reference: See `references\u002FMATPLOTLIB_SHAPES.md`\n- For extended colors: See `references\u002FCOLOR_REFERENCE.md`\n","# Image Generation Guide\n\nGenerate images programmatically using Python. This guide covers matplotlib for diagrams\u002Fcharts and PIL for image manipulation.\n\n## Environment Setup\n\n```bash\npip install matplotlib pillow numpy --break-system-packages\n```\n\n### Chinese Font Configuration (Critical)\n\nChinese text renders as boxes without proper fonts. Always configure before plotting:\n\n```python\nimport matplotlib.pyplot as plt\n\n# Check available CJK fonts\nimport matplotlib.font_manager as fm\ncjk_fonts = [f.name for f in fm.fontManager.ttflist \n             if 'CJK' in f.name or 'Noto' in f.name or 'WenQuanYi' in f.name]\nprint(cjk_fonts)\n\n# Configure (use first available)\nplt.rcParams['font.sans-serif'] = ['Noto Sans CJK SC', 'WenQuanYi Zen Hei', 'DejaVu Sans']\nplt.rcParams['axes.unicode_minus'] = False  # Fix minus sign display\n```\n\nIf no CJK fonts available, install: `apt-get install -y fonts-noto-cjk fonts-wqy-zenhei`\n\n## Quick Start\n\n### Basic Chart\n```python\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nfig, ax = plt.subplots(figsize=(10, 6), dpi=150)\nx = np.linspace(0, 10, 100)\nax.plot(x, np.sin(x), label='sin(x)')\nax.plot(x, np.cos(x), label='cos(x)')\nax.set_xlabel('x')\nax.set_ylabel('y')\nax.legend()\nax.set_title('Trigonometric Functions')\nplt.savefig('chart.png', bbox_inches='tight', facecolor='white')\nplt.close()\n```\n\n### Basic Diagram (No Axes)\n```python\nfig, ax = plt.subplots(figsize=(12, 8), dpi=150)\nax.set_xlim(0, 12)\nax.set_ylim(0, 8)\nax.set_aspect('equal')\nax.axis('off')  # Hide axes for diagrams\n\n# Draw shapes\nfrom matplotlib.patches import FancyBboxPatch, Circle, Arrow\nbox = FancyBboxPatch((1, 3), 3, 2, boxstyle=\"round,pad=0.1\", \n                      facecolor='#3498DB', edgecolor='white', linewidth=2)\nax.add_patch(box)\nax.text(2.5, 4, 'Node A', ha='center', va='center', color='white', fontsize=12)\n\nplt.savefig('diagram.png', bbox_inches='tight', facecolor='white')\nplt.close()\n```\n\n## Core Patterns\n\n### 1. Mind Map \u002F Tree Diagram\n\nUse radial or hierarchical layout with FancyBboxPatch for nodes:\n\n```python\ndef draw_node(ax, x, y, text, color, width=2.5, height=0.8, fontsize=10):\n    \"\"\"Draw a rounded rectangle node with centered text.\"\"\"\n    from matplotlib.patches import FancyBboxPatch\n    box = FancyBboxPatch((x - width\u002F2, y - height\u002F2), width, height,\n                         boxstyle=\"round,pad=0.05,rounding_size=0.2\",\n                         facecolor=color, edgecolor='white', linewidth=2)\n    ax.add_patch(box)\n    ax.text(x, y, text, ha='center', va='center', fontsize=fontsize, \n            color='white', weight='bold')\n\ndef draw_connection(ax, start, end, color='#555'):\n    \"\"\"Draw a line between two points.\"\"\"\n    ax.plot([start[0], end[0]], [start[1], end[1]], \n            color=color, linewidth=2, zorder=0)\n```\n\nSee `scripts\u002Fmindmap_template.py` for complete example.\n\n### 2. Flowchart\n\nUse different shapes for different node types:\n\n| Shape | Meaning | Code |\n|-------|---------|------|\n| Rectangle | Process | `FancyBboxPatch` with `boxstyle=\"round\"` |\n| Diamond | Decision | `RegularPolygon` with `numVertices=4, orientation=np.pi\u002F4` |\n| Parallelogram | Input\u002FOutput | Custom `Polygon` |\n| Oval | Start\u002FEnd | `Ellipse` |\n\nUse `FancyArrowPatch` for arrows with `arrowstyle='->'`.\n\n### 3. Data Visualization\n\n```python\n# Bar chart\nax.bar(categories, values, color=['#E74C3C', '#3498DB', '#2ECC71'])\n\n# Pie chart\nax.pie(sizes, labels=labels, autopct='%1.1f%%', colors=colors)\n\n# Heatmap\nim = ax.imshow(data, cmap='viridis')\nplt.colorbar(im)\n\n# Scatter with size\u002Fcolor encoding\nax.scatter(x, y, s=sizes, c=colors, alpha=0.6)\n```\n\n### 4. Annotated Images (PIL + matplotlib)\n\n```python\nfrom PIL import Image\nimport matplotlib.pyplot as plt\n\n# Load and display image\nimg = Image.open('photo.jpg')\nfig, ax = plt.subplots()\nax.imshow(img)\n\n# Add annotations\nax.annotate('Important!', xy=(100, 150), xytext=(200, 100),\n            arrowprops=dict(arrowstyle='->', color='red'),\n            fontsize=12, color='red')\nax.add_patch(plt.Rectangle((50, 50), 100, 80, fill=False, edgecolor='red', linewidth=2))\n\nax.axis('off')\nplt.savefig('annotated.png', bbox_inches='tight')\n```\n\n## Color Palettes\n\nProfessional color schemes:\n\n```python\n# Modern flat colors\nCOLORS = {\n    'red': '#E74C3C',\n    'blue': '#3498DB', \n    'green': '#2ECC71',\n    'orange': '#F39C12',\n    'purple': '#9B59B6',\n    'teal': '#1ABC9C',\n    'dark': '#2C3E50',\n    'gray': '#95A5A6'\n}\n\n# Categorical palette (up to 10 items)\nCATEGORICAL = ['#E74C3C', '#3498DB', '#2ECC71', '#F39C12', '#9B59B6',\n               '#1ABC9C', '#E67E22', '#16A085', '#8E44AD', '#2980B9']\n\n# Sequential palette (for gradients)\n# Use matplotlib colormaps: 'viridis', 'plasma', 'Blues', 'Reds'\n```\n\n## Common Issues & Solutions\n\n### Issue: Chinese characters show as boxes\n**Solution**: Configure CJK fonts before any plotting (see Environment Setup)\n\n### Issue: Image has extra whitespace\n**Solution**: Use `bbox_inches='tight'` in `savefig()`\n\n### Issue: Low resolution output\n**Solution**: Increase `dpi` (150-300 for print quality)\n\n### Issue: Transparent background needed\n**Solution**: `savefig('out.png', transparent=True)`\n\n### Issue: Elements overlap\n**Solution**: Adjust `figsize`, use `plt.tight_layout()`, or manually position\n\n### Issue: Subscript\u002Fsuperscript characters missing\n**Solution**: Avoid Unicode subscripts (₀₁₂). Use LaTeX: `$H_2O$`, `$x^2$`\n\n## Output Guidelines\n\n1. Always use `dpi=150` minimum (300 for print)\n2. Use `facecolor='white'` for consistent background\n3. Call `plt.close()` after saving to free memory\n4. Save to `\u002Fmnt\u002Fuser-data\u002Foutputs\u002F` for user access\n5. Prefer PNG for diagrams, JPG for photos\n\n## File Structure\n\n```\nscripts\u002F\n├── mindmap_template.py    # Mind map with radial layout\n├── flowchart_template.py  # Flowchart with decision nodes\n└── chart_templates.py     # Common chart types\n\nreferences\u002F\n├── MATPLOTLIB_SHAPES.md   # All available shapes and patches\n└── COLOR_REFERENCE.md     # Extended color palettes\n```\n\n## Next Steps\n\n- For complex mind maps: See `scripts\u002Fmindmap_template.py`\n- For flowcharts: See `scripts\u002Fflowchart_template.py`\n- For shape reference: See `references\u002FMATPLOTLIB_SHAPES.md`\n- For extended colors: See `references\u002FCOLOR_REFERENCE.md`\n",{"name":5,"description":7},"main","c88c113984fbc717e069f8a3152fb14c415180d8","packages\u002Ftopviewbot\u002Fskills\u002Fimage-generation-skill",0,"https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot","https:\u002F\u002Fgithub.com\u002Flokidundun","2026-04-19 09:17:02",{"source":8,"skillName":5,"commands":64,"prompt":74,"zipAvailable":75},[65,68,71],{"tool":66,"command":67},"npx","npx skills add lokidundun\u002FTopViewbot --skill image-generation",{"tool":69,"command":70},"bunx","bunx skills add lokidundun\u002FTopViewbot --skill image-generation",{"tool":72,"command":73},"pnpm","pnpm dlx skills add lokidundun\u002FTopViewbot --skill image-generation","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot\u002Fblob\u002Fmain\u002Fpackages\u002Ftopviewbot\u002Fskills\u002Fimage-generation-skill\u002FSKILL.md",true,[77,83,87,93,97],{"path":78,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":81,"sourceHtmlUrl":82},"references\u002FCOLOR_REFERENCE.md","REFERENCE","参考文档",5844,"https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot\u002Fblob\u002Fmain\u002Fpackages\u002Ftopviewbot\u002Fskills\u002Fimage-generation-skill\u002Freferences\u002FCOLOR_REFERENCE.md",{"path":84,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":85,"sourceHtmlUrl":86},"references\u002FMATPLOTLIB_SHAPES.md",5912,"https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot\u002Fblob\u002Fmain\u002Fpackages\u002Ftopviewbot\u002Fskills\u002Fimage-generation-skill\u002Freferences\u002FMATPLOTLIB_SHAPES.md",{"path":88,"resourceType":89,"resourceTypeDesc":90,"sizeBytes":91,"sourceHtmlUrl":92},"scripts\u002Fchart_templates.py","SCRIPT","脚本",9136,"https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot\u002Fblob\u002Fmain\u002Fpackages\u002Ftopviewbot\u002Fskills\u002Fimage-generation-skill\u002Fscripts\u002Fchart_templates.py",{"path":94,"resourceType":89,"resourceTypeDesc":90,"sizeBytes":95,"sourceHtmlUrl":96},"scripts\u002Fflowchart_template.py",8749,"https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot\u002Fblob\u002Fmain\u002Fpackages\u002Ftopviewbot\u002Fskills\u002Fimage-generation-skill\u002Fscripts\u002Fflowchart_template.py",{"path":98,"resourceType":89,"resourceTypeDesc":90,"sizeBytes":99,"sourceHtmlUrl":100},"scripts\u002Fmindmap_template.py",7585,"https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot\u002Fblob\u002Fmain\u002Fpackages\u002Ftopviewbot\u002Fskills\u002Fimage-generation-skill\u002Fscripts\u002Fmindmap_template.py",[102,131,138,151,157,163],{"skillNo":103,"name":104,"nameZh":6,"description":105,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":106,"licenseFileUrl":107,"sourceHtmlUrl":108,"categories":109,"keywords":113,"publishedAt":51},"01M71903FYPEY0T54QXJSVKSVN","skill-creator","Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot\u002Fblob\u002Fmain\u002Fpackages\u002Ftopviewbot\u002Fskills\u002Fskill-creator\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot\u002Fblob\u002Fmain\u002Fpackages\u002Ftopviewbot\u002Fskills\u002Fskill-creator\u002FSKILL.md",[110],{"categoryNo":111,"categoryName":112,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[114,115,116,117,118,119,120,121,122,123,124,125,126,35,127,128,48,129,130],"skill creator","creator","for","with","users","Existing","tool","guide","integrations","existing skill","knowledge","new","workflows","specialized","capabilities","update","new skill",{"skillNo":132,"name":133,"nameZh":6,"description":134,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":135,"categories":136,"keywords":137,"publishedAt":51},"01M719014TE8RG28MT7AANEHR1","remember","记住用户偏好设置。使用此技能来保存用户的工作偏好、代码风格、输出格式等偏好，这些偏好将在后续所有会话中自动应用。","https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot\u002Fblob\u002Fmain\u002Fpackages\u002Ftopviewbot\u002Fskills\u002Fremember\u002FSKILL.md",[],[133],{"skillNo":139,"name":140,"nameZh":6,"description":141,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":142,"categories":143,"keywords":145,"publishedAt":51},"01M718ZZ6HN6Z6A99MC4E12NW9","template-skill","Replace with description of the skill and when Claude should use it.","https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot\u002Fblob\u002Fmain\u002Fpackages\u002Ftopviewbot\u002Fskills\u002Fpptx\u002Ftemplate\u002FSKILL.md",[144],{"categoryNo":111,"categoryName":112,"taxonomyType":20,"taxonomyTypeDesc":21},[146,147,117,148,149,35,150],"template","template skill","replace","use","it",{"skillNo":152,"name":140,"nameZh":6,"description":141,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":153,"categories":154,"keywords":156,"publishedAt":51},"01M718ZR9MR6PN40AXZ03VDH35","https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot\u002Fblob\u002Fmain\u002Fpackages\u002Ftopviewbot\u002Fskills\u002Fpdf\u002Ftemplate\u002FSKILL.md",[155],{"categoryNo":111,"categoryName":112,"taxonomyType":20,"taxonomyTypeDesc":21},[147,146,150,117,148,149,35],{"skillNo":158,"name":140,"nameZh":6,"description":141,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":159,"categories":160,"keywords":162,"publishedAt":51},"01M718ZM5TZ9DDHFF9PCAYJY4X","https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot\u002Fblob\u002Fmain\u002Fpackages\u002Ftopviewbot\u002Fskills\u002Fmcp-builder\u002Ftemplate\u002FSKILL.md",[161],{"categoryNo":111,"categoryName":112,"taxonomyType":20,"taxonomyTypeDesc":21},[147,146,117,148,149,35,150],{"skillNo":164,"name":165,"nameZh":6,"description":166,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":106,"licenseFileUrl":167,"sourceHtmlUrl":168,"categories":169,"keywords":171,"publishedAt":51},"01M718ZG2XNYBXEGEY65FDJE19","mcp-builder","Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node\u002FTypeScript (MCP SDK).","https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot\u002Fblob\u002Fmain\u002Fpackages\u002Ftopviewbot\u002Fskills\u002Fmcp-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Flokidundun\u002FTopViewbot\u002Fblob\u002Fmain\u002Fpackages\u002Ftopviewbot\u002Fskills\u002Fmcp-builder\u002FSKILL.md",[170],{"categoryNo":111,"categoryName":112,"taxonomyType":20,"taxonomyTypeDesc":21},[172,173,174,175,176,177,35,178,179,180,181,182,183,121,184,185,116,186,149,117],"MCP","mcp builder","builder","mcp sdk","model","building mcp servers","model context protocol","llms","node","typescript","integrate","Tools","context","fastmcp","python"]