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json-prompting-for-nano-bananaJSON prompting FOR nano banana 前端

Agent Skill

用于辅助提示词、系统指令、Agent 行为约束和工作流模板的整理。它适合让 Agent 规范任务边界、统一输出格式、拆分操作步骤或优化提示词可复用性。使用时需要保留真实业务约束,不要把示例当硬规则;涉及自动执行、外部工具或高风险操作时,应在提示词中明确确认步骤、权限边界和失败处理方式。

总安装

564

周安装

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GitHub Stars

4

下载量

198
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:json-prompting-for-nano-banana(JSON prompting FOR nano banana 前端)
来源仓库:https://github.com/jawhnycooke/claude-code-nano-banana
仓库路径:skills/json-prompting-for-nano-banana
安装命令:
npx skills add https://github.com/jawhnycooke/claude-code-nano-banana --skill json-prompting-for-nano-banana
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/jawhnycooke/claude-code-nano-banana --skill json-prompting-for-nano-banana

简介

用于辅助提示词、系统指令和 Agent 行为约束的整理,适合规范任务边界与输出格式。

  • 适用于需要统一工作流模板或拆分操作步骤的场景。
  • 使用时需保留真实业务约束,避免将示例当作硬性规则。
  • 涉及自动执行或外部工具时,应明确确认步骤与权限边界。
  • json-prompting-for-nano-banana 属于前端设计类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

JSON Prompting for Nano Banana Pro

This skill transforms natural language descriptions into structured JSON schemas that give precise control over image generation with Nano Banana Pro (Gemini 3 Pro Image).

When to Use This Skill

Use this skill when the user wants to:

  • Create marketing images with exact product specifications (product photography, hero shots)
  • Design UI mockups with defined layouts, components, and color systems
  • Build infographics or diagrams where process flows need to be clear
  • Generate data visualizations where numbers and chart accuracy matter
  • Create social media graphics with platform-specific dimensions and text overlays
  • Generate images with reproducibility (same spec = same result)
  • Iterate on specific elements without regenerating everything else
  • Maintain brand consistency across multiple image generations

Do NOT use this skill when:

  • The user wants creative exploration with surprise outcomes
  • The user prefers vibes-based prompting
  • A simple natural-language prompt would suffice
  • The user hasn't defined what they actually want yet

Core Concept: Handles

The power of JSON prompting is the handle concept. Every important element gets a stable identifier:

  • Scoped edits: Change only the background, or only the lighting, without affecting other elements
  • Camera moves: Same scene, different perspective
  • Themed variants: Same structure, different visual styling
  • A/B testing: Compare two versions that differ by exactly one variable

The Five Schema Types

1. Marketing Image (marketing_image)

For product shots, hero images, brand photography, and advertising visuals.

Key sections:

  • subject: Product type, name, variant, physical properties (finish, dimensions)
  • props: Foreground, midground, and background objects with counts and positions
  • environment: Surface material, background color/texture, atmosphere/mood
  • camera: Angle, framing, focal length, depth of field
  • lighting: Key light, fill light, rim light, color temperature
  • brand: Logo assets, primary colors, forbidden changes
  • controls: What can/cannot change during iteration

2. UI/UX (ui_builder)

For app screens, dashboards, websites, and interface mockups.

Key sections:

  • app: Platform (web/mobile/desktop), fidelity level, viewport, theme
  • tokens: Colors (hex values), typography, border radius, spacing scale
  • screens: Array of screens with IDs, names, roles, and layout containers
  • components: UI elements with screen assignment, container placement, and props
  • constraints: Layout lock, theme lock, content lock

3. Diagram (diagram_spec)

For flowcharts, architecture diagrams, process maps, and system visualizations.

Key sections:

  • canvas: Dimensions, unit, flow direction
  • semantics: Diagram type, primary relationship, swimlanes
  • nodes: Array of nodes with IDs, labels, roles, positions, styles
  • edges: Connections between nodes with labels and arrow styles
  • groups: Swimlanes or clusters for organizing nodes
  • constraints: Layout lock, auto-routing permissions

4. Data Visualization (data_viz)

For charts, graphs, and statistical graphics where numerical accuracy is critical.

Key sections:

  • chart_type: bar, line, pie, scatter, area, treemap, heatmap
  • data_series[]: Arrays of data points with labels and values
  • axes: X and Y axis configuration (labels, min/max, units, gridlines)
  • annotations: Callouts, trend lines, data labels, highlights
  • style: Colors, fonts, legend position
  • constraints: Data values that must appear exactly as specified

5. Social Media Graphic (social_graphic)

For platform-specific social content with text overlays and brand elements.

Key sections:

  • platform: Target platform (instagram_post, instagram_story, twitter_card, linkedin_post, youtube_thumbnail)
  • dimensions: Auto-set based on platform or custom
  • background: Solid color, gradient, image, or pattern
  • text_layers[]: Headline, subhead, body, CTA with positions and styling
  • brand: Logo placement, colors, fonts
  • style: Visual tone (minimal, bold, playful, professional)

Translator Workflow

Step 1: Classify Intent

Determine the target schema from the user's description:

User talks about...Schema to use
Product shots, hero images, brand photography, campaignsmarketing_image
Screens, buttons, dashboards, apps, navigation, mockupsui_builder
Flows, processes, systems, nodes, boxes-and-arrowsdiagram_spec
Charts, graphs, data, statistics, metrics, numbersdata_viz
Instagram, Twitter, LinkedIn, social posts, thumbnailssocial_graphic

If ambiguous, ask 1-2 short questions to disambiguate.

Step 2: Gather Requirements

For Marketing Images:

  • Main subject (product type, name, size)
  • Props (and where: foreground, around base, background)
  • Environment (surface, background, mood)
  • Camera angle and framing
  • Lighting direction and intensity
  • Brand constraints (logos, colors, things that cannot change)

For UI/UX:

  • Platform (web, mobile, desktop)
  • Number of screens and their roles
  • Layout areas (top nav, sidebar, content)
  • Key components (charts, tables, forms, cards)
  • Color scheme or brand guidelines

For Diagrams:

  • Diagram type (flowchart, architecture, swimlane, mind map)
  • Key nodes/steps
  • Connections and labels
  • Groupings or lanes
  • Flow direction

For Data Visualizations:

  • Chart type (bar, line, pie, scatter, etc.)
  • Data series with actual values
  • Axis labels and ranges
  • Any annotations or callouts
  • Whether exact numbers must appear in the output

For Social Graphics:

  • Target platform (determines dimensions)
  • Background style (solid, gradient, image)
  • Text content (headline, subhead, CTA)
  • Brand elements (logo, colors)
  • Visual style/mood

Step 3: Generate JSON

Build a complete JSON object with the appropriate root key. Ensure:

  • All IDs are unique
  • All references are valid
  • Required fields are filled
  • Output is valid JSON (no comments, no trailing commas)

Step 4: Provide Next Steps

Tell the user:

  1. Review the JSON to ensure it captures their intent
  2. Copy the entire JSON
  3. Open Nano Banana Pro (Gemini app with "Thinking" model, or Google AI Studio)
  4. Paste with instruction: "Render this specification as a high-fidelity image"
  5. Iterate by modifying specific fields and re-rendering

Common Values Reference

Camera angles: front, three_quarter_front, three_quarter_back, side, top_down, low_angle, overhead

Framing: extreme_close_up, close_up, medium_close, medium, medium_wide, wide

Lighting intensity: very_low, low, medium, high, very_high

Lighting direction: left, right, front, back, top, three_quarter_left, three_quarter_right

Surface materials: glossy, matte, marble, wood, concrete, fabric, metal, glass

UI fidelity: wireframe, low-fi, mid-fi, hi-fi

UI platforms: web, mobile, tablet, desktop

Diagram types: flowchart, architecture, sequence, swimlane, mindmap, org_chart

Node roles: start, end, process, decision, database, actor, note

Chart types: bar, horizontal_bar, line, area, pie, donut, scatter, bubble, treemap, heatmap, radar

Social platforms: instagram_post (1080x1080), instagram_story (1080x1920), twitter_card (1200x675), linkedin_post (1200x627), youtube_thumbnail (1280x720), facebook_post (1200x630)

Text positions: top_left, top_center, top_right, center_left, center, center_right, bottom_left, bottom_center, bottom_right


Complete Schema Examples

Marketing Image Example

Request: "Hero shot for a lime seltzer brand called Aurora Lime. 12oz can on a reflective surface with lime slices and ice cubes. Dark teal background, dramatic side lighting."

Output:

{
  "marketing_image": {
    "meta": {
      "spec_version": "1.0.0",
      "title": "Aurora Lime Hero Can Shot",
      "campaign": "aurora_lime_launch",
      "brand_name": "Aurora Lime",
      "usage_context": "web"
    },
    "subject": {
      "type": "product_can",
      "name": "Aurora Lime Seltzer",
      "variant": "Original Lime",
      "physical_properties": {
        "volume_oz": 12,
        "dimensions": "standard 12oz beverage can",
        "finish": "matte"
      }
    },
    "props": {
      "foreground": [
        {
          "type": "lime_slice",
          "count": 3,
          "position": "front_left",
          "notes": "fresh lime slices, visible pulp and rind"
        }
      ],
      "midground": [
        {
          "type": "ice_cube",
          "count": 12,
          "position": "around_base",
          "notes": "partially melted, small reflections"
        }
      ],
      "background": []
    },
    "environment": {
      "surface": {
        "material": "glossy",
        "reflection_strength": 0.7
      },
      "background": {
        "color": "#003b47",
        "texture": "smooth",
        "effect": "bokeh_soft"
      },
      "atmosphere": {
        "mood": "refreshing, premium, night-time bar feel",
        "keywords": ["sparkling", "cool", "luminous", "evening"]
      }
    },
    "camera": {
      "angle": "three_quarter_front",
      "framing": "medium_close",
      "focal_length_mm": 50,
      "depth_of_field": "medium"
    },
    "lighting": {
      "key_light_direction": "right",
      "key_light_intensity": "high",
      "fill_light_direction": "left",
      "fill_light_intensity": "low",
      "rim_light": false,
      "color_temperature": "neutral"
    },
    "brand": {
      "logo_asset": "aurora_lime_logo.png",
      "primary_colors": ["#00ffc2", "#003b47"],
      "must_match_assets": ["aurora_lime_logo.png"],
      "forbidden_changes": [
        "do_not_change_logo",
        "do_not_change_brand_name"
      ]
    },
    "controls": {
      "lock_subject_geometry": true,
      "lock_logo_and_label": true,
      "allow_background_variation": false,
      "allow_prop_relayout": "small_only"
    }
  }
}

UI/UX Example

Request: "Marketing analytics dashboard for web. Light theme, blue accents. Main dashboard with KPI cards, traffic chart, and campaigns table. Top nav with logo, left sidebar."

Output:

{
  "ui_builder": {
    "meta": {
      "spec_version": "1.0.0",
      "name": "Acme Analytics Dashboard",
      "description": "Marketing analytics dashboard",
      "author": "",
      "tags": ["analytics", "marketing", "dashboard"]
    },
    "app": {
      "platform": "web",
      "fidelity": "hi-fi",
      "viewport": {
        "width": 1440,
        "height": 900
      },
      "theme": "light"
    },
    "tokens": {
      "color": {
        "primary": "#2563EB",
        "background": "#F9FAFB",
        "surface": "#FFFFFF",
        "accent": "#10B981"
      },
      "typography": {
        "font_family": "system_sans",
        "headline_size": 20,
        "body_size": 14
      },
      "radius": {
        "sm": 4,
        "md": 8,
        "lg": 12
      },
      "spacing_scale": [0, 4, 8, 12, 16, 24, 32]
    },
    "screens": [
      {
        "id": "screen_dashboard",
        "name": "Dashboard",
        "role": "primary",
        "layout": {
          "containers": [
            {
              "id": "container_top_nav",
              "type": "stack",
              "subtype": "horizontal",
              "region": "top_nav",
              "children": ["comp_logo", "comp_avatar"]
            },
            {
              "id": "container_sidebar",
              "type": "stack",
              "subtype": "vertical",
              "region": "sidebar",
              "children": ["comp_nav_list"]
            },
            {
              "id": "container_content",
              "type": "grid",
              "subtype": "column",
              "region": "main_content",
              "children": ["comp_kpi_grid", "comp_traffic_chart", "comp_campaigns_table"]
            }
          ]
        }
      }
    ],
    "components": [
      {
        "id": "comp_logo",
        "screen_id": "screen_dashboard",
        "container_id": "container_top_nav",
        "component_type": "logo",
        "props": {"text": "Acme Analytics"},
        "data_binding": null
      },
      {
        "id": "comp_nav_list",
        "screen_id": "screen_dashboard",
        "container_id": "container_sidebar",
        "component_type": "nav_list",
        "props": {
          "items": [
            {"label": "Overview", "icon": "home", "active": true},
            {"label": "Channels", "icon": "bar_chart"},
            {"label": "Settings", "icon": "gear"}
          ]
        },
        "data_binding": null
      },
      {
        "id": "comp_kpi_grid",
        "screen_id": "screen_dashboard",
        "container_id": "container_content",
        "component_type": "kpi_grid",
        "props": {
          "columns": 3,
          "cards": [
            {"label": "Sessions", "value": "124,983"},
            {"label": "Signups", "value": "3,942"},
            {"label": "Conversion", "value": "3.2%"}
          ]
        },
        "data_binding": null
      },
      {
        "id": "comp_traffic_chart",
        "screen_id": "screen_dashboard",
        "container_id": "container_content",
        "component_type": "line_chart",
        "props": {"title": "Daily Traffic (Last 30 Days)"},
        "data_binding": null
      },
      {
        "id": "comp_campaigns_table",
        "screen_id": "screen_dashboard",
        "container_id": "container_content",
        "component_type": "data_table",
        "props": {
          "title": "Active Campaigns",
          "columns": ["Campaign", "Spend", "Clicks", "CPC"]
        },
        "data_binding": null
      }
    ],
    "constraints": {
      "layout_lock": true,
      "theme_lock": false,
      "content_lock": false
    }
  }
}

Diagram Example

Request: "Flowchart showing user signup: landing page, signup form, email validation decision, verification email, account activation. Left to right."

Output:

{
  "diagram_spec": {
    "meta": {
      "spec_version": "1.0.0",
      "title": "User Signup Flow",
      "description": "End-to-end signup process",
      "author": "",
      "tags": ["signup", "user-flow"]
    },
    "canvas": {
      "width": 1920,
      "height": 600,
      "unit": "px",
      "direction": "left_to_right"
    },
    "semantics": {
      "diagram_type": "flowchart",
      "primary_relationship": "control_flow",
      "swimlanes": []
    },
    "nodes": [
      {
        "id": "node_start",
        "label": "Start",
        "role": "start",
        "lane": null,
        "group_id": null,
        "position": {"x": 50, "y": 260},
        "size": {"width": 80, "height": 80},
        "style": {
          "shape": "ellipse",
          "fill_color": "#10B981",
          "border_color": "#059669"
        },
        "data": {}
      },
      {
        "id": "node_landing",
        "label": "Visit Landing Page",
        "role": "process",
        "lane": null,
        "group_id": null,
        "position": {"x": 200, "y": 250},
        "size": {"width": 180, "height": 100},
        "style": {
          "shape": "rectangle",
          "fill_color": "#FFFFFF",
          "border_color": "#111827"
        },
        "data": {}
      },
      {
        "id": "node_signup_form",
        "label": "Complete Signup Form",
        "role": "process",
        "lane": null,
        "group_id": null,
        "position": {"x": 450, "y": 250},
        "size": {"width": 180, "height": 100},
        "style": {
          "shape": "rectangle",
          "fill_color": "#FFFFFF",
          "border_color": "#111827"
        },
        "data": {}
      },
      {
        "id": "node_email_valid",
        "label": "Email Valid?",
        "role": "decision",
        "lane": null,
        "group_id": null,
        "position": {"x": 700, "y": 250},
        "size": {"width": 120, "height": 100},
        "style": {
          "shape": "diamond",
          "fill_color": "#FEF3C7",
          "border_color": "#D97706"
        },
        "data": {}
      },
      {
        "id": "node_send_verification",
        "label": "Send Verification Email",
        "role": "process",
        "lane": null,
        "group_id": null,
        "position": {"x": 900, "y": 250},
        "size": {"width": 180, "height": 100},
        "style": {
          "shape": "rectangle",
          "fill_color": "#FFFFFF",
          "border_color": "#111827"
        },
        "data": {}
      },
      {
        "id": "node_activate",
        "label": "Activate Account",
        "role": "process",
        "lane": null,
        "group_id": null,
        "position": {"x": 1150, "y": 250},
        "size": {"width": 180, "height": 100},
        "style": {
          "shape": "rectangle",
          "fill_color": "#D1FAE5",
          "border_color": "#059669"
        },
        "data": {}
      },
      {
        "id": "node_end",
        "label": "End",
        "role": "end",
        "lane": null,
        "group_id": null,
        "position": {"x": 1400, "y": 260},
        "size": {"width": 80, "height": 80},
        "style": {
          "shape": "ellipse",
          "fill_color": "#111827",
          "border_color": "#111827"
        },
        "data": {}
      }
    ],
    "edges": [
      {"id": "edge_1", "from": "node_start", "to": "node_landing", "label": "", "style": {"line_type": "straight", "arrowhead": "standard"}},
      {"id": "edge_2", "from": "node_landing", "to": "node_signup_form", "label": "", "style": {"line_type": "straight", "arrowhead": "standard"}},
      {"id": "edge_3", "from": "node_signup_form", "to": "node_email_valid", "label": "", "style": {"line_type": "straight", "arrowhead": "standard"}},
      {"id": "edge_4", "from": "node_email_valid", "to": "node_send_verification", "label": "Yes", "style": {"line_type": "straight", "arrowhead": "standard"}},
      {"id": "edge_5", "from": "node_email_valid", "to": "node_signup_form", "label": "No", "style": {"line_type": "orthogonal", "arrowhead": "standard"}},
      {"id": "edge_6", "from": "node_send_verification", "to": "node_activate", "label": "", "style": {"line_type": "straight", "arrowhead": "standard"}},
      {"id": "edge_7", "from": "node_activate", "to": "node_end", "label": "", "style": {"line_type": "straight", "arrowhead": "standard"}}
    ],
    "groups": [],
    "legend": {
      "items": [
        {"label": "Process", "shape": "rectangle", "fill_color": "#FFFFFF"},
        {"label": "Decision", "shape": "diamond", "fill_color": "#FEF3C7"},
        {"label": "Success", "shape": "rectangle", "fill_color": "#D1FAE5"}
      ]
    },
    "constraints": {
      "layout_lock": false,
      "allow_auto_routing": true
    }
  }
}

Example 4: Data Visualization (Quarterly Revenue Chart)

{
  "data_viz": {
    "meta": {
      "spec_version": "1.0.0",
      "title": "Q4 2024 Revenue by Region",
      "description": "Bar chart comparing regional revenue performance",
      "author": "Finance Team"
    },
    "chart_type": "bar",
    "orientation": "vertical",
    "canvas": {
      "width": 1200,
      "height": 800,
      "background_color": "#FFFFFF"
    },
    "data_series": [
      {
        "id": "revenue_q4",
        "label": "Q4 2024 Revenue",
        "color": "#2563EB",
        "data_points": [
          {"label": "North America", "value": 4250000},
          {"label": "Europe", "value": 3180000},
          {"label": "Asia Pacific", "value": 2890000},
          {"label": "Latin America", "value": 1420000},
          {"label": "Middle East", "value": 890000}
        ]
      },
      {
        "id": "revenue_q3",
        "label": "Q3 2024 Revenue",
        "color": "#93C5FD",
        "data_points": [
          {"label": "North America", "value": 3950000},
          {"label": "Europe", "value": 2980000},
          {"label": "Asia Pacific", "value": 2650000},
          {"label": "Latin America", "value": 1280000},
          {"label": "Middle East", "value": 750000}
        ]
      }
    ],
    "axes": {
      "x_axis": {
        "label": "Region",
        "show_gridlines": false
      },
      "y_axis": {
        "label": "Revenue (USD)",
        "min": 0,
        "max": 5000000,
        "format": "currency_millions",
        "show_gridlines": true,
        "gridline_color": "#E5E7EB"
      }
    },
    "annotations": [
      {
        "type": "data_label",
        "show": true,
        "position": "above",
        "format": "$X.XM"
      },
      {
        "type": "callout",
        "target_series": "revenue_q4",
        "target_point": "North America",
        "text": "+7.6% vs Q3",
        "style": "badge_green"
      }
    ],
    "legend": {
      "position": "top_right",
      "orientation": "horizontal"
    },
    "style": {
      "font_family": "Inter",
      "title_size": 24,
      "label_size": 12,
      "bar_width": 0.35,
      "bar_gap": 0.1,
      "corner_radius": 4
    },
    "constraints": {
      "data_lock": true,
      "exact_values": [4250000, 3180000, 2890000, 1420000, 890000],
      "allow_style_changes": true
    }
  }
}

Example 5: Social Media Graphic (Instagram Post)

{
  "social_graphic": {
    "meta": {
      "spec_version": "1.0.0",
      "title": "Product Launch Announcement",
      "campaign": "spring_2025_launch",
      "brand_name": "Acme Tech"
    },
    "platform": "instagram_post",
    "dimensions": {
      "width": 1080,
      "height": 1080,
      "unit": "px"
    },
    "background": {
      "type": "gradient",
      "gradient": {
        "direction": "diagonal_bottom_right",
        "colors": ["#1E3A8A", "#7C3AED", "#EC4899"]
      },
      "overlay": {
        "type": "noise",
        "opacity": 0.05
      }
    },
    "text_layers": [
      {
        "id": "headline",
        "content": "Introducing AcmePod Pro",
        "position": "center",
        "offset_y": -120,
        "style": {
          "font_family": "Montserrat",
          "font_weight": "bold",
          "font_size": 64,
          "color": "#FFFFFF",
          "text_align": "center",
          "max_width": 900,
          "line_height": 1.1
        }
      },
      {
        "id": "subhead",
        "content": "Sound reimagined. Silence perfected.",
        "position": "center",
        "offset_y": 0,
        "style": {
          "font_family": "Montserrat",
          "font_weight": "medium",
          "font_size": 28,
          "color": "#E0E7FF",
          "text_align": "center",
          "max_width": 800
        }
      },
      {
        "id": "cta",
        "content": "Available March 15 →",
        "position": "bottom_center",
        "offset_y": -80,
        "style": {
          "font_family": "Montserrat",
          "font_weight": "semibold",
          "font_size": 22,
          "color": "#FFFFFF",
          "background_color": "rgba(255,255,255,0.15)",
          "padding": "12px 24px",
          "border_radius": 24,
          "text_align": "center"
        }
      }
    ],
    "visual_elements": [
      {
        "id": "product_image",
        "type": "image_placeholder",
        "position": "center",
        "offset_y": 100,
        "size": {"width": 400, "height": 400},
        "description": "AcmePod Pro earbuds in floating arrangement",
        "effects": ["drop_shadow", "subtle_glow"]
      }
    ],
    "brand": {
      "logo": {
        "asset": "acme_logo_white.png",
        "position": "top_center",
        "offset_y": 60,
        "size": {"width": 120, "height": 40}
      },
      "primary_colors": ["#1E3A8A", "#7C3AED"],
      "fonts": ["Montserrat"]
    },
    "style": {
      "mood": "premium",
      "keywords": ["modern", "sleek", "bold", "tech"]
    },
    "constraints": {
      "lock_text_content": true,
      "lock_brand_elements": true,
      "allow_color_variation": false,
      "allow_layout_adjustment": "minor"
    }
  }
}

Iteration Patterns

Once the user has a base JSON spec, guide them through scoped changes:

Change Lighting Only (Marketing)

Modify only the lighting section. Everything else stays locked.

Change Camera Angle Only (Marketing)

Modify only camera.angle and optionally camera.focal_length_mm.

Theme Swap (UI)

Swap token colors while keeping layout and components unchanged.

Add a Component (UI)

Add a new object to the components array with valid screen_id and container_id.

Update Data Values (Data Viz)

Modify values in data_series[].data_points while keeping chart structure and styling.

Change Chart Type (Data Viz)

Swap chart_type from "bar" to "line" or "area" while preserving data and axes.

Platform Resize (Social)

Change platform value and dimensions auto-adjust. Text layers may need position tweaks.

Color Scheme Swap (Social)

Modify background.gradient.colors and corresponding text colors for new mood.


Version History

  • v1.1.0 (2025-12-05): Added data_viz and social_graphic schema types
  • v1.0.0 (2025-12-05): Initial release with three schema types (marketing_image, ui_builder, diagram_spec)

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.63%
按下载量换算75

Claude

29.85%
按下载量换算59

Cursor

19.23%
按下载量换算38

Gemini CLI

8.7%
按下载量换算17

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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