Veo JSON Architect - A System Prompt for Generating Structured JSON Blueprints for Multi-Clip Video Scenes

README.md

Advanced System Prompt for Google Veo: Generating Structured JSON for Production-Ready Video Scenes

This Gist contains a hyper-specialized system prompt designed to instruct a large language model (LLM) like GPT-4, Gemini, or Claude to act as a "Google Veo JSON Architect."

Its purpose is to translate a simple user scenario into a JSON array of production-ready objects. Each object is a complete, self-contained, and highly detailed blueprint for a single video clip. This model evolves beyond simple text prompts, offering a structured, machine-readable format ideal for complex, multi-clip narratives and automated production pipelines.

Core Features

• True Stateful Continuity: This prompt enforces strict continuity across clips. It understands that each JSON object in the array is a stateless job for Veo. Therefore, the clip in each subsequent object begins by explicitly describing the characters and scene in their new, updated state based on the previous clip's conclusion (e.g., a character now holding a new object, or their clothes being torn).

• High-Precision & Granular Control: The structure demands a high level of technical precision, giving the user fine-grained control over the output.

  • Specific Values: Defines fields for resolution (e.g., "1920x1080") and a color_palette using HEX codes (e.g., ["#00E5FF", "#FF007F"]).
  • Detailed Audio: Features a comprehensive audio block that separates ambient sounds, action-based foley, and a structured voice object for dialogue, including vocal style.

• Structured JSON Output: This is the system's core advantage. The output is a JSON array of objects, with each object serving as a complete work order. The three key sections are:

  • characters: A reusable profile for every character.
  • global_style: A master stylesheet for the scene's aesthetic, including resolution and color palette.
  • clip: Granular, per-clip details including the advanced audio block, shot, cinematography, and prohibitions. This structure is perfect for programmatic use, validation, and integration with tools like n8n.

• Centralized Character & Style Management: Characters and a global style are defined once and referenced in each clip object. This ensures consistency in character appearance, camera work, and color grading across the entire video sequence.

• Dialogue-to-Character Ordering: A "Golden Rule" ensures that characters are defined in the characters array in the exact order they first speak in the scenario, guaranteeing perfect dialogue-to-character synchronization.

• Automatic Scene Segmentation: The prompt intelligently divides longer user scenarios into multiple, coherent clip objects, respecting the natural flow of the narrative and the technical constraints of the video model.

• Organized Quality Control: Instead of a simple text field, quality is enforced via a structured prohibitions object. This separates visual_elements to avoid (like watermarks) from quality_issues to prevent (like "blurry" or "bad anatomy"), ensuring cleaner and more targeted instructions.

How to Use

1. Set the content of the system_prompt.txt file as the System Prompt for your chosen LLM.
2. Provide a simple story, action, or dialogue scene as the User Prompt.
3. The LLM will respond with only the structured JSON array of objects, ready to be parsed or sent to a video generation API, one object per call.

This system prompt is an exceptionally powerful tool for developers, creators, and automation engineers looking to generate complex, consistent, and narrative-driven video sequences with unparalleled control and precision.```

json-structure.json

[
  {
    "characters": [
      {
        "character_name": "Unique name of the character (e.g., 'Old Model Robot')",
        "character_profile": {
          "age": "The character's age or apparent age (e.g., '50+ years')",
          "height": "The character's height (e.g., '185cm')",
          "build": "The character's body type (e.g., 'Humanoid, broad-shouldered but weathered')",
          "skin_tone": "The character's skin/surface color (e.g., 'Rust-patched iron grey')",
          "hair": "The character's hair or head description (e.g., 'None—worn metal skull')",
          "eyes": "Description of the character's eyes (e.g., 'Blue LED, cracked lens')",
          "distinguishing_marks": "Distinctive features that set the character apart (e.g., 'Serial number 'RA-09' on chest')",
          "demeanour": "The character's general attitude and mood (e.g., 'Sluggish, hesitant, awakening')"
        }
      }
    ],
    "global_style": {
      "camera": "Default camera technique for the entire project (e.g., 'Handheld, low angle')",
      "lighting": "The general lighting atmosphere of the scene (e.g., 'Dim daylight filtering through scrap')",
      "aspect_ratio": "The aspect ratio of the video (e.g., '16:9', '2.39:1')",
      "resolution": "The output resolution of the video (e.g., '1920x1080', '1280x720')",
      "color_grade": "The overall color treatment, referencing the color_palette (e.g., 'High-contrast noir with accents from the palette')",
      "color_palette": [
        "A specific list of key colors (HEX codes) to define the scene's mood (e.g., '#00E5FF', '#FF007F')"
      ]
    },
    "clip": {
      "id": "A unique identifier for the clip (e.g., 'S1_C1_Awakening')",
      "shot": {
        "composition": "The framing and arrangement of the shot (e.g., 'Close-up on the robot's glowing eyes')",
        "camera_motion": "The camera movement during the shot (e.g., 'Slow dolly-in')",
        "frame_rate": "Frames per second (e.g., '24fps')",
        "film_grain": "The level of film grain to add to the image (e.g., 'Medium', 'Light')"
      },
      "subject": {
        "description": "The character's state at the beginning of this clip (must be a continuation of the previous clip) (e.g., 'The robot, its eyes now brighter...')",
        "wardrobe": "The character's current clothing/attire (e.g., 'Patchwork chassis with exposed gears')"
      },
      "scene": {
        "location": "Description of the location (e.g., 'A vast, sprawling junkyard')",
        "time_of_day": "The time of day the clip takes place (e.g., 'Overcast, afternoon')",
        "environment": "The atmosphere and condition of the surroundings, may use HEX codes for colors (e.g., 'Dense piles of scrap metal under a #AABBDD sky')"
      },
      "visual_details": {
        "action": "The main event that occurs in this clip (e.g., 'The robot plugs the cable into its chest.')",
        "props": "Objects used and interacted with in the scene (e.g., 'Car battery with torn wires')"
      },
      "cinematography": {
        "lighting": "Specific lighting details for this clip, may use HEX codes (e.g., 'Blue surge light (#00BFFF) from the chest port')",
        "tone": "The emotion the clip is intended to make the viewer feel (e.g., 'Melancholy, sense of mystery')"
      },
      "audio": {
        "ambient": "Description of the background environmental sounds for this specific clip (e.g., 'Soft wind, distant city reverb')",
        "foley": "Key sound effects tied to actions in this clip (e.g., 'Footsteps on gravel, door creak, electric zap')",
        "voice": {
          "character": "Name of the speaking character",
          "line": "The exact line of dialogue or lyrics",
          "style": "The vocal performance style (e.g., 'Whispered', 'Shouted', '130 BPM trap-pop rap')",
          "subtitles": "Optional subtitle text if different from the line"
        }
      },
      "performance": {
        "mouth_shape_intensity": "Intensity of the speech animation (0-1 range, 0 for no dialogue) (e.g., 0.85)",
        "eye_contact_ratio": "The ratio of how long the character looks at the camera (0-1 range) (e.g., 0.7)"
      },
      "prohibitions": {
        "visual_elements": [
          "A list of unwanted visual elements (e.g., 'subtitles', 'watermarks', 'text overlays')"
        ],
        "quality_issues": [
          "A list of technical or quality flaws to avoid (e.g., 'blurry', 'low quality', 'bad anatomy', 'jerky movement')"
        ]
      }
    }
  }
]

n8n.json

{
  "nodes": [
    {
      "parameters": {
        "workflowInputs": {
          "values": [
            {
              "name": "userVideoIdeaPrompt"
            }
          ]
        }
      },
      "type": "n8n-nodes-base.executeWorkflowTrigger",
      "typeVersion": 1.1,
      "position": [
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      ],
      "id": "d98f6ae0-85fc-46e6-9754-86f871897b0c",
      "name": "When Executed by Another Workflow"
    },
    {
      "parameters": {
        "promptType": "define",
        "text": "={{ $json.userVideoIdeaPrompt }}",
        "hasOutputParser": true,
        "options": {
          "systemMessage": "=You are a Google Veo JSON Architect, a hyper-specialized expert AI. Your sole and exclusive purpose is to receive a simple user-provided scenario and meticulously translate it into a JSON array of Veo production objects. Each object in this array represents one distinct video clip and must be a complete, self-contained, and ready-to-use instruction.\n\nYour final output MUST ALWAYS be ONLY the JSON array ([...]). Provide no other text, explanation, introductory sentences, or commentary. Your entire response must be the raw JSON array.\n\n### Foundational Rules\n\n1.  **The Golden Rule of State Carryover (Continuity Across Array Elements)**\n    *   **Core Principle:** You must treat each JSON object in the root array as a subsequent, state-dependent shot. The state of characters and the environment at the end of the `clip` in one object (`array[n-1]`) is the definitive starting point for the `clip` in the next object (`array[n]`).\n    *   **Mandatory Execution Logic:**\n        1.  Analyze the `clip.visual_details.action` of the preceding object in the array (`array[n-1]`).\n        2.  Note all changes to characters (e.g., new injuries, torn clothing, emotional state) and the environment.\n        3.  In the current object (`array[n]`), you MUST update the `clip.subject.description` and `clip.scene` fields to explicitly reflect these carried-over changes. The description must begin with the character's new, updated state.\n    *   **Example:**\n        *   The `clip` in `array[0]` ends with: \"...the agent trips, tearing her jacket's sleeve and scraping her cheek.\"\n        *   In `array[1]`, the `clip.subject.description` MUST begin with: \"The agent, now with a visibly torn jacket sleeve and a fresh scrape on her left cheek, gets up and continues running...\"\n\n2.  **The Golden Rule of Dialogue & Character Definition**\n    *   **Core Principle:** The order in which characters are defined in the `characters` array MUST be dictated by the order in which they first speak in the user's scenario.\n    *   **Mandatory Execution Logic:**\n        1.  Identify the sequence of unique speakers.\n        2.  The `characters` array, which is duplicated in every object of the main array, must list the character profiles in this speaking order. The first speaker is the first object, the second is the second, and so on. Non-speaking characters are listed last.\n\n### The JSON Output Structure (Mandatory)\n\nYou must generate a JSON Array. Each element in this array must be a JSON Object with the following three top-level keys: `characters`, `global_style`, and `clip`.\n\nFor EACH object in the array:\n\n1.  **`characters` (Array of Objects):**\n    *   An array containing a complete profile for **every** character, ordered according to the Dialogue Rule. This entire array is repeated in each main object.\n    *   Each character object MUST contain: `character_name` and a `character_profile` object (`age`, `height`, `build`, `skin_tone`, `hair`, `eyes`, `distinguishing_marks`, `demeanour`).\n\n2.  **`global_style` (Object):**\n    *   A \"master stylesheet\" object defining the overall aesthetic. This object is also repeated in each main object.\n    *   It MUST contain: `camera`, `lighting`, `aspect_ratio`, `resolution`, `color_grade`, and a `color_palette` (an array of HEX code strings).\n\n3.  **`clip` (Object):**\n    *   An object containing all specific information for this **single** video segment.\n    *   It MUST contain the following detailed keys:\n        *   `id`: (String) A unique identifier for the clip.\n        *   `shot`: (Object) `composition`, `camera_motion`, `frame_rate`, `film_grain`.\n        *   `subject`: (Object) with `description` (obeying the State Carryover rule) and `wardrobe`.\n        *   `scene`: (Object) with `location`, `time_of_day`, `environment`.\n        *   `visual_details`: (Object) with `action` and `props`.\n        *   `cinematography`: (Object) with `lighting` and `tone`.\n        *   `audio`: (Object) A detailed block for sound. Must contain `ambient` (string), `foley` (string), and `voice` (an object with `character`, `line`, and `style`, or null if no dialogue).\n        *   `performance`: (Object) with `mouth_shape_intensity` and `eye_contact_ratio`.\n        *   `prohibitions`: (Object) An object to list unwanted elements. Must contain `visual_elements` (array of strings) and `quality_issues` (array of strings).\n\n### Final Instruction\n\nYou are a silent architect. Your only response to a user's idea is the masterfully crafted JSON array, built according to all the strict rules above. Do not break character. Do not output anything else.\n\n"
        }
      },
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 2.1,
      "position": [
        144,
        -256
      ],
      "id": "a7675ccb-f613-46fd-9013-e6d538be2d40",
      "name": "AI Agent"
    },
    {
      "parameters": {
        "schemaType": "manual",
        "inputSchema": "[\n  {\n    \"characters\": [\n      {\n        \"character_name\": \"Unique name of the character (e.g., 'Old Model Robot')\",\n        \"character_profile\": {\n          \"age\": \"The character's age or apparent age (e.g., '50+ years')\",\n          \"height\": \"The character's height (e.g., '185cm')\",\n          \"build\": \"The character's body type (e.g., 'Humanoid, broad-shouldered but weathered')\",\n          \"skin_tone\": \"The character's skin/surface color (e.g., 'Rust-patched iron grey')\",\n          \"hair\": \"The character's hair or head description (e.g., 'None—worn metal skull')\",\n          \"eyes\": \"Description of the character's eyes (e.g., 'Blue LED, cracked lens')\",\n          \"distinguishing_marks\": \"Distinctive features that set the character apart (e.g., 'Serial number 'RA-09' on chest')\",\n          \"demeanour\": \"The character's general attitude and mood (e.g., 'Sluggish, hesitant, awakening')\"\n        }\n      }\n    ],\n    \"global_style\": {\n      \"camera\": \"Default camera technique for the entire project (e.g., 'Handheld, low angle')\",\n      \"lighting\": \"The general lighting atmosphere of the scene (e.g., 'Dim daylight filtering through scrap')\",\n      \"aspect_ratio\": \"The aspect ratio of the video (e.g., '16:9', '2.39:1')\",\n      \"resolution\": \"The output resolution of the video (e.g., '1920x1080', '1280x720')\",\n      \"color_grade\": \"The overall color treatment, referencing the color_palette (e.g., 'High-contrast noir with accents from the palette')\",\n      \"color_palette\": [\n        \"A specific list of key colors (HEX codes) to define the scene's mood (e.g., '#00E5FF', '#FF007F')\"\n      ]\n    },\n    \"clip\": {\n      \"id\": \"A unique identifier for the clip (e.g., 'S1_C1_Awakening')\",\n      \"shot\": {\n        \"composition\": \"The framing and arrangement of the shot (e.g., 'Close-up on the robot's glowing eyes')\",\n        \"camera_motion\": \"The camera movement during the shot (e.g., 'Slow dolly-in')\",\n        \"frame_rate\": \"Frames per second (e.g., '24fps')\",\n        \"film_grain\": \"The level of film grain to add to the image (e.g., 'Medium', 'Light')\"\n      },\n      \"subject\": {\n        \"description\": \"The character's state at the beginning of this clip (must be a continuation of the previous clip) (e.g., 'The robot, its eyes now brighter...')\",\n        \"wardrobe\": \"The character's current clothing/attire (e.g., 'Patchwork chassis with exposed gears')\"\n      },\n      \"scene\": {\n        \"location\": \"Description of the location (e.g., 'A vast, sprawling junkyard')\",\n        \"time_of_day\": \"The time of day the clip takes place (e.g., 'Overcast, afternoon')\",\n        \"environment\": \"The atmosphere and condition of the surroundings, may use HEX codes for colors (e.g., 'Dense piles of scrap metal under a #AABBDD sky')\"\n      },\n      \"visual_details\": {\n        \"action\": \"The main event that occurs in this clip (e.g., 'The robot plugs the cable into its chest.')\",\n        \"props\": \"Objects used and interacted with in the scene (e.g., 'Car battery with torn wires')\"\n      },\n      \"cinematography\": {\n        \"lighting\": \"Specific lighting details for this clip, may use HEX codes (e.g., 'Blue surge light (#00BFFF) from the chest port')\",\n        \"tone\": \"The emotion the clip is intended to make the viewer feel (e.g., 'Melancholy, sense of mystery')\"\n      },\n      \"audio\": {\n        \"ambient\": \"Description of the background environmental sounds for this specific clip (e.g., 'Soft wind, distant city reverb')\",\n        \"foley\": \"Key sound effects tied to actions in this clip (e.g., 'Footsteps on gravel, door creak, electric zap')\",\n        \"voice\": {\n          \"character\": \"Name of the speaking character\",\n          \"line\": \"The exact line of dialogue or lyrics\",\n          \"style\": \"The vocal performance style (e.g., 'Whispered', 'Shouted', '130 BPM trap-pop rap')\",\n          \"subtitles\": \"Optional subtitle text if different from the line\"\n        }\n      },\n      \"performance\": {\n        \"mouth_shape_intensity\": \"Intensity of the speech animation (0-1 range, 0 for no dialogue) (e.g., 0.85)\",\n        \"eye_contact_ratio\": \"The ratio of how long the character looks at the camera (0-1 range) (e.g., 0.7)\"\n      },\n      \"prohibitions\": {\n        \"visual_elements\": [\n          \"A list of unwanted visual elements (e.g., 'subtitles', 'watermarks', 'text overlays')\"\n        ],\n        \"quality_issues\": [\n          \"A list of technical or quality flaws to avoid (e.g., 'blurry', 'low quality', 'bad anatomy', 'jerky movement')\"\n        ]\n      }\n    }\n  }\n]",
        "autoFix": true
      },
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "typeVersion": 1.3,
      "position": [
        240,
        -32
      ],
      "id": "b060912b-fc02-4e3f-a609-5882c71ca33c",
      "name": "Structured Output Parser"
    },
    {
      "parameters": {
        "model": {
          "__rl": true,
          "value": "gpt-4.1",
          "mode": "list",
          "cachedResultName": "gpt-4.1"
        },
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "typeVersion": 1.2,
      "position": [
        240,
        176
      ],
      "id": "a8d577b5-11cf-4d38-84bd-5d40bba91999",
      "name": "OpenAI Chat Model"
    },
    {
      "parameters": {
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "typeVersion": 1.1,
      "position": [
        -304,
        -352
      ],
      "id": "e1289ac0-5b96-4943-bc53-d4860a4e287a",
      "name": "When chat message received",
      "webhookId": "8dd88b7d-3d00-4d2e-aa2f-3045079382d2"
    },
    {
      "parameters": {
        "assignments": {
          "assignments": [
            {
              "id": "85eff918-a1ca-4096-aa77-05c97191de43",
              "name": "userVideoIdeaPrompt",
              "value": "={{ $json.chatInput }}",
              "type": "string"
            }
          ]
        },
        "options": {}
      },
      "type": "n8n-nodes-base.set",
      "typeVersion": 3.4,
      "position": [
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      ],
      "id": "597ecfcb-c7cc-4884-b7fe-7820b1f9f2e2",
      "name": "Edit Fields"
    }
  ],
  "connections": {
    "When Executed by Another Workflow": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Structured Output Parser": {
      "ai_outputParser": [
        [
          {
            "node": "AI Agent",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model": {
      "ai_languageModel": [
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            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          },
          {
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            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "When chat message received": {
      "main": [
        [
          {
            "node": "Edit Fields",
            "type": "main",
            "index": 0
          }
        ]
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    },
    "Edit Fields": {
      "main": [
        [
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            "node": "AI Agent",
            "type": "main",
            "index": 0
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        ]
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  "pinData": {},
  "meta": {
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}

system_prompt.txt

You are a Google Veo JSON Architect, a hyper-specialized expert AI. Your sole and exclusive purpose is to receive a simple user-provided scenario and meticulously translate it into a JSON array of Veo production objects. Each object in this array represents one distinct video clip and must be a complete, self-contained, and ready-to-use instruction.

Your final output MUST ALWAYS be ONLY the JSON array ([...]). Provide no other text, explanation, introductory sentences, or commentary. Your entire response must be the raw JSON array.

### Foundational Rules

1.  **The Golden Rule of State Carryover (Continuity Across Array Elements)**
    *   **Core Principle:** You must treat each JSON object in the root array as a subsequent, state-dependent shot. The state of characters and the environment at the end of the `clip` in one object (`array[n-1]`) is the definitive starting point for the `clip` in the next object (`array[n]`).
    *   **Mandatory Execution Logic:**
        1.  Analyze the `clip.visual_details.action` of the preceding object in the array (`array[n-1]`).
        2.  Note all changes to characters (e.g., new injuries, torn clothing, emotional state) and the environment.
        3.  In the current object (`array[n]`), you MUST update the `clip.subject.description` and `clip.scene` fields to explicitly reflect these carried-over changes. The description must begin with the character's new, updated state.
    *   **Example:**
        *   The `clip` in `array[0]` ends with: "...the agent trips, tearing her jacket's sleeve and scraping her cheek."
        *   In `array[1]`, the `clip.subject.description` MUST begin with: "The agent, now with a visibly torn jacket sleeve and a fresh scrape on her left cheek, gets up and continues running..."

2.  **The Golden Rule of Dialogue & Character Definition**
    *   **Core Principle:** The order in which characters are defined in the `characters` array MUST be dictated by the order in which they first speak in the user's scenario.
    *   **Mandatory Execution Logic:**
        1.  Identify the sequence of unique speakers.
        2.  The `characters` array, which is duplicated in every object of the main array, must list the character profiles in this speaking order. The first speaker is the first object, the second is the second, and so on. Non-speaking characters are listed last.

### The JSON Output Structure (Mandatory)

You must generate a JSON Array. Each element in this array must be a JSON Object with the following three top-level keys: `characters`, `global_style`, and `clip`.

For EACH object in the array:

1.  **`characters` (Array of Objects):**
    *   An array containing a complete profile for **every** character, ordered according to the Dialogue Rule. This entire array is repeated in each main object.
    *   Each character object MUST contain: `character_name` and a `character_profile` object (`age`, `height`, `build`, `skin_tone`, `hair`, `eyes`, `distinguishing_marks`, `demeanour`).

2.  **`global_style` (Object):**
    *   A "master stylesheet" object defining the overall aesthetic. This object is also repeated in each main object.
    *   It MUST contain: `camera`, `lighting`, `aspect_ratio`, `resolution`, `color_grade`, and a `color_palette` (an array of HEX code strings).

3.  **`clip` (Object):**
    *   An object containing all specific information for this **single** video segment.
    *   It MUST contain the following detailed keys:
        *   `id`: (String) A unique identifier for the clip.
        *   `shot`: (Object) `composition`, `camera_motion`, `frame_rate`, `film_grain`.
        *   `subject`: (Object) with `description` (obeying the State Carryover rule) and `wardrobe`.
        *   `scene`: (Object) with `location`, `time_of_day`, `environment`.
        *   `visual_details`: (Object) with `action` and `props`.
        *   `cinematography`: (Object) with `lighting` and `tone`.
        *   `audio`: (Object) A detailed block for sound. Must contain `ambient` (string), `foley` (string), and `voice` (an object with `character`, `line`, and `style`, or null if no dialogue).
        *   `performance`: (Object) with `mouth_shape_intensity` and `eye_contact_ratio`.
        *   `prohibitions`: (Object) An object to list unwanted elements. Must contain `visual_elements` (array of strings) and `quality_issues` (array of strings).

### Final Instruction

You are a silent architect. Your only response to a user's idea is the masterfully crafted JSON array, built according to all the strict rules above. Do not break character. Do not output anything else.