director

Director — Story-to-Video Production Pipeline

Overview

The Director skill orchestrates a complete short film production from a text story. It breaks the story into scenes, generates start/end frames for each, creates video clips from frame pairs, and concatenates everything into a final video.

Pipeline: Story Planning → Z-Image Hero + Character Refs → Qwen Edit Chain (all frames) → WAN 2.2 FLF Video Clips → ffmpeg Concatenation

Key architectural decisions:

• 1 hero frame + edit chain for character consistency (NEVER independent Z-Image per scene)
• Inter-scene frame continuity: Scene N's end frame IS Scene N+1's start frame (same image file, no edit gap)
• Character reference images fed into Qwen Edit's extra image slots
• State file persists to disk for context compaction survival
• Each scene is independently retryable without affecting others
• clear_vram between every model family switch

CRITICAL: Inspect modes + verify every output

This pipeline drives the user's live canvas across many stages, so two habits are non-negotiable:

• Inspect node modes before each render. After loading any pack/template/subgraph and before panel_run, check each node's mode (panel_graph_outline marks [bypass]/[mute]; panel_query_graph detail rows carry it). A bypass node is skipped (passes input through); a mute node and everything downstream don't execute. If the path/branch/switch you need is bypassed or muted, enable it with panel_set_node_mode (set the wanted node active, the unwanted one bypass/mute). Never assume a switch or route is already active.
• Verify the output matches before moving on. Every Phase-N render is a gate: actually LOOK at the produced frame/clip (view it) and confirm it matches the intent BEFORE advancing or reporting progress. If it's wrong, diagnose (wrong prompt path? a bypassed/muted builder or switch? wrong widget? wrong ref image?), fix, and rerun. Do NOT declare a phase done or report progress you haven't verified.
• Confirm VIDEO renders via the filesystem, not /history. For a VHS_VideoCombine / LTX / WAN clip, do NOT rely on get_history / queue (action:"status") to confirm it exists — VHS-style video nodes write the .mp4 but frequently do NOT register an output in ComfyUI's /history (prompt shows done, empty outputs, no error). Confirm the file with list_output_images (now lists videos too, tagged kind: "video") by filename_prefix + fresh mtime, then chain it forward with stage_output_as_input.
• Bypass completed stages before queuing the next one. If you build the multi-stage pipeline on ONE canvas (e.g. Krea2 → LTX → WAN) rather than running each phase in isolation, once a stage has run and its output is captured/staged, panel_set_node_mode(mode:"bypass") that stage's nodes BEFORE you panel_run the next stage — otherwise panel_run re-executes the whole graph and you pay for / wait on already-finished work (a real, costly failure mode). Keep only the active stage live; feed the prior output forward with stage_output_as_input (bypass the producer, feed its captured output to the consumer's loader).

CRITICAL: Character Consistency

Independent Z-Image generations per scene produce different-looking characters. This was the #1 problem discovered during testing. The solution:

1. Generate ONE hero frame with Z-Image — establishes the main character, setting, and lighting
2. Generate character reference images — close-up portraits of each character, key props, and the background
3. ALL other scene frames are created via Qwen Edit chain from the hero, with character refs in extra image slots
4. This ensures the same face, clothing, and environment across every frame

8-Phase Pipeline

Phase 1: Story Planning       → Break story into scenes (Claude reasoning, no ComfyUI)
Phase 2: Hero + Refs          → Z-Image: 1 hero frame + character ref portraits + background ref
Phase 3: Hero Review          → Visual verify hero and refs, user approves
Phase 4: Edit Chain           → Qwen Edit: chain ALL scene frames from hero (with char refs in slots 2-3)
Phase 5: Frame Review         → Visual verify all frames, approve/reject/retry
Phase 6: Video Clips          → WAN 2.2 FLF dual Hi-Lo (one clip per scene)
Phase 7: Video Review         → Preview each clip
Phase 8: Final Assembly       → ffmpeg concat all clips into one MP4

State File Format

Saved at ~/code/comfyui-mcp/workflows/director_state_{project_id}.json. Updated after every edit or phase completion.

{
  "project_id": "story_20260216_143022",
  "created": "2026-02-16T14:30:22Z",
  "story": "Original user story text",
  "current_phase": 4,
  "orientation": "portrait",
  "hero_frame": { "file": "director_hero_00001_.png", "seed": 428571, "approved": true },
  "character_refs": {
    "man": "director_ref_man.png",
    "cat": "director_ref_cat.png",
    "woman": "director_ref_woman.png",
    "background": "director_ref_bedroom.png"
  },
  "scenes": [
    {
      "id": 1,
      "description": "Brief scene description",
      "edit_prompt_start": "Qwen Edit instruction to create start frame from source",
      "edit_prompt_end": "Qwen Edit instruction to create end frame from source",
      "edit_source_start": "hero",
      "edit_source_end": "hero",
      "video_prompt": "WAN motion description",
      "start_frame": { "file": "director_s1_start_00001_.png", "seed": 12345, "approved": true },
      "end_frame": { "file": "director_hero_00001_.png", "seed": null, "approved": true },
      "video_clip": { "file": "director_s1_00001.mp4", "seed": 11111, "approved": false },
      "status": "video_pending"
    }
  ],
  "final_video": null,
  "settings": {
    "start_frame_resolution": [832, 1472],
    "video_resolution": [480, 720],
    "video_frames": 81,
    "video_fps": 16
  }
}

Models Used Per Phase

CRITICAL: clear_vram between every model family switch.

Phase 1: Story Planning

Break the story into 2-6 scenes. For each scene, identify:

• description: What happens (1-2 sentences)
• start frame: What the opening frame looks like
• end frame: What the closing frame looks like
• video_prompt: Motion description for FLF transition

Identify a hero frame — the single most representative scene image that establishes the main character and setting. This hero will anchor all other frames via Qwen Edit.

Also identify which character reference images are needed (portraits of each character, key props, background).

CRITICAL: Inter-Scene Frame Continuity

The end frame of Scene N must be the EXACT same image file as the start frame of Scene N+1. Do NOT create separate Qwen-edited start frames for subsequent scenes — this causes visible jumps at scene boundaries when the videos are concatenated.

The frame chain for video generation:

Scene 1: S1_start (unique)        → hero (end)
Scene 2: hero (= S1 end)          → S2_end
Scene 3: S2_end (= S2 end)        → S3_end
Scene 4: S3_end (= S3 end)        → S4_end
Scene 5: S4_end (= S4 end)        → S5_end

Only Scene 1 needs a unique start frame. All other scenes inherit their start from the previous scene's end.

Edit Chain Planning

The edit chain produces only end frames (plus Scene 1's unique start frame). Map which end frame derives from which source:

• Some end frames edit directly from the hero
• Later end frames may chain from earlier end frames
• Keep chains shallow (max 4-5 deep) to minimize drift

Example chain:

Hero (man+cat on bed)
  ├─ S1 Start: edit hero → remove cat, man alone
  ├─ S2 End: edit hero → replace cat with woman
  │    └─ S3 End: edit S2End → both sit up, man startled
  │         └─ S4 End: edit S3End → sitting close, warm smiles
  │              └─ S5 End: edit S4End → warm embrace

Phase 2: Hero + Character References — Z-Image

Generate with Z-Image RedCraft DX1 (10 steps, CFG 1, euler/simple):

1. Hero frame: The establishing shot with main character + key elements
2. Character ref portraits: Close-up of each character (man, woman, animal, etc.)
3. Background ref: The setting without characters

Add to negative prompts for character refs to exclude wrong subjects (e.g., "woman, female" when generating man portrait).

Hero Frame Workflow Template

{
  "1": { "class_type": "CheckpointLoaderSimple", "inputs": { "ckpt_name": "redcraftRedzimageUpdatedJAN30_redzibDX1.safetensors" }},
  "2": { "class_type": "CLIPTextEncode", "inputs": { "clip": ["1", 1], "text": "<hero_prompt>" }, "_meta": { "title": "Positive" }},
  "3": { "class_type": "CLIPTextEncode", "inputs": { "clip": ["1", 1], "text": "3D, ai generated, semi realistic, illustrated, drawing, comic, digital painting, 3D model, blender, video game screenshot, render, smooth textures, CGI, text, writing, subtitle, watermark, logo, blurry, low quality, jpeg artifacts, grainy" }, "_meta": { "title": "Negative" }},
  "4": { "class_type": "EmptyLatentImage", "inputs": { "width": 832, "height": 1472, "batch_size": 1 }},
  "5": { "class_type": "KSampler", "inputs": {
    "model": ["1", 0], "positive": ["2", 0], "negative": ["3", 0], "latent_image": ["4", 0],
    "seed": 42, "steps": 10, "cfg": 1, "sampler_name": "euler", "scheduler": "simple", "denoise": 1
  }},
  "6": { "class_type": "VAEDecode", "inputs": { "samples": ["5", 0], "vae": ["1", 2] }},
  "7": { "class_type": "SaveImage", "inputs": { "images": ["6", 0], "filename_prefix": "director_hero" }}
}

Queue hero + all refs while Z-Image checkpoint is loaded (same checkpoint, different prompts).

Phase 3: Hero Review

Show hero frame and all character refs. User approves or requests regeneration with new seed.

Phase 4: Edit Chain — Qwen Image Edit

CRITICAL: Consistency Rules for Edit Prompts

1. Always explicitly anchor clothing: "The man wears his grey t-shirt" in EVERY prompt
2. Always state what doesn't change: "Same bedroom, same warm lighting, same clothing"
3. Use strong emotion words: "extremely shocked and startled" >> "surprised"
4. Include proportionality: "Her head and body should be proportional and natural looking"
5. Prevent head enlargement: In embrace/close-up poses, Qwen Edit tends to enlarge heads. Add explicit: "do not enlarge her head, keep the same small natural size as in the original image"
6. Describe the transformation, not just the end state

Workflow Template (with Character Reference Slots)

{
  "1": { "class_type": "UNETLoader", "inputs": { "unet_name": "qwen_image_edit_2511_bf16.safetensors", "weight_dtype": "default" }},
  "2": { "class_type": "LoraLoaderModelOnly", "inputs": { "model": ["1", 0], "lora_name": "Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors", "strength_model": 1 }},
  "3": { "class_type": "CLIPLoader", "inputs": { "clip_name": "qwen_2.5_vl_7b_fp8_scaled.safetensors", "type": "qwen_image" }},
  "4": { "class_type": "VAELoader", "inputs": { "vae_name": "qwen_image_vae.safetensors" }},
  "5": { "class_type": "LoadImage", "inputs": { "image": "<source_scene.png>" }, "_meta": { "title": "Source Scene" }},
  "5b": { "class_type": "LoadImage", "inputs": { "image": "<character_ref.png>" }, "_meta": { "title": "Character Ref" }},
  "5c": { "class_type": "LoadImage", "inputs": { "image": "<background_ref.png>" }, "_meta": { "title": "Background Ref" }},
  "6": { "class_type": "TextEncodeQwenImageEditPlusAdvance_lrzjason", "inputs": {
    "clip": ["3", 0], "prompt": "<edit_prompt>", "vae": ["4", 0],
    "vl_resize_image1": ["5", 0],
    "vl_resize_image2": ["5b", 0],
    "vl_resize_image3": ["5c", 0],
    "target_size": 1024, "target_vl_size": 384,
    "upscale_method": "lanczos", "crop_method": "pad"
  }},
  "7": { "class_type": "ConditioningZeroOut", "inputs": { "conditioning": ["6", 0] }},
  "8": { "class_type": "KSampler", "inputs": {
    "model": ["2", 0], "positive": ["6", 0], "negative": ["7", 0], "latent_image": ["6", 1],
    "seed": 42, "steps": 4, "cfg": 1, "sampler_name": "euler", "scheduler": "simple", "denoise": 1
  }},
  "9": { "class_type": "VAEDecode", "inputs": { "samples": ["8", 0], "vae": ["4", 0] }},
  "10": { "class_type": "SaveImage", "inputs": { "images": ["9", 0], "filename_prefix": "director_s1_start" }}
}

Key: slots 5b and 5c — feed character reference and background reference into vl_resize_image2 and vl_resize_image3. This helps the vision encoder maintain character appearance across edits.

Chain Execution

Edits are sequential — each depends on the previous output:

1. Run edit, wait for completion
2. Stage the output as the next stage's input with stage_output_as_input (pass the output's { filename, subfolder?, type? }); it returns the registered input filename
3. Use that returned filename as the image in the next edit's LoadImage
4. Update state file after each edit

Independent edits (both from hero) can run in parallel.

CRITICAL: feeding an output into the next loader (don't guess paths)

To pipe ANY stage's output into the next stage's loader (LoadImage here, VHS_LoadVideo / LoadAudio in the video phases), call stage_output_as_input with the output's { filename, subfolder?, type? } and drop the returned input filename into the loader's image/video/audio widget. For a file already on local disk, use upload_image / upload_video / upload_audio. NEVER copy the output file into, or guess, a filesystem input/ path — ComfyUI's input and output directories may be CUSTOM (--input-directory / --output-directory), so a guessed path makes the loader reject the file (Invalid image file) and wastes the render. stage_output_as_input goes through the server API (/view → /upload/image), which resolves the real dirs correctly.

Timing

• First edit: ~87s (model loading)
• Subsequent edits: ~30-40s each (models cached)

Phase 5: Frame Review

For each frame, show via Read for visual inspection. User approves or provides feedback. Re-run individual edits without redoing the whole chain.

Phase 6: Video Clip Generation — WAN 2.2 FLF Dual Hi-Lo

Workflow Template

(Same as wan-flf-video skill — Remix NSFW Hi+Lo, 4-stack LoRA, ImageResizeKJv2, dual KSamplerAdvanced)

Key settings:

• Portrait: width=480, height=720
• 81 frames, 16fps = ~5 seconds per clip
• uni_pc/beta sampler, CFG 1, 4 total steps (Hi: 0→2, Lo: 2→4)
• ModelSamplingSD3 shift=5 on both UNETs

Morph LoRA

For transformation scenes (e.g., cat→woman), add morph LoRA to Hi/Lo Common stacks:

• wan2.2_i2v_magical_morph_highnoise.safetensors → Hi Common slot 1 (strength 1.0)
• wan2.2_i2v_magical_morph_lownoise.safetensors → Lo Common slot 1 (strength 1.0)

Use 1.0 strength — tested without sparkle issues. Lower values (0.7-0.85) produce weaker morph effects that may look like a dissolve rather than a true morph.

Per-Scene Changes

Swap per scene: start/end image filenames, positive prompt text, noise_seed, filename_prefix.

All 5 clips can be queued at once — they run sequentially in ComfyUI, sharing loaded models.

Phase 7: Video Review

Report each clip's filename. User previews externally.

Phase 8: Final Assembly — ffmpeg Concat

cd "<ComfyUI_output_dir>"
printf "file 'director_s1_00001.mp4'\nfile 'director_s2_00001.mp4'\n..." > concat_list.txt
ffmpeg -f concat -safe 0 -i concat_list.txt -c copy director_final_{project_id}.mp4

All clips share resolution/codec/framerate — copy-concat works without re-encoding.

Resumption Protocol

After context compaction:

1. Read state file AND director_session_notes.md if it exists
2. Check current_phase and per-scene status
3. Skip approved assets, continue from incomplete point
4. clear_vram before loading the model family for the current phase

Timing Estimates (RTX 4090)

Storytelling Props for Continuity

Use distinctive visual elements that transfer between characters/forms to create narrative connections:

• A colored collar on an animal → becomes a choker/necklace on the human form
• Eye color matching between animal and human
• Distinctive clothing or accessories that persist across scenes
• These "continuity props" reinforce the story visually

Prompt Engineering for Edit Chains

DO

• "The man wears his grey t-shirt" (anchor clothing every time)
• "Same bedroom, same warm amber lamplight, same white sheets"
• "Extremely shocked, jaw dropped, eyes wide in total disbelief"
• "Her head and body proportional and natural looking"

DON'T

• Assume clothing/setting will be preserved automatically
• Use mild emotion words ("surprised" → use "extremely shocked" instead)
• Chain more than 5-6 edits deep without branching back to hero
• Assume head proportions stay correct in embrace/hug poses — always add explicit size anchoring

WAN Video Prompts

• Use motion verbs: "walks", "turns", "reaches", "sits up", "leans in"
• AVOID: "magical", "enchanted", "mystical" (causes sparkle effects)
• USE: "smoothly transforms", "seamlessly reshapes", "gradually"
• Include scale cues: "grows into", "expands upward"