video/skills/pipelines/avatar-spokesperson/asset-director.md

Asset Director - Avatar Spokesperson Pipeline

When To Use

This stage prepares the actual spokesperson ingredients: narration, avatar or lip-sync footage, subtitle assets, branded backgrounds, and the minimal support graphics needed to complete the cut.

Prerequisites

Layer	Resource	Purpose
Schema	schemas/artifacts/asset_manifest.schema.json	Artifact validation
Prior artifacts	state.artifacts["scene_plan"]["scene_plan"], state.artifacts["script"]["script"], state.artifacts["idea"]["brief"]	Presenter plan and narration needs
Tools	talking_head, lip_sync, tts_selector, subtitle_gen, image_selector, audio_enhance — selectors auto-discover all available providers from the registry	Avatar, narration, and support asset options
Playbook	Active style playbook	Background, type, and subtitle rules

Process

1. Lock The Avatar Generation Path

Use one primary path and record it clearly:

• talking_head from still image plus audio,
• lip_sync from existing presenter plate plus new audio,
• externally supplied avatar render if created outside the current runtime.

Do not hide a blocked avatar path. Record it.

1b. Sample Preview (Prevents Wasted Spend)

Before batch-generating assets, produce one sample of each expensive type and show the user:

1. TTS sample (if generating narration): Generate one section. Confirm voice, pace, and persona before batching the rest.
2. Avatar sample (if using talking_head): Generate a short test clip. Confirm the avatar quality is acceptable before committing to full generation.

If rejected, adjust parameters and retry (max 3 iterations). Do not batch until approved.

2. Resolve Narration Before Support Graphics

Spokesperson videos depend on speech. Determine whether narration is:

• supplied,
• TTS-generated,
• already embedded in a presenter plate.

If narration is missing and no TTS tool is available, mark the project blocked instead of pretending the stage succeeded.

3. Build The Minimal Support Kit

Prepare only what the scene plan actually needs:

• subtitle files,
• one lower-third system,
• CTA card,
• background or plate assets,
• optional still or product support images.

4. Use Metadata For Capability Truth

Recommended metadata keys:

• avatar_generation_path
• narration_assets
• subtitle_assets
• background_assets
• scene_asset_index
• blocked_assets

5. Quality Gate

• the avatar path is explicit,
• narration and avatar assets align,
• support graphics stay minimal,
• every referenced file exists.

No-Avatar Path

When the EP has triggered a narration-over-graphics pivot (neither talking_head nor lip_sync available), skip avatar generation entirely and produce a graphics-driven asset kit instead:

What to produce:

1. Narration audio — via tts_selector (mandatory; block the project if no TTS is available either).
2. Scene visuals — via image_selector or video_selector. One primary visual per scene that reinforces the spoken point (diagram, illustration, product shot, or stock footage).
3. Subtitle files — same as standard path.
4. Text cards — key-point overlays, stat cards, CTA end card.
5. Backgrounds — consistent family matching the playbook.

What to skip:

• No talking_head or lip_sync calls.
• No presenter framing metadata.
• avatar_generation_path should be set to "none — narration-over-graphics pivot".

Metadata for this path:

• avatar_generation_path: "narration_over_graphics"
• pivot_reason: why the no-avatar path was chosen
• All other metadata keys remain the same.

Mid-Production Fact Verification

If you encounter uncertainty during asset generation:

• Use web_search to verify visual accuracy of subjects (e.g. what does this building actually look like?)
• Use web_search to find reference images before generating illustrations
• Log verification in the decision log: category="visual_accuracy_check"

Visual accuracy matters. If the script mentions a specific place, person, or object, verify what it actually looks like before generating images. Don't rely on the AI model's training data — it may be wrong or outdated.

Common Pitfalls

• Building decorative assets before the narration path is solved.
• Mixing multiple avatar-generation strategies in one simple spokesperson video.
• Marking the stage complete when the core presenter asset is still hypothetical.
• (No-avatar path) Generating filler visuals with no connection to the narration — every image must reinforce the spoken point.

When You Do Not Know How

If you encounter a generation technique, provider behavior, or prompting pattern you are unsure about:

1. Search the web for current best practices — models and APIs change frequently, and the agent's training data may be stale
2. Check .agents/skills/ for existing Layer 3 knowledge (provider-specific prompting guides, API patterns)
3. If neither helps, write a project-scoped skill at projects/<project-name>/skills/<name>.md documenting what you learned
4. Reference source URLs in the skill so the knowledge is traceable
5. Log it in the decision log: category: "capability_extension", subject: "learned technique: <name>"

This is especially important for:

• Video generation prompting — models respond to specific vocabularies that change with each version
• Image model parameters — optimal settings for FLUX, DALL-E, Imagen differ and evolve
• Audio provider quirks — voice cloning, music generation, and TTS each have model-specific best practices
• Remotion component patterns — new composition techniques emerge as the framework evolves

Do not rely on stale knowledge. When in doubt, search first.