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calesthio 355fd2b7d6 Implementation spec: governance, decision intelligence, theme system, and E2E bug fixes

Implements the 2026-04-02 transformation spec (Phases 1-8) and fixes all
critical bugs found during 5-pipeline E2E testing.

Governance & Decision Intelligence:
- Pipeline-specific stage order in checkpoint (replaces global STAGES list)
- Provider scoring engine (lib/scoring.py) with 7-dimension weighted ranking
- Decision log artifact enforced at proposal/idea stage across all 10 pipelines
- Delivery promise classifier prevents silent motion-to-still downgrades
- Structured shot language in scene_plan schema (camera, lens, lighting, DOF)
- Variation checker and slideshow risk scorer block samey output before render
- Creative intake, capability extension, and creative-intake meta skills
- Final self-review artifact with 5 mandatory checks before presenting output
- Source media review contract for user-supplied footage

Render & Theme System:
- Remotion AnimatedBackground now derives colors from playbook (no more hardcoded
  dark blue fintech gradient on every video)
- video_compose builds custom ThemeConfig from playbook YAML colors/fonts —
  custom playbooks flow through to Remotion automatically
- Explainer component wires theme to all child components (charts, cards, etc.)
- resolveAsset() handles absolute paths on Windows/Unix via file:// URIs
- RENDERER_FAMILY_MAP synced with actual Remotion compositions

Critical Bug Fixes:
- Windows npx subprocess: run_command() resolves .cmd wrappers via shutil.which()
- Silent renderer downgrade: Remotion failure now returns explicit error with
  options instead of silently falling back to FFmpeg
- .env inline comment parsing strips trailing # comments from API keys
- concat_path UnboundLocalError in video_compose finally block
- audio_mixer and showcase_card capture=True kwarg bug
- Selector estimate_cost() calls fixed (_select_tool -> _select_best_tool)
- asset_manifest schema expanded with provider, license, subtype fields
- screen-demo subtitle_gen moved from required to optional tools
- Duration drift detection in post-render final review (>25% warns)

2026-04-03 09:35:09 -07:00

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Script Director - Hybrid Pipeline

When To Use

This stage maps the story across source-led beats and support-led beats. You are deciding where the source carries the message and where support assets clarify it.

Prerequisites

Layer	Resource	Purpose
Schema	`schemas/artifacts/script.schema.json`	Artifact validation
Prior artifact	`state.artifacts["idea"]["brief"]`	Anchor medium and deliverable mix
Tools	`transcriber`, `scene_detect`, `audio_enhance`	Optional source analysis

Process

1. Mark Source-Led Versus Support-Led Beats

For each section, state whether it is:

carried by source dialogue or footage,
carried by narration,
carried by diagrams or overlays,
carried by text only.

2. Use Source Speech When It Is Better Than Rewriting

If the supplied footage already contains strong lines, use transcriber and keep the authenticity. Do not replace good source material with unnecessary narration.

3. Use Support Only To Clarify

Support-led beats should answer:

what is not visible,
what needs summarizing,
what needs emphasis,
what changes for a different platform.

4. Use Metadata For Structure

Recommended metadata keys:

anchor_sections
support_sections
narration_sections
required_support_assets

5. Quality Gate

source-led beats are clearly marked,
support-led beats are justified,
the script does not depend on fake or unavailable assets without saying so,
the structure can produce the intended deliverables.

Mid-Production Fact Verification

If you encounter uncertainty during script writing:

Use web_search to verify factual claims before committing them to the script
Use web_search to find reference images for visual accuracy
Log verification in the decision log: category="visual_accuracy_check"

Every factual claim in the script should be traceable to the research_brief. If you make a claim that isn't in the research, do additional research and add the source. Do not invent statistics, dates, or attributions.

Common Pitfalls

Rewriting strong source dialogue into weaker narration.
Adding diagrams or cards where the footage already explains the point.
Hiding unsupported requirements until asset generation.

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