- AGENT_GUIDE.md: add "never read source code" rule — skills are the
interface, not .py files
- animation.yaml: add Layer 2 skill-first guardrail in assets stage
- video-reference-analyst.md: Step 4b now mandates Layer 2 before Layer 3,
explicitly forbids reading implementation code
- CinematicRenderer: add TikTok-style CaptionOverlay and separate music
track support (narration + music as independent audio layers)
- cinematic/types.ts: add CinematicCaptionConfig and music prop types
Chirp3-HD is near-free ($0.003 vs $0.30+ per script), expressive,
24kHz, and available without quota limits. ElevenLabs demoted to
voice-cloning-only recommendation.
New Step 4b requires the agent to read agent_skills from every tool
before writing generation prompts. Discovered during UAT: agent
generated video clips, images, and TTS without reading provider-specific
prompting guidance, violating AGENT_GUIDE governance.
Proposals must now specify clip duration strategy (prefer 10s over 5s
to halve API costs) and list Layer 3 skills that must be read before
generating assets. Both were governance gaps found during UAT.
Agent must run tts_selector preflight to check available providers
instead of defaulting to ElevenLabs. Supports ElevenLabs, Google TTS,
OpenAI TTS, and Piper (offline).
The agent must lock the audio approach (single narrator vs. character
dialogue vs. both) during Step 3, not defer it to script/compose stage.
Proposals now include voice casting with specific voice IDs.
Remotion is now the default composition engine for ALL final renders
when available — video clips, images, mixed content. FFmpeg is only
used as fallback when Remotion is not installed or for standalone
operations (trim, transcode). Also fixes three FFmpeg fallback bugs:
profile + copy codec conflict, stream order mapping, and segment
seeking for audio-first containers.
The reference analyst skill went straight from capability audit to
creative proposals with no research. This caused the agent to propose
concepts based solely on the reference analysis and its own knowledge,
missing content landscape context, technique best practices, and
subject-matter depth.
Added Step 3b between critical questions and creative proposals:
- Content landscape scan (3-5 similar existing videos)
- Style/technique research (AI model strengths, prompting patterns)
- Subject-matter research (facts, tropes, hooks)
- 2-3 minute time budget — lightweight, not full research-director
The AGENT_GUIDE establishes Remotion as the preferred composition engine
over FFmpeg, but the reference analyst skill was presenting them as peer
options. This caused the agent to default to FFmpeg during proposals.
- Capability audit template now labels Remotion as "preferred" and FFmpeg
as "fallback only"
- Added explicit composition engine priority note
- Proposal template separates Composition and Motion as distinct lines
Video analyzer now uses Farneback dense optical flow to classify each
scene as motion_clip, animated_still, or static_image. This lets the
agent correctly identify whether a reference video uses AI-generated
video clips vs still images with pan/zoom — and plan the right pipeline.
Changes:
- video_analyzer.py: new Step 3b with _classify_scene_motion() and
_read_frame_at() helpers; updated _needs_motion() to use per-scene
motion data instead of pacing heuristic alone
- video-reference-analyst.md: added Motion line to summary template
and instructions to read motion_type field before proposing tools
calesthio