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