菜单
Automated video editing pipeline for CC's personal brand content. Use whenever CC drops raw footage and needs it edited, captioned, graded, and sent for review. The primary tool is video_editor.py which handles the full 8-step pipeline.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Higgsfield image prompt director covering Banana Pro, Soul Cinema, and GPT-2. Three asset types in strict order — single-image character outfit on white seamless studio (Banana Pro or Soul Cinema two-step), 6-panel multi-angle character sheet off that base, and scene plates with/without characters. Plus GPT-2 for detail face/chest-up portraits. Reads reference images for hair, makeup, wardrobe, jewelry, identity. Outputs photorealistic prompts with locked hyperreal stack — skin pores, subsurface scattering, strand-by-strand hair, fabric weave, Kodak Vision3 film. Use for any character outfit reference, character sheet, model sheet, ref sheet, multi-angle sheet, scene plate, environment plate, face detail, or photorealistic still — even without saying 'Banana Pro,' 'Nano Banana,' or 'Soul Cinema.'
Universal cinema worldbuilding director for Seedance video prompts. Five cinema modes (Narrative, Studio, Action, Performance, Atmospheric) with locked ARRI + Panavision/Cooke camera specs and diegetic-only audio rules. Reads reference images for wardrobe, hair, makeup, identity, and environment. Outputs production-ready Seedance prompts. Use whenever CC asks for a Seedance video prompt, mentions Seedance, asks for cinematic scene breakdowns, uploads reference images for a scene, describes a scene for video generation, or asks for shot prompts for music videos, action sequences, performance scenes, narrative shorts, fashion films, or atmospheric environment plates — even if 'cinematic' or a mode name isn't said.
Complete automated video production system for CC's content pipeline. Use whenever CC provides raw video footage and says "make this a post", "edit this", or asks for a cinematic output. Replaces a human video editor entirely. Covers hook engineering, pacing, caption styling, color grading, audio mastering, sound design, motion graphics, and multi-platform export.
Read-only social + web listening across public platforms (YouTube, Twitter/X, LinkedIn, Reddit, the open web, GitHub, Exa search) for competitive intelligence, content research, transcript mining, and checking public post results. Wraps Agent Reach via scripts/social_reach_tool.py. Does NOT read Instagram, TikTok, or Facebook.
Build high-converting, education-first advertorial / "infomercial" landing pages for ecommerce products — long-form scrollable HTML that warms cold paid traffic and clicks through to the product page. Covers angle selection, direct-response copy doctrine, AI image generation with a product reference, a premium anti-slop design system, and a portable build/QA convention. Use for advertorials, pre-sell pages, native/listicle ad landers, VSL pages, or any "read-an-article-then-buy" funnel page.
Use this skill whenever the user wants to capture, organize, retrieve, or maintain business intelligence. Covers PARA implementation, information capture protocols, progressive summarization, retrieval frameworks, freshness scoring, template library management, and weekly maintenance checklists.
| name | video-editing |
| description | Automated video editing pipeline for CC's personal brand content. Use whenever CC drops raw footage and needs it edited, captioned, graded, and sent for review. The primary tool is video_editor.py which handles the full 8-step pipeline. |
| triggers | ["video","edit","raw footage","silence","filler","caption","grade","master","review","content day","batch"] |
| tier | standard |
| dependencies | ["content-engine","elite-video-production"] |
| canon_references | ["sutherland-signalling","dunford-positioning"] |
| canon_source | brain/MARKETING_CANON.md |
| universal | true |
Primary tool:
scripts/video_editor.py
Supports:scripts/content_pipeline.py(captions, transcription)
video_editor.pyedit command)Step 1: Silence detection (FFmpeg silencedetect, threshold -30dB, min 0.4s)
Step 2: Filler word detection (Whisper word-level timestamps)
Step 3: Apply cuts (FFmpeg concat demuxer, keep segments only)
Step 4: Audio mastering (Gate→Highpass→Lowpass→Compand→Loudnorm -14 LUFS)
Step 5: Color grading (Pillar-auto-mapped: teal_orange, editorial, warm, clean)
Step 6: Karaoke captions (Word-by-word highlight via content_pipeline.py ASS format)
Step 7: Background music (Auto-ducked, mood-matched to pillar from media/music/)
Step 8: Telegram review (sendVideo to CC, awaits 'approve' or feedback)
# Full edit pipeline (raw → review-ready)
python scripts/video_editor.py edit media/raw/piece_1.mp4 --pillar ai_oracle
# Remove silence + fillers only (no captions, no music, no grading)
python scripts/video_editor.py clean media/raw/piece_1.mp4
# Preview what would be cut (non-destructive analysis)
python scripts/video_editor.py analyze media/raw/piece_1.mp4
# Export edited video to all platform formats
python scripts/video_editor.py export media/exports/piece_1_final.mp4
# Send edited video to Telegram for CC's review
python scripts/video_editor.py review media/exports/piece_1_final.mp4
# Content Day: batch edit all videos in a directory
python scripts/video_editor.py batch media/raw/ --manifest data/content_day/2026-04-27_template.json
--skip-music # No background music overlay
--skip-captions # No karaoke captions
--skip-review # No Telegram notification
--skip-grade # No color grading
--skip-master # No audio mastering
--grade warm # Override auto-selected grade preset
| Preset | Pillar Default | Look |
|---|---|---|
teal_orange | AI Oracle | Cinematic teal shadows, warm skin tones |
editorial | CEO Log | Desaturated, high contrast, professional |
warm | The Becoming, The Journey | Warm orange tones, gentle vignette |
clean | (manual) | Neutral with micro-contrast, minimal processing |
Applied automatically in step 4:
| Platform | Max Duration | Resolution |
|---|---|---|
| Instagram Reels | 90s | 1080x1920 |
| TikTok | 180s | 1080x1920 |
| YouTube Shorts | 60s | 1080x1920 |
| 600s | 1080x1920 | |
| 240s | 1080x1920 | |
| X/Twitter | 140s | 1080x1920 |
media/
raw/ # CC drops raw footage here
exports/ # Edited videos output here
music/
intense/ # AI Oracle pillar tracks
warm/ # The Becoming pillar tracks
emotional/ # The Journey pillar tracks
confident/ # CEO Log pillar tracks
| Package | Purpose | Status |
|---|---|---|
openai-whisper | Transcription + filler detection | Installed |
auto-editor | Silence removal (backup method) | Installed |
pydub | Audio analysis | Installed |
ffmpeg | All video/audio processing | Installed |
1. CC films 7 pieces → drops into media/raw/
2. python scripts/video_editor.py batch media/raw/ --manifest data/content_day/YYYY-MM-DD_template.json
3. Each video: silence cut → filler cut → master → grade → caption → music → Telegram
4. CC reviews each on phone, replies 'approve' or feedback
5. python scripts/batch_content_day.py schedule --manifest data/content_day/YYYY-MM-DD_template.json
6. Videos go live across 8 platforms over the next 7 days
| Repo | Stars | What We Use From It |
|---|---|---|
| WyattBlue/auto-editor | 4.2k | Silence removal architecture, margin/threshold approach |
| SamurAIGPT/AI-Youtube-Shorts-Generator | — | Viral highlight detection pattern |
| MatteoFasulo/Whisper-TikTok | — | Caption burn-in workflow |
| HubertKasperek/short-maker | — | Audio ducking + subtitle approach |
After scripts/video_editor.py review sends the edit to Telegram and CC responds:
| CC's response | Where to log | What to propagate to brain/video-style/taste_profile.md |
|---|---|---|
| "approve" | brain/video-style/approved_edits/YYYY-MM-DD_<slug>.md — note what landed (hook style, pacing, B-roll choices, grade) | Nothing direct, but this counts toward a 3-confirmation promotion of a default. |
| "approve but [change]" | approved_edits/YYYY-MM-DD_<slug>.md AND propagate change | Add dated bullet under the relevant section, cite the slug. |
| "reject because [reason]" | brain/video-style/rejected_edits/YYYY-MM-DD_<slug>.md — paste CC's verbatim feedback | Add dated bullet under the relevant section, cite the slug. Update last_updated:. |
Read brain/video-style/taste_profile.md FIRST on the next edit. Full system spec in brain/video-style/README.md and skills/elite-video-production/SKILL.md Section 16.