video-production▌
casper-studios/casper-marketplace · updated Apr 8, 2026
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Assemble course videos from individual lesson files with title slides and auto-generated timestamps for YouTube.
Video Production
Overview
Assemble course videos from individual lesson files with title slides and auto-generated timestamps for YouTube.
Quick Decision Tree
What do you need?
│
├── Full course assembly (end-to-end)
│ └── references/workflow.md
│ └── Combines all scripts below
│
├── Download videos from Drive
│ └── Script: scripts/gdrive_video_download.py
│
├── Create title slides
│ └── Script: scripts/create_title_slides.py
│
├── Stitch videos together
│ └── Script: scripts/stitch_videos.py
│
└── Generate YouTube description
└── Script: scripts/generate_youtube_description.py
Environment Setup
Google Drive OAuth (same as google-workspace skill).
System Requirements
- FFmpeg installed and in PATH
- Python 3.9+
Complete Workflow
# Full course assembly from Drive folder
python scripts/stitch_videos.py \
--folder "https://drive.google.com/drive/folders/xxx" \
--output "Complete Course.mp4" \
--slide-duration 3
Pipeline Steps
- Download - Get all videos from Drive folder
- Parse Titles - Extract clean names from
[e1] Introformat - Get Metadata - FFprobe for duration/resolution
- Generate Slides - Title card for each lesson
- Build Concat List - video1 → slide2 → video2 → ...
- Stitch with FFmpeg - Concatenate all segments
- Calculate Timestamps - Track cumulative duration
- Generate Description - YouTube-ready markdown
Outputs
| File | Description |
|---|---|
{output_name}.mp4 |
Final stitched video |
youtube_description.md |
Timestamped description |
metadata.json |
Processing info |
Performance
| Input | Time | Output Size |
|---|---|---|
| 5 videos (30 min) | ~5 min | ~1.5 GB |
| 10 videos (1 hr) | ~10 min | ~3 GB |
| 20 videos (2 hr) | ~20 min | ~6 GB |
Security Notes
Credential Handling
- Google OAuth credentials for Drive access (see google-workspace skill)
mycreds.txtandclient_secrets.jsonnever committed to git- No additional API keys required for local video processing
Data Privacy
- All video processing happens locally using FFmpeg
- No video content is uploaded to external cloud services
- Source videos downloaded from Google Drive to local
.tmp/ - Final videos stored locally until manually uploaded
- Metadata JSON contains file names and timestamps only
Access Scopes
- Google Drive:
drive.readonlysufficient for downloading - Google Drive:
driverequired for uploading final videos - No external video processing APIs used
Compliance Considerations
- Local Processing: All encoding/stitching done locally (privacy-preserving)
- No Cloud Upload: Videos never leave your machine during processing
- Content Rights: Ensure you have rights to source video content
- Course Content: Verify licensing for educational content distribution
- YouTube ToS: Generated descriptions comply with YouTube guidelines
- Storage: Large video files require adequate local disk space
- Cleanup: Remove temporary files from
.tmp/after processing
Troubleshooting
Common Issues
Issue: FFmpeg not found
Symptoms: "FFmpeg not found" or "command not found: ffmpeg" Cause: FFmpeg not installed or not in system PATH Solution:
- Install FFmpeg:
brew install ffmpeg(macOS) or download from ffmpeg.org - Verify installation:
ffmpeg -version - Add FFmpeg to PATH if installed in non-standard location
- Restart terminal after installation
Issue: Codec mismatch / incompatible videos
Symptoms: "Non-monotonous DTS" or codec errors during stitching Cause: Source videos have different codecs, resolutions, or frame rates Solution:
- Re-encode all source videos to the same format before stitching
- Use FFmpeg to normalize:
ffmpeg -i input.mp4 -c:v libx264 -c:a aac output.mp4 - Ensure consistent resolution (e.g., all 1920x1080)
- Match frame rates across all videos (e.g., all 30fps)
Issue: Audio out of sync
Symptoms: Audio drifts from video over time Cause: Inconsistent frame rates or variable frame rate sources Solution:
- Use constant frame rate for all source videos
- Re-encode with
-vsync cfrflag - Avoid mixing video from different sources/devices
- Check audio sample rates match across files
Issue: Insufficient disk space
Symptoms: "No space left on device" or incomplete output Cause: Not enough free space for video processing Solution:
- Check available disk space:
df -h - Clear
.tmp/directory of old files - Move large source videos to external drive
- Process fewer videos at once
Issue: Google Drive download fails
Symptoms: Videos fail to download from Drive folder Cause: OAuth issue, permissions, or network timeout Solution:
- Verify Google OAuth credentials (see google-workspace skill)
- Check folder sharing permissions
- Try downloading single file first to test
- Check for network connectivity issues
Issue: Title slides not generating
Symptoms: Missing title cards in final video Cause: Font or image generation issue Solution:
- Verify ImageMagick or Pillow is installed
- Check font files exist if custom fonts specified
- Review title text for special characters
- Try with default font settings first
Resources
- references/workflow.md - Complete video course workflow
Integration Patterns
Full Course Pipeline
Skills: google-workspace → video-production → google-workspace Use case: End-to-end course video assembly Flow:
- Download lesson videos from Google Drive folder
- Generate title slides and stitch all videos together
- Upload final video back to Drive and generate YouTube description
Transcript to Timestamps
Skills: transcript-search → video-production Use case: Generate YouTube descriptions from meeting recordings Flow:
- Search transcripts for relevant meetings
- Extract topic timestamps from transcript
- Generate formatted YouTube description with chapter markers
Content to Title Slides
Skills: content-generation → video-production Use case: Create branded title cards for videos Flow:
- Generate title slide images with content-generation
- Export slides in video-compatible format
- Insert title slides between video segments
How to use video-production on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add video-production
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches video-production from GitHub repository casper-studios/casper-marketplace and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate video-production. Access the skill through slash commands (e.g., /video-production) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★67 reviews- ★★★★★Arya White· Dec 24, 2024
We added video-production from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★James Wang· Dec 24, 2024
I recommend video-production for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Luis Reddy· Dec 20, 2024
Registry listing for video-production matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Sophia Mehta· Dec 20, 2024
video-production fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Nia Okafor· Dec 16, 2024
Keeps context tight: video-production is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Shikha Mishra· Dec 12, 2024
video-production fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Ganesh Mohane· Dec 8, 2024
video-production reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Sophia Menon· Nov 23, 2024
video-production reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Luis Bhatia· Nov 15, 2024
Keeps context tight: video-production is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Kwame Choi· Nov 15, 2024
Solid pick for teams standardizing on skills: video-production is focused, and the summary matches what you get after install.
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