Assemble course videos from individual lesson files with title slides and auto-generated timestamps for YouTube.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionvideo-productionExecute the skills CLI command in your project's root directory to begin installation:
Fetches video-production from casper-studios/casper-marketplace and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate video-production. Access via /video-production in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
0
total installs
0
this week
10
GitHub stars
0
upvotes
Run in your terminal
0
installs
0
this week
10
stars
Assemble course videos from individual lesson files with title slides and auto-generated timestamps for YouTube.
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
Google Drive OAuth (same as google-workspace skill).
# 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
[e1] Intro format| File | Description |
|---|---|
{output_name}.mp4 |
Final stitched video |
youtube_description.md |
Timestamped description |
metadata.json |
Processing info |
| 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 |
mycreds.txt and client_secrets.json never committed to git.tmp/drive.readonly sufficient for downloadingdrive required for uploading final videos.tmp/ after processingSymptoms: "FFmpeg not found" or "command not found: ffmpeg" Cause: FFmpeg not installed or not in system PATH Solution:
brew install ffmpeg (macOS) or download from ffmpeg.orgffmpeg -versionSymptoms: "Non-monotonous DTS" or codec errors during stitching Cause: Source videos have different codecs, resolutions, or frame rates Solution:
ffmpeg -i input.mp4 -c:v libx264 -c:a aac output.mp4Symptoms: Audio drifts from video over time Cause: Inconsistent frame rates or variable frame rate sources Solution:
-vsync cfr flagSymptoms: "No space left on device" or incomplete output Cause: Not enough free space for video processing Solution:
df -h.tmp/ directory of old filesSymptoms: Videos fail to download from Drive folder Cause: OAuth issue, permissions, or network timeout Solution:
Symptoms: Missing title cards in final video Cause: Font or image generation issue Solution:
Skills: google-workspace → video-production → google-workspace Use case: End-to-end course video assembly Flow:
Skills: transcript-search → video-production Use case: Generate YouTube descriptions from meeting recordings Flow:
Skills: content-generation → video-production Use case: Create branded title cards for videos Flow:
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
supercent-io/skills-template
casper-studios/casper-marketplace
affaan-m/everything-claude-code
remotion-dev/skills
heygen-com/skills
zrong/skills
We added video-production from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend video-production for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for video-production matched our evaluation — installs cleanly and behaves as described in the markdown.
video-production fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: video-production is the kind of skill you can hand to a new teammate without a long onboarding doc.
video-production fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
video-production reduced setup friction for our internal harness; good balance of opinion and flexibility.
video-production reduced setup friction for our internal harness; good balance of opinion and flexibility.
Keeps context tight: video-production is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: video-production is focused, and the summary matches what you get after install.
showing 1-10 of 67