
Webinar To Content Multiplier
You record a webinar and then it sits in a folder doing nothing. This skill takes that recording and breaks it down into blog posts, social media snippets, email sequences, and pulls out quotable stats. The output format gives you structured content with timestamps and recommendations for what to do next. Honestly, the real win here is speed. Instead of manually combing through an hour of video to find three good tweets, you get formatted content ready to schedule. Best for marketing teams running regular webinars who need to justify the production effort with more distribution.
- skills.sh installs
- 321
- GitHub stars
- 422
- last updated
- Aug 21, 2026
Install
$ npx -y skills add onewave-ai/claude-skills --skill webinar-to-content-multiplier --agent claude-codeInstalls into .claude/skills of the current project.
Files
Webinar To Content Multiplier
Convert webinar recordings into blog posts, social snippets, email series. Extract key quotes, statistics, and soundbites.
Instructions
You are an expert at content repurposing and marketing automation. Transform webinars into multiple content formats optimized for each channel.
Output Format
# Webinar To Content Multiplier Output
**Generated**: {timestamp}
---
## Results
[Your formatted output here]
---
## Recommendations
[Actionable next steps]
Best Practices
- Be Specific: Focus on concrete, actionable outputs
- Use Templates: Provide copy-paste ready formats
- Include Examples: Show real-world usage
- Add Context: Explain why recommendations matter
- Stay Current: Use latest best practices for marketing
Common Use Cases
Trigger Phrases:
- "Help me with [use case]"
- "Generate [output type]"
- "Create [deliverable]"
Example Request:
"[Sample user request here]"
Response Approach:
- Understand user's context and goals
- Generate comprehensive output
- Provide actionable recommendations
- Include examples and templates
- Suggest next steps
Sponsors
Details
- Repository
- github.com/onewave-ai/claude-skills
- Categories
- Documentation, Data Science & ML
- First seen
- Jun 3, 2026
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