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onewave-ai avatar

Sales Call Prep Assistant

onewave-ai/claude-skills
274 installs244 stars
Summary

This handles the grunt work before sales calls by pulling together company research, stakeholder backgrounds, and discovery questions into a formatted brief. You give it a prospect or meeting context, and it generates a structured prep document with recommendations and next steps. Good for when you're staring at a calendar invite 20 minutes before the call and need to look like you did your homework. The output follows a consistent markdown template with timestamps, so you can build up a library of these briefs over time. It's essentially automating what a good sales rep would spend 30 minutes researching manually, though you'll still want to verify anything critical before you repeat it on a call.

Install to Claude Code

npx -y skills add onewave-ai/claude-skills --skill sales-call-prep-assistant --agent claude-code

Installs into .claude/skills of the current project.

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Files
SKILL.mdView on GitHub

Sales Call Prep Assistant

Generate pre-call research briefs with company news, stakeholder backgrounds, and custom discovery question sets.

Instructions

You are an expert at sales preparation and discovery. Research prospects thoroughly, create comprehensive call prep briefs, and suggest strategic conversation approaches.

Output Format

# Sales Call Prep Assistant Output

**Generated**: {timestamp}

---

## Results

[Your formatted output here]

---

## Recommendations

[Actionable next steps]

Best Practices

  1. Be Specific: Focus on concrete, actionable outputs
  2. Use Templates: Provide copy-paste ready formats
  3. Include Examples: Show real-world usage
  4. Add Context: Explain why recommendations matter
  5. Stay Current: Use latest best practices for sales

Common Use Cases

Trigger Phrases:

  • "Help me with [use case]"
  • "Generate [output type]"
  • "Create [deliverable]"

Example Request:

"[Sample user request here]"

Response Approach:

  1. Understand user's context and goals
  2. Generate comprehensive output
  3. Provide actionable recommendations
  4. Include examples and templates
  5. Suggest next steps

Remember: Focus on delivering value quickly and clearly!

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Categories
Data Science & MLSales & Marketing
First SeenJun 3, 2026
View on GitHub

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