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14790897
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kwp-sales-call-summary

Extract action items, objections, and key points from sales call transcripts.

7|5|Updated May 7, 2026
Search Tags:#transcript#summarization#productivity#sales#crm#follow-up
One-click install
npx skills add https://github.com/14790897/MiQi --skill kwp-sales-call-summary
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: kwp-sales-call-summary
Source: https://github.com/14790897/MiQi/tree/main/miqi/skills/kwp/sales/call-summary
Command: npx skills add https://github.com/14790897/MiQi --skill kwp-sales-call-summary

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill eliminates the manual effort required to synthesize unstructured meeting notes or transcripts into professional summaries, follow-up emails, and CRM updates.

Core Features & Use Cases

  • Automated Synthesis: Extracts key discussion points, decisions, and competitive intelligence from raw text.
  • Actionable Output: Generates structured internal summaries and customer-facing follow-up emails.
  • Use Case: After a discovery call, paste your rough notes to instantly generate a professional email for the client and a structured summary for your internal CRM.

Quick Start

Use the kwp-sales-call-summary skill to process the meeting transcript provided in the current chat context.

Frequently Asked Questions about kwp-sales-call-summary

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I summarize sales call transcripts into action items?▼

Yes, this skill generates professional follow-up emails by extracting key discussion points and decisions from raw sales call notes. It transforms unstructured text into actionable, customer-facing communications automatically.

Can I use raw meeting notes to generate a CRM update summary?▼

Processing unstructured sales call notes requires natural language processing capabilities to identify business-critical information. This skill handles the parsing internally to extract objections, decisions, and action items from conversational data.

What is the best way to extract customer objections from discovery call notes?▼

To start summarizing a transcript, paste your rough meeting notes into the current chat context. The skill processes the provided text to output structured internal summaries and professional client emails.

Does this skill work with completely unstructured conversational data?▼

This skill works with unstructured conversational data by using natural language processing to identify and structure business-critical information. It handles raw text from discovery calls to extract actionable sales intelligence.

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