customer-research

Identify customer questions, gather sources, and generate confidence-scored answers.

14|3|Updated Jan 19, 2026
One-click install
npx skills add https://github.com/kevinlin/cowork-z --skill customer-research-kevinlin
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: customer-research
Source: https://github.com/kevinlin/cowork-z/tree/main/src-tauri/resources/skill-templates/support-customer-research
Command: npx skills add https://github.com/kevinlin/cowork-z --skill customer-research-kevinlin

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Researchers and customer-facing teams spend hours cross-referencing docs, tickets, and knowledge sources to answer customer questions. This skill streamlines that process by centralizing multi-source research and delivering a confidence-scored answer.

Core Features & Use Cases

  • Multi-source question analysis: identifies the customer's question and aggregates evidence from official docs, CRM data, and internal communications.
  • Evidence synthesis with confidence scoring: combines findings across sources and assigns a clear confidence level.
  • Use Case: Customer success inquiries, product feedback clarifications, and account context research.

Quick Start

Summarize a customer question with supporting sources from docs, tickets, and knowledge bases.

Frequently Asked Questions about customer-research

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

FAQPage Schema
How do I synthesize customer insights across multiple sources like docs and CRM records?

To synthesize customer insights across multiple sources, the skill identifies the customer question and applies a tiered source approach. It gathers official docs, CRM data, and team communications to corroborate findings and return a structured synthesis.

What is the best way to cross-reference customer tickets and knowledge bases for product feedback clarifications?

Cross-referencing customer tickets and knowledge bases is best handled by centralizing multi-source research. The skill aggregates evidence to deliver a confidence-scored answer for product feedback clarifications and account context research.

How does confidence scoring work for customer research answers derived from internal communications and external references?

Confidence scoring works by combining findings across various sources and assigning a clear confidence level. The skill evaluates official docs, CRM records, and external references to corroborate the evidence supporting the final answer.

Can I use this approach for customer success inquiries without manually checking each knowledge source?

Yes, you can use this approach for customer success inquiries without manual checks. The skill automates cross-referencing across docs, tickets, and knowledge bases, returning a structured synthesis with direct answers and recommended next steps.

What components are included in the structured synthesis returned for customer research?

The structured synthesis returned for customer research includes a direct answer, confidence level, supporting evidence, caveats, and recommended next steps. This format ensures researchers receive comprehensive, actionable context.