customer-research

Synthesize customer questions from multiple knowledge sources with confidence scoring.

7|Updated Feb 6, 2026
One-click install
npx skills add https://github.com/Epiphytic/ai-plugin-translator --skill customer-research-epiphytic
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: customer-research
Source: https://github.com/Epiphytic/ai-plugin-translator/tree/main/packages/core/test/fixtures/regression-output/knowledge-work-plugins/customer-support/skills/customer-research
Command: npx skills add https://github.com/Epiphytic/ai-plugin-translator --skill customer-research-epiphytic

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps customer-facing teams answer complex customer questions by systematically researching scattered information sources and synthesizing reliable responses with confidence levels.

Core Features & Use Cases

  • Multi-Source Investigation: Guides research across documentation, knowledge bases, CRM records, support history, communications, and external resources.
  • Confidence-Based Synthesis: Organizes findings, resolves contradictions, cites evidence, and communicates certainty levels before sharing answers.
  • Use Case: Support teams can investigate a customer's product question by combining account context, technical documentation, and previous interactions into a verified response.

Quick Start

Use the customer-research skill to investigate this customer question and provide a confidence-scored answer with supporting sources.

Frequently Asked Questions about customer-research

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

FAQPage Schema
How do I research customer support questions across multiple knowledge sources?

Research customer support questions by systematically investigating scattered knowledge bases, CRM records, and documentation. The skill synthesizes these multiple sources into reliable responses with confidence levels before sharing answers.

What's the best way to synthesize technical documentation and account context for product inquiries?

Synthesize technical documentation and account context by prioritizing information sources, resolving contradictions, and citing evidence. This approach combines account background research with product capability questions to generate verified technical inquiry responses.

Can I use confidence scoring to verify answers for complex customer investigations?

Yes, confidence scoring verifies answers for complex customer investigations. The skill assesses evidence certainty and communicates confidence levels while attributing sources, ensuring support teams share reliable responses backed by documented findings.

Does source synthesis work for resolving contradictions in scattered support history?

Source synthesis resolves contradictions in scattered support history by systematically prioritizing knowledge sources and attributing evidence. The skill organizes findings from documentation, communications, and CRM records to generate structured, verified answers.

How do I structure answer generation for technical inquiries with evidence attribution?

Structure answer generation for technical inquiries by applying systematic source prioritization and evidence attribution. The skill organizes research findings, assesses confidence, and generates structured responses that cite supporting documentation and account contexts.

When should I not rely on confidence-scored synthesis for customer research?

Avoid confidence-scored synthesis when knowledge sources are entirely unavailable or when customer questions require real-time system data rather than documentation-based research. The skill depends on accessible knowledge bases, CRM records, and support history to function effectively.