customer-research

Synthesize customer questions into confidence-scored answers with citations from documentation and knowledge bases.

Updated Mar 15, 2026
One-click install
npx skills add https://github.com/lilbom32/ketnoitrithuc --skill customer-research-lilbom32
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: customer-research
Source: https://github.com/lilbom32/ketnoitrithuc/tree/main/.claude/skills/customer-support/1.1.0/skills/customer-research
Command: npx skills add https://github.com/lilbom32/ketnoitrithuc --skill customer-research-lilbom32

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps researchers gather and synthesize information from multiple sources to deliver accurate, confidence-scored answers for customer questions.

Core Features & Use Cases

  • Multi-source research across documentation, knowledge bases, and CRM data to build comprehensive answers
  • Explicit citations and a transparent confidence level to support decision-making
  • Escalation-ready outputs for unresolved questions and gaps in knowledge

Quick Start

Ask the AI to perform a multi-source research pass across documents, knowledge bases, and connected sources, then synthesize a confidence-scored answer.

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 research from multiple knowledge bases and CRM data?

Synthesize customer research by searching across documentation, knowledge bases, and CRM data to aggregate and reconcile multiple sources into a confidence-scored answer. The tool enforces source prioritization and explicit citations for transparent decision-making.

What is the best way to answer customer inquiries when information is spread across disconnected sources?

Answer customer inquiries by performing a multi-source research pass across connected documents and knowledge bases. The tool reconciles conflicting information, applies source prioritization, and generates an escalation path when policy questions cannot be resolved.

How does confidence scoring work for multi-source synthesized answers?

Confidence scoring evaluates the reconciled information from connected sources to produce a transparent confidence level. It enforces source prioritization and explicit citations, ensuring the final account context output clearly indicates the reliability of the synthesized answer.

Can I use multi-source synthesis for unresolved policy questions and knowledge gaps?

Multi-source synthesis handles unresolved policy questions by generating escalation-ready outputs. When information cannot be reconciled across knowledge bases and CRM data, the tool explicitly identifies gaps and provides a defined escalation path rather than forcing a low-confidence answer.

What's the best way to reconcile conflicting documentation when researching account context?

Reconcile conflicting documentation by applying a defined source prioritization during the research pass. The tool aggregates data from connected sources, weighs them according to priority rules, and outputs a confidence-scored answer with explicit citations for account context.

Do I need connected CRM data to generate confidence-scored answers for customer questions?

Connected CRM data is not strictly required but significantly enhances the accuracy of confidence-scored answers for customer inquiries. The tool searches across available documentation and knowledge bases, synthesizing whatever connected sources are present to build comprehensive responses.