bkn-domain

Identify business text domains with scoring and confidence outputs.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/kweaver-ai/kweaver-dip --skill bkn-domain
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bkn-domain
Source: https://github.com/kweaver-ai/kweaver-dip/tree/main/skills/bkn-creator/internal/bkn-domain
Command: npx skills add https://github.com/kweaver-ai/kweaver-dip --skill bkn-domain

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Automates the task of identifying the functional domain from business text by applying a scoring model across predefined domains, enabling faster routing and domain-specific processing.

Core Features & Use Cases

  • Keyword extraction and weighted signals across domains to produce a top domain score.
  • Normalized scoring with rules to determine high-confidence matches and provide evidence for decisions.
  • Use Case: classify customer PRDs, emails, and tickets into domains like supply_chain, crm_sales, or project_delivery to route to the correct pipeline.
  • Example: Given a product requirement document, returns top_domain: "supply_chain" with a normalized_top around 72 and a confidence level.

Quick Start

Provide the most likely domain for the input business text using the scoring rules.

Frequently Asked Questions about bkn-domain

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

FAQPage Schema
How do I identify the business domain of unstructured text like emails or tickets?▼

To identify the business domain of unstructured text like emails or tickets, the Skill applies a scoring-based approach using weighted keyword signals across predefined domains to return a top match and confidence score.

What is score-based domain recognition for business text?▼

Score-based domain recognition is a technique that evaluates business text against predefined domains using weighted signals to produce a normalized score, determining the most likely functional domain such as supply chain or CRM sales.

How to classify product requirement documents into functional domains?▼

To classify product requirement documents into functional domains, provide the text to the scoring model which evaluates keyword signals and outputs the top domain, a normalized score, and evidence for downstream pipeline routing.

Can I use confidence scores to route tickets to specific pipelines?▼

Yes, you can use confidence scores to route tickets to specific pipelines because the output includes a normalized top score and evidence suitable for determining high-confidence matches and directing downstream processing.

What predefined domains are supported for text classification?▼

The text classification supports predefined domains such as supply_chain, crm_sales, and project_delivery, applying weighted scoring rules to determine the most likely domain match from the provided business text.