reduce

Extract structured domain notes, tensions, and open questions from source documents.

Updated Feb 26, 2026
One-click install
npx skills add https://github.com/shakedfb/deterministic-agentic-sdlc-workflow --skill reduce-shakedfb
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: reduce
Source: https://github.com/shakedfb/deterministic-agentic-sdlc-workflow/tree/main/.claude/skills/reduce
Command: npx skills add https://github.com/shakedfb/deterministic-agentic-sdlc-workflow --skill reduce-shakedfb

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manual extraction of domain insights from source materials is time-consuming, error-prone, and difficult to scale. This Skill automates structured extraction to build a retrievable knowledge vault.

Core Features & Use Cases

  • Automated extraction of core domain notes from diverse sources (docs, meeting notes, design docs)
  • Enrichment detection to augment existing notes with new evidence, examples, or framing
  • Open questions and tension notes to capture unresolved topics and trade-offs
  • Cross-linking to existing topic maps to maintain navigable, connected knowledge

Quick Start

Provide a source document to start extracting structured domain notes and review the resulting outputs before updating the vault.

Frequently Asked Questions about reduce

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

FAQPage Schema
How do I extract structured domain knowledge from raw source documents?

To extract structured domain knowledge from raw sources, provide your documents to the Skill. It processes docs, design notes, and code comments to generate retrievable vault notes, enrichment tasks, and open questions automatically.

What is the best way to automate building a knowledge vault from meeting notes?

Automating a knowledge vault from meeting notes involves classifying extracted insights into core notes, tensions, and validations. This Skill targets domain-relevant materials and performs duplicate detection against existing vault notes to maintain structure.

How does duplicate detection work when enriching an existing notes vault?

Duplicate detection for an existing notes vault works by cross-linking extracted source material against your current topic maps. The Skill identifies overlaps to augment existing notes with new evidence rather than creating redundant entries.

Can I capture unresolved trade-offs and open questions from design docs?

You can capture unresolved trade-offs and open questions from design docs by using this extraction process. It specifically categorizes output into tension notes and open questions, separating unresolved topics from core domain notes.

Do I need to review the extracted domain notes before updating my vault?

You need to review the extracted domain notes before updating your vault. After providing a source document, you review the resulting classified outputs, including validations and enrichment tasks, to ensure accuracy before integration.