concept-synthesis

Deduplicate and tier concept stubs into a structured intellectual map.

2|1|Updated Jun 16, 2026
One-click install
npx skills add https://github.com/bish-x/bx-gbrain --skill concept-synthesis-bish-x
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: concept-synthesis
Source: https://github.com/bish-x/bx-gbrain/tree/main/skills/concept-synthesis
Command: npx skills add https://github.com/bish-x/bx-gbrain --skill concept-synthesis-bish-x

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

The skill helps manage thousands of concept stubs by deduplicating them and synthesizing them into a structured intellectual map, tracing the evolution of ideas over time.

Core Features & Use Cases

  • Deduplication and Synthesis: Turns raw concept stubs into a curated intellectual fingerprint.
  • Tiering: Classifies concepts into Tiers (Canon, Developing, Speculative, Riff) based on frequency, mention span, and engagement.
  • Evolution Tracing: Shows how the concept evolved across different sources and time.
  • Intellectual Map: Organizes concepts into clusters and creates a master concepts/README.md with the full map.

Quick Start

Run the concept-synthesis skill on your brain to deduplicate and tier concept stubs into a structured intellectual map.

Frequently Asked Questions about concept-synthesis

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

FAQPage Schema
How do I deduplicate and organize thousands of raw concept stubs into a structured map?

Concept synthesis deduplicates raw concept stubs using Jaccard, substring, and semantic matching, then organizes them into a structured intellectual map. It classifies concepts into tiers and traces idea evolution across sources over time.

What is concept tiering and how does it classify ideas by engagement?

Concept tiering classifies ideas into Canon, Developing, Speculative, and Riff tiers based on frequency, mention span, and engagement. This scoring mechanism transforms raw concept stubs into a curated intellectual fingerprint.

How do I trace the evolution of ideas across different sources over time?

Idea evolution tracing maps how concepts develop across different sources and time periods. The synthesis process identifies concept clusters and generates a master README.md documenting the full intellectual map.

Can I use cluster analysis to group related concept stubs into an intellectual map?

Cluster analysis groups related concept stubs into organized clusters as part of the intellectual mapping process. The synthesis logic deduplicates concepts and structures them into a comprehensive map over time.

What is the best way to manage concept stubs and remove duplicate ideas from my notes?

Idea deduplication removes duplicate concepts from raw stubs using Jaccard similarity, substring matching, and semantic analysis. This synthesis process creates a curated intellectual fingerprint ready for tiering and mapping.

When should I not use automated concept synthesis for organizing my idea database?

Concept synthesis requires a large volume of concept stubs to be effective, as it relies on frequency and mention span for tiering. It is not suited for small datasets where manual organization is more efficient.