verify-idea

Detect semantic duplicate ideas in a personal knowledge base using embedding similarity with grep fallback.

12|2|Updated Jun 8, 2026
One-click install
npx skills add https://github.com/Loringtonian/second-brain-template --skill verify-idea
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: verify-idea
Source: https://github.com/Loringtonian/second-brain-template/tree/main/.claude/skills/verify-idea
Command: npx skills add https://github.com/Loringtonian/second-brain-template --skill verify-idea

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you avoid creating duplicate or near-duplicate ideas in your second brain by checking whether a concept is already captured elsewhere.

Core Features & Use Cases

  • Compares the core meaning of an idea, not just shared keywords.
  • Distinguishes exact duplicates, partial overlaps, and genuinely new ideas.
  • Falls back to keyword search when semantic matching is ambiguous.
  • Use it before adding a new note, project, or example so you can reuse an existing file or decide whether to merge.

Quick Start

Ask the skill to check whether your idea already exists in the second brain and return the most likely duplicate matches.

Frequently Asked Questions about verify-idea

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

FAQPage Schema
How do I check for duplicate ideas in my personal knowledge base?

To check for duplicate ideas, semantic embedding similarity scans your knowledge base to match core meanings rather than exact keywords. This detects exact duplicates, partial overlaps, and genuinely new concepts before you create a new note.

What is the best way to detect near-duplicate notes during idea intake?

The best way to detect near-duplicate notes is using semantic search, which compares the underlying meaning of your idea intake against existing entries. It returns clear duplicate, overlap, or not found verdicts.

How does semantic duplicate detection differ from keyword matching?

Semantic duplicate detection uses embeddings to compare the core meaning of ideas, unlike keyword matching. It distinguishes exact duplicates from partial overlaps, and uses a grep fallback when semantic matching is ambiguous.

Can I use grep fallback for duplicate detection when semantic search is uncertain?

Yes, you can use a grep fallback for duplicate detection when semantic search returns uncertain verdicts. The system automatically applies keyword search to verify potential matches across your second brain.

Why does semantic search return uncertain verdicts for some idea verification checks?

Semantic search returns uncertain verdicts when embedding similarity is ambiguous between existing knowledge base entries. This triggers a grep keyword fallback to manually verify potential duplicate matches.