wiki-index-qmd

Index semantic chunks into QMD collections for local hybrid search.

2|1|Updated Mar 18, 2026

Search Tags:#research #indexing #rag #article #local-search #qmd #semantic-chunks

Ready to run

npx skills add https://github.com/cdeistopened/skill-stack-skills --skill wiki-index-qmd

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: wiki-index-qmd
Source: https://github.com/cdeistopened/skill-stack-skills/tree/main/wiki-pipeline/wiki-index-qmd
Command: npx skills add https://github.com/cdeistopened/skill-stack-skills --skill wiki-index-qmd

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Index semantic chunks into QMD to enable local hybrid search for article research and RAG queries.

Core Features & Use Cases

Index chunks into a wiki-index-qmd-transcripts collection for rapid retrieval.
Support hybrid search combining BM25 and vector similarity for topic exploration.
Use during offline research to prototype and refine agent prompts before production.

Quick Start

Index the local chunks found in data/chunks/ into a wiki-index-qmd-transcripts collection using the QMD CLI.

Frequently Asked Questions about wiki-index-qmd

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

FAQPage Schema

How do I index semantic chunks for local research and RAG queries?▼

You can index semantic chunks for local research by placing properly formatted JSON files into the data/chunks/ directory and using the QMD CLI to boot the indexing process. This builds a local collection for private retrieval.

What is hybrid search and how does it work for article retrieval?▼

Hybrid search for article retrieval combines BM25 keyword matching with vector similarity to find relevant semantic chunks. This approach improves topic exploration by balancing exact term matching with contextual meaning.

Does local RAG indexing work offline for private data handling?▼

Yes, local RAG indexing works offline for private data handling by keeping all chunks and search processes on your local machine. It requires no external network calls, ensuring data privacy during retrieval and iteration.

Do I need the QMD CLI to index semantic chunks locally?▼

Yes, you need the QMD CLI installed to boot the indexing and search processes. The workflow relies on the CLI to read chunks from data/chunks/ and build the searchable local collection.

How do I set up JSON chunks for local indexing?▼

To set up JSON chunks for local indexing, format your semantic chunks as proper JSON files and place them in the data/chunks/ directory. The QMD CLI will read this directory to index the chunks into the collection.

Can I use local semantic search to prototype agent prompts offline?▼

Yes, you can use local semantic search to prototype and refine agent prompts offline before production. The hybrid search retrieval allows rapid iteration on RAG queries without requiring cloud infrastructure.