kb-retriever

Navigate hierarchical data_structure.md indices to retrieve answers from local knowledge bases.

10.2k|1.3k|Updated Apr 21, 2026
One-click install
npx skills add https://github.com/ConardLi/garden-skills --skill kb-retriever
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: kb-retriever
Source: https://github.com/ConardLi/garden-skills/tree/main/skills/kb-retriever
Command: npx skills add https://github.com/ConardLi/garden-skills --skill kb-retriever

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pdf2image, and includes scripts (resource) and references (resource) components.

What problem does it solve?

It enables AI agents to answer questions from a local, multi-format knowledge base without loading entire files, by using a hierarchical index and progressive retrieval.

Core Features & Use Cases

  • Hierarchical index navigation using data_structure.md at each level to target relevant documents.
  • Progressive retrieval that reads only small windows around matches and avoids full-file loads.
  • Mandatory learning steps for PDFs/Excel via references/*.md to select the right extraction tools before processing.
  • Default knowledge base location is knowledge/, with support for user-specified paths.

Quick Start

Instruct the agent to search your knowledge base in knowledge/ and answer the question with sources.

Frequently Asked Questions about kb-retriever

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

FAQPage Schema
How do I search a local knowledge base without loading entire PDF or Excel files into context?

You can search a local knowledge base without loading entire files by using a hierarchical data_structure.md index and progressive retrieval. This approach reads only small windows around grep matches, avoiding full-file loads into context.

How does progressive retrieval work for multi-format knowledge bases?

Progressive retrieval works by navigating hierarchical indices at each level to target relevant documents, then iteratively refining results across up to five rounds. It reads only small windows around matches and restricts full-file reads to extract information efficiently.

Do I need to preprocess PDFs and Excel files before searching my local knowledge base?

Yes, you need to complete mandatory learning steps via references/*.md files before processing. This pre-processing step ensures the agent selects the right extraction tools, like pdfplumber for PDFs and pandas for Excel, to extract information efficiently.

What's the best way to extract answers from a local multi-format document repository?

The best way to extract answers is using hierarchical index navigation with data_structure.md files to target relevant documents. This method uses grep, Read, pdfplumber, and pandas to iteratively refine results across up to five rounds while avoiding loading entire files.

Can I specify a custom directory path for my local knowledge base search?

Yes, you can specify a custom directory path for your local knowledge base search. While the default knowledge base location is the knowledge/ directory, the system supports user-specified paths to locate answers in different locations.

Why does my knowledge base search return irrelevant results from large documents?

Irrelevant results from large documents occur when full-file reads are not restricted. By enforcing progressive retrieval and hierarchical index navigation, the system reads only small windows around matches and iteratively refines results across up to five rounds to avoid this issue.