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kb-retriever

Search local knowledge directories for answers using hierarchical indexes and progressive retrieval.

1|Updated Aug 16, 2023
Search Tags:#pdf processing#local knowledge base#data indexing#hierarchical indexing#progressive retrieval
One-click install
npx skills add https://github.com/monlor/dotfiles --skill kb-retriever-monlor
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: kb-retriever
Source: https://github.com/monlor/dotfiles/tree/main/config/ai/agents/skills/kb-retriever
Command: npx skills add https://github.com/monlor/dotfiles --skill kb-retriever-monlor

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires grep, read_file, pdftotext, pdfplumber, pandas, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill streamlines AI agents' ability to answer questions based on a local, multi-format knowledge directory, eliminating the need for loading entire files into context.

Core Features & Use Cases

  • Multi-format Support: Works with Markdown, PDF, Excel, and more, adaptable for various file types.
  • Hierarchical Indexing: Navigates through a hierarchical index structure in data_structure.md for precise searches.
  • Progressive Retrieval: Uses grep and selective file reading to efficiently search for answers without overwhelming context.
  • Use Case: Retrieve specific information from a complex knowledge directory stored on local storage, allowing for more efficient decision-making and knowledge utilization.

Quick Start

Load your local knowledge base and activate the skill 'kb-retriever'. Then ask your AI, "Provide information from the knowledge base on topic 'Project Management'."

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 full PDF and Markdown files into context?▼

Search a local knowledge base without loading full files by using progressive retrieval to navigate a hierarchical index in data_structure.md, then selectively reading specific data structures to find precise answers efficiently.

Can AI agents retrieve specific information from mixed file formats like PDF and Excel?▼

AI agents can retrieve specific information from mixed formats like PDF and Excel by applying file and tool-specific reading strategies, adapting processing logic for each format without overwhelming the context window.

What is hierarchical indexing for local data indexing and how does it work?▼

Hierarchical indexing for local data indexing works by mapping a structured knowledge directory into a data_structure.md file, allowing searches to progressively navigate the hierarchy to locate exact answers without scanning entire documents.

Does progressive retrieval work with grep and selective file reading for local directories?▼

Progressive retrieval works with grep and selective file reading by first searching the hierarchical index structure, then using targeted tool-specific strategies to extract exact answers from local directories efficiently.

What are the limitations of using hierarchical indexing for complex knowledge directories?▼

A limitation of hierarchical indexing for complex knowledge directories is the requirement for a structured data_structure.md file, meaning unstructured local data must be pre-processed and indexed before progressive retrieval can function.

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