context-guardian

Extract and store user facts, decisions, and entities into a searchable knowledge base.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/zkksdk/skills --skill context-guardian-zkksdk
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: context-guardian
Source: https://github.com/zkksdk/skills/tree/main/skills/context-guardian
Command: npx skills add https://github.com/zkksdk/skills --skill context-guardian-zkksdk

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Context switching during conversations and maintaining a reliable, searchable knowledge base is challenging; this Skill automatically tracks dialogue, extracts user facts, decisions, and entities, and stores them for on-demand retrieval.

Core Features & Use Cases

  • Automatic context tracking: continuously monitor conversations and capture relevant facts, decisions, and entities.
  • Knowledge repository: store entries under facts/, decisions/, entities/, and conversation archives for quick lookup.
  • On-demand retrieval: fetch matched knowledge when needed to inform ongoing interactions and decisions.

Quick Start

Invoke the context-guardian in a session and let it automatically extract and index knowledge as you converse.

Frequently Asked Questions about context-guardian

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

FAQPage Schema
How do I track conversation context and extract entities automatically?

To track conversation context across multi-turn dialogues, this Skill continuously monitors interactions to automatically capture user facts, decisions, and extracted entities. It stores entries for on-demand retrieval to inform ongoing interactions.

What is the best way to build a searchable knowledge base from chat history?

Building a searchable knowledge base from chat history is done by automatically extracting facts, decisions, and entities from multi-turn conversations. Captured knowledge is structured under facts/, decisions/, entities/, and conversation archives for quick lookup.

How does automatic knowledge retrieval work for ongoing conversations?

Automatic knowledge retrieval works by fetching matched facts, decisions, and entities from a structured knowledge repository to inform ongoing interactions. It continuously monitors multi-turn conversations and retrieves relevant stored knowledge on demand.

Can I store extracted decisions and facts in structured directories?

Yes, extracted decisions and facts can be stored in structured directories. The Skill applies automatic extraction rules to organize captured knowledge into workspace/knowledge subdirectories including facts/, decisions/, entities/, and conversations/ for structured storage.

Do I need any external dependencies to manage conversation context?

No external dependencies are required to manage conversation context. The Skill operates independently with no dependencies to automate context tracking, knowledge extraction, and storage into a searchable knowledge base without needing additional components.