query

Query brain runtime database entries for documented project facts.

Updated Jun 10, 2026
One-click install
npx skills add https://github.com/starlink-awaken/omostation-gbrain --skill query-starlink-awaken
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: query
Source: https://github.com/starlink-awaken/omostation-gbrain/tree/main/test/fixtures/openclaw-reference-minimal/skills/query
Command: npx skills add https://github.com/starlink-awaken/omostation-gbrain --skill query-starlink-awaken

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the challenge of navigating large, fragmented knowledge bases by providing a direct interface to query specific brain pages within the OpenClaw reference system.

Core Features & Use Cases

  • Targeted Retrieval: Quickly locate information stored in the brain runtime without manual browsing.
  • Contextual Search: Use natural language triggers to find relevant documentation or knowledge snippets.
  • Use Case: When you need to recall specific architectural decisions or project facts, simply ask the system to look up the relevant page to get an immediate answer.

Quick Start

Use the query skill to search for information regarding the current project architecture.

Frequently Asked Questions about query

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

FAQPage Schema
How do I search and retrieve specific knowledge entries from a brain runtime database?

To search and retrieve knowledge entries from the brain runtime database, use an intent-based query interface to directly locate specific project facts and technical details without manual browsing.

What's the best way to look up documented architectural decisions in a TypeScript environment?

Looking up architectural decisions in a TypeScript environment is best handled by querying the brain runtime to instantly retrieve documented project facts and recall specific technical details.

Can I use natural language triggers to find relevant documentation in the OpenClaw reference framework?

Yes, you can use natural language triggers to find relevant documentation within the OpenClaw reference framework, enabling rapid access to targeted knowledge snippets and project facts.

How does knowledge retrieval work for navigating large, fragmented knowledge bases?

Knowledge retrieval for navigating large, fragmented knowledge bases works by providing a direct interface to query specific brain pages, solving the challenge of manual browsing across scattered information.

Does the query skill require any external dependencies to operate?

No, the query skill requires no external dependencies to operate, functioning independently within the OpenClaw reference framework to provide efficient knowledge retrieval.