brain-ops

Read, enrich, and write knowledge base entries with source citations.

2|1|Updated Jun 16, 2026
One-click install
npx skills add https://github.com/bish-x/bx-gbrain --skill brain-ops-bish-x
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: brain-ops
Source: https://github.com/bish-x/bx-gbrain/tree/main/skills/brain-ops
Command: npx skills add https://github.com/bish-x/bx-gbrain --skill brain-ops-bish-x

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill facilitates the maintenance of an always-updated, contextual knowledge base, ensuring data accuracy and relevance across various interactions.

Core Features & Use Cases

  • Core Operations: Read, write, and enrich brain content, including entities like people, companies, and deals.
  • Brain-First Lookup: Prioritize brain knowledge over external sources, maintaining data consistency.
  • Read → Enrich → Write Loop: Ensures that every incoming and outgoing signal triggers relevant brain updates.
  • Source Attribution: Inlines citations for every piece of data written to the brain.
  • Back-Linking: Automatically creates back-links for referenced entities to ensure a robust network of knowledge.
  • Use Case: For an AI assistant handling inquiries about individuals or companies, this Skill ensures that the AI always consults the brain before responding, keeping the information current and well-connected.

Quick Start

Run the brain-ops skill to check and update the brain information on a specific individual, company, or event.

Frequently Asked Questions about brain-ops

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

FAQPage Schema
How do I maintain a live knowledge base with consistent context for AI assistants?

Maintaining a live knowledge base requires a brain-first lookup mechanism that prioritizes internal data over external sources. This skill uses a Read → Enrich → Write loop to trigger contextual updates, ensuring data accuracy and relevance across interactions.

What's the best way to ensure data consistency when an AI reads and writes to a knowledge repository?

To ensure data consistency during read-write operations, the system inlines source attribution citations for every piece of data written. It also automatically creates back-links for referenced entities to maintain a robust, well-connected knowledge network.

How does ambient enrichment work for updating knowledge base entities like people and companies?

Ambient enrichment works through a Read → Enrich → Write loop where every incoming and outgoing signal triggers relevant brain updates. This process updates knowledge base entities like people, companies, and deals with full contextual information.

Do I need any specific dependencies to run brain-ops for knowledge base maintenance?

You do not need any specific external dependencies to run brain-ops for knowledge base maintenance. The skill operates independently using its internal scripts to manage secure write operations and contextual data enrichment.

Can I use this approach to prioritize internal brain knowledge over external sources?

Yes, you can prioritize internal brain knowledge over external sources using the brain-first lookup feature. This mechanism ensures that the AI assistant always consults the brain before responding to inquiries about individuals or companies.

Why does my AI assistant provide outdated information about contacts and companies?

Your AI assistant provides outdated information because it lacks a continuous update loop. By implementing a Read → Enrich → Write cycle with automatic back-linking and source attribution, the knowledge base stays current, accurately representing people, companies, and deals.