ethereal-sage-brain

Formalize SAGE Brain and Concierge operational protocols to prevent cross-path leakage.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

SAGE Brain operates as the central protocol that coordinates brain processing, tool execution, model routing, credit billing, context enrichment, persona, memory, and concierge tasks across the Ethereal workspace, and historically risks cross-path leakage between Concierge and Brain paths.

Core Features & Use Cases

  • Separate Concierge vs Brain paths to prevent cross-pollution between client-facing and artist-facing workflows.
  • Centralized governance of tool orchestration, memory updates, and billing with guardrails and anti-hallucination rules.
  • Auditable architecture map and failure-pattern documentation to reduce runtime errors and security risks.
  • Real-world use: deploying updates to the brain path without affecting concierge quality of service.

Quick Start

Review the Brain operational protocol and validate the Concierge and Brain paths remain correctly isolated during changes.

Frequently Asked Questions about ethereal-sage-brain

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

FAQPage Schema
How do I prevent cross-path leakage between client-facing and artist-facing AI agent workflows?

To prevent cross-path leakage, you must separate Concierge and Brain paths using strict sender_type checks. This isolation stops cross-pollution between client-facing and artist-facing workflows while maintaining secure multi-tenant access.

What is the best way to enforce mandatory credit billing after LLM calls in an AI agent?

To enforce mandatory credit billing after LLM calls, implement a centralized governance protocol that mandates recordAICost execution. This ensures accurate billing and tool orchestration alongside anti-hallucination guardrails.

How do you secure multi-tenant data access in an AI agent with complex tool execution?

You secure multi-tenant data access by applying Row Level Security (RLS) and strict guardrails within the agent's operational protocol. This prevents unauthorized data access across separate client and artist contexts.

Does this AI agent context management protocol support updating memory without affecting quality of service?

Yes, this protocol supports deploying updates to the brain path without affecting Concierge quality of service. It achieves this through separate context management paths and centralized memory governance.

Why do I need an operational protocol for AI agent memory management and model routing?

You need an operational protocol to prevent misrouting, reduce runtime errors, and govern tool execution across memory, model routing, and persona tasks. It provides an auditable architecture map and failure-pattern documentation to minimize security risks.