synapse

Inject contextual rules into AI prompts through an 8-layer processing pipeline.

Updated May 27, 2026

Search Tags:#workflow #context #orchestration #governance #prompt-engineering #ai-agents

Ready to run

npx skills add https://github.com/bychrisr/now-company --skill synapse-bychrisr

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: synapse
Source: https://github.com/bychrisr/now-company/tree/main/.claude/skills/synapse
Command: npx skills add https://github.com/bychrisr/now-company --skill synapse-bychrisr

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and assets (resource) components.

What problem does it solve?

This Skill solves the challenge of maintaining consistent, context-aware AI behavior across complex business workflows by providing a unified, rule-based engine that injects relevant instructions into every prompt.

Core Features & Use Cases

8-Layer Context Engine: Automatically manages rules ranging from core constitutional principles to specific task-based instructions.
Dynamic Context Adaptation: Adjusts the volume and priority of injected rules based on the remaining context window to ensure optimal performance.
Agent & Workflow Scoping: Automatically activates specific domains based on the active agent or workflow, ensuring the AI always has the right instructions for the job.

Quick Start

Use the synapse skill to check the current status of the context engine and verify active domains.

Frequently Asked Questions about synapse

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

FAQPage Schema

What is context window optimization for AI agents?▼

Context window optimization manages the volume and priority of contextual rules injected into AI prompts to ensure optimal performance within remaining token limits. This Skill uses an 8-layer processing pipeline to dynamically adapt these instructions based on available context window capacity.

How do I maintain consistent business logic across multi-agent orchestration?▼

Multi-agent orchestration maintains consistent business logic by using a unified, rule-based engine to inject relevant instructions into every prompt. This Skill applies agent and workflow scoping to automatically activate specific domains based on the active agent or workflow.

How do I configure domain-specific rules for AI prompt engineering?▼

Domain-specific rules for AI prompt engineering are configured through CRUD-based configuration of agent behaviors. This Skill provides an 8-layer context engine ranging from core constitutional principles to specific task-based instructions for managing these injected rules.

Does this context orchestration approach work for state-aware workflows?▼

Yes, context orchestration works for state-aware workflows by applying governance and state-aware prompt engineering. The engine automatically adjusts injected rules based on the active agent or workflow, ensuring the AI receives the correct instructions for its current state.

What is the best way to manage workflow governance for AI agents?▼

Workflow governance for AI agents is best managed by injecting contextual rules into prompts through a structured processing pipeline. This Skill provides dynamic context adaptation and agent scoping to ensure the AI follows governance requirements across complex business workflows.

Why does my AI agent lose context in complex workflows?▼

AI agents lose context in complex workflows when contextual rules are not dynamically managed or scoped correctly. This Skill solves this by using an 8-layer context engine that automatically activates specific domains based on the active agent or workflow, maintaining consistent behavior.