Compact Notation for Grok-Powered Agent Systems
Aglyphs is a compact symbolic notation that lets you describe complex AI agent systems in a single line. Built for Grok and modern agent workflows.
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Aglyphs lets you describe complex AI agent architectures, teams, memory systems, and workflows in **one compact line** β perfect for docs, code comments, whiteboards, and GitHub READMEs.
Why We Need Better Notation
Most of us currently describe agent systems with long paragraphs, messy diagrams, or code. None of these scale well when youβre working with complex teams of agents.
Aglyphs solves this by giving us a clean, text-native way to express architectures that would normally take dozens of lines to explain.
Core Primitives
The system is built on a small set of primitives:
`πΎ` β Grok Agent
`β¨` β Agentic Operator (supervisor)
`π` β Memory (`πΛ’`, `πΛ‘`, `πα΅`)
`β` β Reflection
`β` β Human-in-the-Loop
Examples:
Basic React Agent:
πΎ[ΞΛ£ β π] (β β Ξ β β β β·) β³Grok as Central Operator:
β¨(πΎ) β {πΈβ[research + πα΅], πΈβ[execution + π], πΈβ[analysis]}Production Loop with Human Approval
πΎ[ΞΛ£] β β¨ β (β β β β β β β·) β³Get Started
The full notation specification, comparison with other methods, and contribution guidelines are available in the repository:
β github.com/rb-thompson/aglyphs
Iβm excited to see what patterns the community creates with it. If you build something interesting using Aglyphs, feel free to open a PR or reach out.