nshkr-ai-agents

TRINITY in Elixir (An Evolved LLM Coordinator): route LLM calls via a small-model hidden-state router + Axon coordination head, with Thinker/Worker/Verifier orchestration and policy loop for acceptance-driven completion.

Headless, declarative multi-agent orchestration framework with a domain-agnostic signal bus, workflow engine with Postgres persistence, and configurable agent runtime (ships code review domain).

Asset-first data orchestration for Elixir/BEAM. Dagster-inspired with OTP fault tolerance, LiveView dashboard, lineage tracking, checkpoint gates, and distributed execution via Oban.

Declarative Self Improving Elixir - DSPy Orchestration in Elixir

DSPEx - Declarative Self-improving Elixir | A BEAM-Native AI Program Optimization Framework

Claude Code + Gemini AI collaboration orchestration tools

Multi-agent systems framework for the BEAM platform - build distributed autonomous agents with OTP supervision and fault tolerance

The Agent & Tool Arbitration Protocol

Phoenix coordination server and embeddable Elixir client for augmented human-AI telepathy. Transforms multiplayer terminal chat into live, room-scoped structured context graphs and actionable consensus workflows.

FlowStone integration for altar_ai - AI-powered data pipeline assets with classify_each, enrich_each, embed_each helpers and unified telemetry

Synapse integration for altar_ai - SDK-backed LLM providers for multi-agent workflows with automatic fallback, signal handlers, and workflow actions

An advanced Elixir-based AI coding agent focused on full-stack code generation, orchestration, and intelligent source code management.

First proving-ground product app for the nshkr stack: a thin, sophisticated operations surface above AppKit that configures a generalized AI-work business engine, coordinates multi-agent execution across local and remote infrastructure, and turns distributed agent operations into a secure operator product.

Neutral high-level reusable monorepo for the nshkr stack: Ash-driven business semantics, configurable workflow machinery, operational state models, and reusable application logic above AppKit and below proving-ground products, built to run global AI operations across distributed clusters through pure effects projected to execution_plane.