A platform for building reliable AI agents

zer0dex is a local dual-layer memory pattern for AI agents: a compressed, human-readable markdown index plus a vector store queried automatically before each message. Built for cross-project recall and cross-reference where flat memory files or vector-only RAG fall short. Local-first, low-latency. Reference implementation by Hermes Labs.

lintlang is a static linter for AI agent configs, tool descriptions, and system prompts that runs zero-LLM quality gating in CI. Catches language-level failures (vague tool descriptions, missing stop conditions, schema gaps) before they reach runtime, with deterministic regex + structural detectors and no model calls.

The open-source MultiAgentOps evaluation and verification harness for any industry business workflow.

Open-source AI model evaluation and benchmarking framework for LLMs (OpenAI, Ollama, Claude, Gemini)

Turn failed AI agent runs into replayable regression tests. Catch regressions before you ship.

The "Cloudflare for AI Agents". 7-layer security interceptor, real-time observability dashboard, and automated reliability testing for MCP and AI tool chains. Prevent hallucinations, prompt injection, and destructive tool calls.

Production-grade TypeScript AI runtime focused on reliability, governance, and reproducible LLM systems. Multi-provider gateway, agents, RAG, workflows, policy engine, audit trails, and deterministic testing — built for teams shipping AI in production.

MCP server for the Ejentum API. 8 cognitive operations across 4 harnesses (reasoning, code, anti-deception, memory) in dynamic and adaptive modes.

Failure Compiler for AI agents: turn failed outputs into replayable regression cases.

Architectural standards and best practices for building reliable AI Agents and LLM workflows. Defining the framework for AI Reliability Engineering (AIRE).

Context-compensation scaffold for LLM evaluation prompts. A short language prefix you prepend so the model discloses prior exposure, scores on quoted evidence only, and hedges on thin evidence — for scorers that can see your CLAUDE.md, memory, or session context. Backend-agnostic. Experimental: variance-reduction effect not yet measured.

AION Scaffold — Intelligent tree-to-filesystem generator. Built by Sheldon K. Salmon, AI Reliability Architect. Part of the AION Constitutional Stack. Free forever. No tracking.

Sheldon K. Salmon — AI Reliability Architect. Creator of the AION Constitutional Stack and the CERTUS certainty‑engineering methodology. He designed, directed, and red‑teamed VERITAS — applying epistemic scoring, Uncertainty Mass, and permanent STP seals to community crisis data. Code is open source. The judgment is not.

quick-gate-js (npm: quick-gate) is a deterministic JS/TS CI quality gate that unifies ESLint, TypeScript, build, and Lighthouse checks into one fail-fast result, with bounded auto-repair and structured escalation evidence for humans or agents. Works with Next.js, React, Vue, Svelte, or any Node project. A gate-and-escalate wrapper, not a dashboard.

Benchmark for evaluating advanced reasoning, recursive dependency resolution, and robustness capabilities of large language models in dynamic, noisy, and structurally challenging environments.

Dual-Ring Gate — a Hermes Agent skill that makes self-checks impossible to skip. Shell gate + Prompt gate + dynamic rule lifecycle.

hermeneutic is an evidence-first drift gate for AI agents. It mines corrections from your AI chat logs (prior response, user correction, repair), classifies the drift, and runs a cheap-to-expensive pre-flight gate on the next response before drift ships. Regex, then structured scoring, then a pressure probe. MIT, zero dependencies, by Hermes Labs.

Research archive — eight published papers, Mahdi Ledger, and empirical foundations of the LC-OS governance framework.

ByteStack Labs marketplace for Claude Code. Open reliability skills that audit AI which passes evaluation but fails in production. Every number reproducible.