ai-governance-layer

CHAP, the Collaborative Human Agent Protocol, is a MCP/A2A-compatible runtime for auditable human-agent work: approvals, overrides, handoffs, escalation and verifiable evidence logs.

Mapping intelligence for enterprise data migrations: schema mapping, lineage, and transformation traceability that compounds across every project

The ultimate agent productivity system - 32+ skills with intelligent recommendations, risk-based planning

Read-only mongosh checks that measure how many agents in a LibreChat deployment would fail a delegation policy review: capability held without stated bounds, reach beyond the author, revisions nobody approved. Reports audit coverage too -- lifecycle events that happened against records kept of them. Aggregate output only. Submissions welcome.

A practical repository showcasing guardrails for AI and LLM agents, including input/output validation, jailbreak protection, prompt security, and agent safety techniques to build secure and reliable AI systems.

Building a transparency model & badging tool.

Oblivion / the-recursive-threshold. When AI starts helping build the AI that comes next: recursive self-improvement, autonomous agents, cyber risk, nuclear stability, and the control gap. Bardiya Shokri

Practical frameworks, assessment guides, testing procedures, checklists, and templates for AI governance and assurance.

Oversight is an open standard for governing AI agents in production to make them safe, stoppable, and auditable.

2nd-line independent model validation harness for NLP/LLM claims triage systems

Signed, offline-verifiable records for AI models. Open standard, Apache 2.0.

an innovation initiative to build comprehensive physcian clinical reasoning simulation model for all medical specialties integrated with EHR in health organization