The Agent Specifications define a comprehensive framework for building, deploying, and governing intelligent software agents capable of assisting with complex tasks, automating workflows, and supporting human decision-making. These specifications provide the foundations needed for reliable AI agents, including execution environments, knowledge retrieval, memory systems, reasoning capabilities, workflow management, security controls, interoperability, and transparency mechanisms. Together, they enable developers to create AI systems that can understand objectives, access relevant information, perform structured actions, and maintain accountability throughout their operation.
Designed for modular, local-first, and extensible AI ecosystems, these specifications support both specialized task agents and the infrastructure required to operate them at scale. They emphasize human oversight, verifiable outputs, secure tool usage, provenance tracking, and responsible autonomy. By separating intelligence workflows from underlying infrastructure layers, they allow organizations to build adaptable AI systems that can evolve over time while reducing vendor lock-in and improving reliability, privacy, and control.
All specifications are released under the GNU Affero General Public License v3.0 or later (AGPL-3.0+) and may be freely used, modified, and distributed with the required attribution provisions outlined in Section 7 of the license. Organizations seeking attribution-free commercial deployment may obtain a Specification Branding License (SBL), with licensing terms and pricing based on the specification category, deployment scope, usage scale, and the size of the network or organization utilizing the specification.
AuthenticAI
https://roxanneardary.com/authenticai/
An AI governance and identity framework for managing AI agents as controlled entities with permissions, tool access, monitoring, audit trails, and policy enforcement.
Axis Intelligence
https://roxanneardary.com/axis-intelligence/
A personal AI assistant workflow combining conversational intelligence, memory, retrieval, and reasoning. It provides a persistent assistant experience that can understand context, manage interactions, and assist with ongoing personal workflows.
BridgeBuddy
https://roxanneardary.com/bridgebuddy/
A single AI assistant workflow designed to guide users through complex processes. The agent interprets user needs, provides step-by-step guidance, retrieves relevant information, manages workflow progress, and helps users complete tasks through conversational interaction.
CivicOS AI
https://roxanneardary.com/civicos-ai/
An AI operating system architecture designed for autonomous systems, combining agent workflows, memory, tools, plugins, governance controls, and human approval mechanisms.
Cognitive Orchestration Stack (COS)
https://roxanneardary.com/cognitive-orchestration-stack/
An orchestration architecture for coordinating AI capabilities including reasoning, memory, retrieval, and execution. It provides the workflow coordination layer required for advanced AI agents.
EnerAgent
https://roxanneardary.com/eneragent/
An energy management AI agent workflow designed to analyze energy data, forecast demand, optimize usage, and support automated energy decisions for smart energy environments.
HelmOS
https://roxanneardary.com/helmos/
An AI agent operating layer focused on controlled autonomy. It provides intent verification, agent governance, execution controls, trust management, and auditable agent behavior.
Horizon Runtime
https://roxanneardary.com/horizon-runtime/
An AI execution runtime designed for scalable inference, multimodal workloads, adaptive computation, and the infrastructure required to operate advanced AI agents.
LatticeOS
https://roxanneardary.com/latticeos/
An AI system architecture designed around connected intelligence components, knowledge management, memory, and contextual reasoning for adaptive agent environments.
MachinaCore
https://roxanneardary.com/machinacore/
A foundational AI infrastructure specification providing core building blocks required for intelligent systems. It supports model execution, modular AI components, reasoning systems, and the underlying architecture needed to power AI agents.
Open Intelligence Stack
https://roxanneardary.com/open-intelligence-stack/
A governance-first AI architecture that organizes intelligence systems into modular components with provenance, evidence tracking, accountability, and human oversight.
PolyConnect
https://roxanneardary.com/polyconnect/
An interoperability layer enabling AI agents and intelligent systems to communicate across different platforms, models, services, and environments.
PublicStack AI
https://roxanneardary.com/publicstackai/
An AI infrastructure specification focused on discovering, evaluating, and assembling open technology components. It supports AI agents that research, analyze, and construct software stacks.
RAGBase
https://roxanneardary.com/ragbase/
A retrieval-augmented generation foundation for AI agents. It provides knowledge retrieval capabilities, document processing, embeddings, contextual search, and grounding mechanisms that allow agents to access external information.
RightGuide
https://roxanneardary.com/rightguide/
A specialized AI legal guidance agent workflow that analyzes user questions, applies structured reasoning, retrieves relevant information, and assists users through legal research and decision-support processes.
ScriptFlow
https://roxanneardary.com/scriptflow/
A creative AI agent workflow focused on storytelling and content development. It assists with narrative planning, character development, structure, and creative generation workflows.
Securekit
https://roxanneardary.com/securekit/
A security infrastructure layer for AI systems providing sandboxing, secure execution, authentication, and protection for AI agent tools and workflows.
Semantic Firewall
https://roxanneardary.com/semantic-firewall/
A privacy and security layer that protects sensitive information while allowing AI agents to process, reason, and interact with protected data.
Stratum
https://roxanneardary.com/stratum/
Stratum is an AI governance layer for MCP systems that controls agent execution through permissions, policy enforcement, context filtering, approval workflows, sandboxing, and audit logging. It provides a trusted boundary between AI intent and real-world actions, ensuring autonomous systems operate with structure, accountability, and transparency.
TraceCommons
https://roxanneardary.com/tracecommons/
A provenance and observability infrastructure specification for AI systems. It records agent actions, data sources, decisions, and execution history to improve transparency and accountability.
A Specification Branding License can be purchased for the basket of Provenance Specs
Provenance Specifications Basket Pricing:
| Network Size | # of Users | One-Time Price | Duration |
| Small | 1 – 20 | $700,000 | Perpetual License |
| Medium | 21- 1000 | $4,400,000 | Perpetual License |
| Large | 1001 + | Custom Quote | Custom Quote |
