SPEC‑1: CLEARGLASS Guardian Command Nexus

1. Purpose and Scope

The Guardian Command Nexus is the central command‑and‑control dashboard for CLEARGLASSINC’s GUARDIAN suite. It is a single‑page web application that provides operators with real‑time oversight of security workflows, simulated environments and system health. Its cyberpunk aesthetic hides a sophisticated architecture that orchestrates reactive state management, simulations, audit logging and AI‑driven command routing.

The purpose of this specification is to clearly define the initial production version, inform refactoring of the existing prototype, and provide a base for future extension. In scope are the modules already present in the current HTML artifact—shell kernel, reactive state fabric, simulation grid, audit ledger, operator routing and AI command orchestration—as well as their integration points. Out of scope are detailed implementation of third‑party integrations (e.g. PowerShell modules) or platform‑specific deployment scripts; these may be defined in later specs.

2. System Overview

The Command Nexus is architected as a client‑side SPA built with modern JavaScript (ES6+) and an application framework (assumed to be React or Vue given the prototype’s reactive state fabric). The application bootstraps a shell kernel that coordinates all subsystems and exposes a command bus to the UI. A state fabric holds canonical application state and broadcasts changes via events. A simulation grid synthesises sensor and environmental data at a configurable cadence to drive dashboards and AI reasoning. An audit ledger records all operator actions and system events with severity levels and metadata. AI command orchestration parses natural‑language intents from operators or connected systems and translates them into structured actions. Operator routing provides navigation between views (Dashboard, Pipeline, Surveillance, Tasks, AI Console, System) and orchestrates hotkeys and quick actions. The visual layer comprises responsive panels, charts and terminal components consistent with the cyberpunk console aesthetic.

The HTML front end communicates with back‑end services via internal APIs. For the initial version these may be mocked or stubbed; the specification assumes eventual REST or GraphQL endpoints for persistence (audit log export, state snapshots), AI inference and external data feeds. External systems (e.g. network scanners, SOC tools) will integrate through defined interfaces but are not implemented in this revision.

3. Core Requirements

3.1 Functional Requirements

• Dashboard view: Display high‑level metrics from the simulation grid and real operations. Operators can interact with widgets to drill down into pipeline tasks, surveillance feeds and incident timelines.
• Pipeline view: Visualise and manage workflows such as network scans, security automation or predictive analysis. Tasks move through stages with status indicators.
• Surveillance view: Present live or simulated sensor feeds (e.g. CCTV, network traffic). Operators can control playback and adjust filters.
• Tasks view: List assigned tasks, alerts and incidents with sorting and filtering. Operators can acknowledge, snooze or transfer tasks.
• AI console: Accept natural‑language commands, display parsed intents and proposed actions, and allow operators to confirm execution. Provide a transcript of AI conversations.
• System view: Show system health (CPU, memory, network) and log messages. Allow administrators to start/stop subsystems.
• Audit logging: Record all operator actions (navigation, confirmations, command executions), AI actions, and system events with timestamp, severity and context.
• State persistence: Persist state fabric snapshots and audit ledger entries to local storage or back‑end services. Support schema versioning to handle migrations.
• Simulation controls: Provide settings to adjust simulation cadence, toggle stochastic/deterministic mode and seed values.

3.2 Non‑Functional Requirements

• Performance: The dashboard should render initial content within 2 seconds on modern browsers and maintain 60 fps during interaction. Simulation updates should not block UI rendering.
• Reliability: The shell kernel must recover gracefully from subsystem failures. Unhandled exceptions should be captured by the audit ledger and displayed in the System view.
• Usability: The interface shall support keyboard navigation and screen‑reader labels. Hotkeys must not conflict with browser shortcuts.
• Maintainability: Code should be modularised by subsystem with typed interfaces. Event names and payload shapes should be centralised. Tests should cover reducers, command parsing and critical UI flows.
• Extensibility: New views and AI intents should be pluggable without changing core modules. The spec defines clear extension points for PowerShell integration and SOC workflows.

Implementation Priority

1. Core Framework and State Fabric: Establish the shell kernel, event bus, reducers, selectors and routing. Implement domain models and ensure persistence with schema versioning.
2. Simulation Grid and Dashboard: Build the simulation scheduler and sensor models, and render dashboard widgets. Provide controls for cadence and mode.
3. AI Command Orchestration: Implement the rule‑based parser, console UI and command execution flow with confirmation dialogues.

Note: This document is intentionally scoped from the provided specification content and preserved as a standalone, styled artifact for ClearGlassInc Artemis documentation.