chronoholographic-scheduler

name	chronoholographic-scheduler
description	Merges chronobiology, temporal reasoning engine, and AdS/CFT analogues for causal dependency resolution under legal-governance constraints.
version	1.0.0
category	AI
author	EVEZ-OS / Steven Vearl Crawford-Maggard

ChronoholographicScheduler Skill

Overview

Schedule cognitive tasks at biologically optimal circadian windows while resolving causal dependency chains via AdS/CFT boundary encoding analogues.

Use When

• Scheduling multi-step cognitive workflows
• Legal-governance constraint satisfaction (task ordering)
• Temporal reasoning engine stability optimization
• Any task where execution timing matters for outcome quality

Circadian Phase Map

Phase	Hours	Φ Target	Task Types
PEAK	09:00–12:00	0.95	High-complexity reasoning, legal analysis
RECOVERY	17:00–21:00	0.82	Pattern matching, synthesis
REST	21:00–06:00	0.60	Consolidation, archival
TROUGH	14:00–15:00	0.45	Simple retrieval only

Workflow

1. Register tasks with schedule(task_id, optimal_phase, causal_deps)
2. Call current_phase() to determine active window
3. Call get_ready_tasks(current_phi) — returns tasks whose Φ threshold is met and deps satisfied
4. Execute in order; update update_stability(phi) after each

Implementation

from src.rqns.chronoholographic import ChronoholographicScheduler, CircadianPhase
sched = ChronoholographicScheduler()
sched.schedule("legal_analysis", CircadianPhase.PEAK, phi_threshold=0.9)
ready = sched.get_ready_tasks(current_phi=0.92)

AdS/CFT Analogue

The causal dependency graph is the 'boundary'. Resolve boundary constraints first, then propagate solutions to interior task states. Never execute an interior task before its boundary (dependency) tasks complete.