| 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
- Register tasks with
schedule(task_id, optimal_phase, causal_deps)
- Call
current_phase() to determine active window
- Call
get_ready_tasks(current_phi) — returns tasks whose Φ threshold is met and deps satisfied
- 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.
