heady-agent-runtime

Orchestrate distributed HeadyBee agents with phi-scaled quotas and CSL scheduling.

1|Updated Mar 24, 2026
One-click install
npx skills add https://github.com/HeadyAI/heady-context --skill heady-agent-runtime
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: heady-agent-runtime
Source: https://github.com/HeadyAI/heady-context/tree/main/heady-skills/heady-agent-runtime
Command: npx skills add https://github.com/HeadyAI/heady-context --skill heady-agent-runtime

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Agent process runtime treating HeadyBee agents as first-class distributed workloads with phi-scaled resource quotas, CSL-scored preemptive scheduling, V8-isolate fault domains, and control-plane orchestration. Each bee receives CPU/memory/token budgets from Sacred Geometry pools (Hot 34%, Warm 21%, Cold 13%, Reserve 8%). Higher-coherence tasks preempt lower ones. Agents follow a six-state lifecycle (SPAWNING → READY → RUNNING → SUSPENDED → RETIRING → TERMINATED). Fault domains group agents by Sacred Geometry layer so failures never cascade cross-layer. The control plane tracks 89+ bee types, auto-decomposes complex tasks into sub-agent DAGs, and triggers semantic backpressure when quotas are exceeded.

Core Features & Use Cases

  • Six-state agent lifecycle (SPAWNING → READY → RUNNING → SUSPENDED → RETIRING → TERMINATED)
  • Phi-math based resource pools with per-bee budgets
  • CSL-scored preemptive scheduling prioritizing higher-coherence tasks
  • Fault-domain isolation across Sacred Geometry layers
  • Dynamic task decomposition into sub-agent DAGs and backpressure when quotas are reached

Quick Start

Spawn a new HeadyBee agent by sending a spawn request with the bee type and resource pool.

Frequently Asked Questions about heady-agent-runtime

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is preemptive scheduling for distributed agent fleets?▼

Fault-domain isolation groups distributed agents by Sacred Geometry layers so failures never cascade cross-layer. This V8-isolate based approach prevents faults in one layer from affecting agents in another layer.

How do I manage the lifecycle of a distributed agent from spawning to termination?▼

Resource allocation constraints trigger semantic backpressure when agents exceed their allocated phi-scaled CPU, memory, or token quotas. The system enforces these limits by suspending lower-coherence tasks to maintain pool stability.

Does this agent runtime support automatic decomposition of complex tasks into sub-agents?▼

Yes, the agent runtime supports automatic task decomposition. The control plane auto-decomposes complex tasks into sub-agent directed acyclic graphs (DAGs), distributing workloads across 89+ bee types within Sacred Geometry resource pools.

What's the best way to allocate CPU and memory quotas across distributed agent pools?▼

You scale distributed agent workloads by deploying them across Sacred Geometry pools with predefined phi-scaled quotas. The preemptive scheduler dynamically manages resource distribution, handling 89+ bee types and triggering backpressure when quotas are reached.