Saba-AgenticFlow — Multi-Agent Orchestration Framework

Abstract

Saba-AgenticFlow is a production-grade multi-agent orchestration system for AI agent ecosystems. It implements a hierarchical delegation model with Alfred (CEO) + 5 specialists (coder, debug, security, research, qa-tester), supported by Kanban tracking, heartbeat autonomy, and PDCA continuous improvement. Unlike simple multi-agent systems, it provides a complete orchestration lifecycle: delegate → execute → review → improve. Built on OpenClaw, it powers complex autonomous workflows with clear ownership boundaries and quality gates.

Architecture

┌─────────────────────────────────────────────────────────────┐
│                   Alfred (CEO Agent)                  │
│              Decision Maker + Delegator                    │
├─────────────────────────────────────────────────────────────┤
│         5 Specialists (bounded ownership)                 │
├──────────┬──────────┬──────────┬──────────┬─────────┤
│  Coder   │  Debug    │ Security   │ Research  │ QA-Test │
│ (impl)   │ (diag)   │ (audit)   │ (invest) │ (test)  │
├──────────┴──────────┴──────────┴──────────┴─────────┤
│                   Orchestration Primitives               │
│  Kanban + Heartbeat + OpenProse + sessions_spawn       │
└─────────────────────────────────────────────────────────────┘

Orchestration Primitives

Primitive	Purpose	Owner
Kanban	Task tracking, quality gates, async work	Alfred creates, specialists process
Heartbeat	Autonomous 30-min cycles, claim work, handoff	All agents run independently
OpenProse	Multi-agent parallel workflows	Alfred/cross-domain
sessions_spawn	Helper subtasks, bounded scope	Specialist with context
sessions_yield	Pass baton back to owner	Specialist preserving ownership

Production Metrics

6 months continuous operation with OpenClaw multi-agent ecosystem:

Metric	Value
Total tasks processed	847
Tasks completed	782 (92.3% completion rate)
Average cycle time	45 min
Handoffs between agents	156
PDCA iterations	34
Quality gates passed	98.2%

Patterns

Delegation Pattern: Alfred delegates with explicit scope → Specialist claims → Specialist executes → Specialist yields back → Alfred reviews

Autonomy Pattern: Heartbeat every 30 min → Check Kanban → Claim if available → Execute → Handoff on completion

Parallel Pattern: OpenProse spawns parallel specialists → All run bounded tasks → Results aggregated → Continue flow

Quick Start

# Clone repo
git clone https://github.com/SabaTech-dev/Saba-AgenticFlow.git
cd Saba-AgenticFlow

# Read architecture
cat docs/architecture.md

# Explore patterns
cat docs/patterns.md

# See [CHANGELOG.md](CHANGELOG.md) for version history
## Releases
See [CHANGELOG.md](CHANGELOG.md) for version history.

API Reference

Orchestration Operations

Operation	Purpose	Flow
delegate	Alfred delegates to specialist	Alfred → specialist via sessions_spawn
heartbeat	Autonomous work cycle	All agents every 30 min
handoff	Return baton with summary	Specialist → Alfred via sessions_yield
claim	Take ownership of task	Specialist → Kanban
review	Quality gate before done	Debug/Security → Done

Example: Delegation

# Alfred delegates to coder

**Goal:** Implement OAuth2 authentication

**Scope:** src/auth/, tests/auth/

**Acceptance Criteria:**
- Login/logout endpoints functional
- Token refresh mechanism
- All tests passing

**Constraints:**
- No DB schema changes
- Security audit before done

Roadmap

v1.1 (Next)

• Auto-discovery of specialist capabilities
• Dynamic task routing based on skills
• Metrics dashboard

v1.2 (Future)

• Federated orchestration across clusters
• Multi-cloud deployment
• AI-powered task prioritization

Documentation

• Architecture - Delegation model, specialist matrix
• Patterns - Reusable delegation, parallelization, PDCA
• Contributing - Development guidelines

License

MIT License — see LICENSE