Project Index
Summary of all Orchestrator projects analyzed in this book
Detailed Project Profiles
Tmux-Orchestrator
| Dimension |
Details |
| Language/Tech Stack |
Bash + tmux |
| Core Architecture |
Three-Layer Hierarchy (Orchestrator → Architect → Executor) |
| Communication Method |
bracket-paste injection + capture-pane monitoring |
| Fault Tolerance |
2 layers (built-in heartbeat + systemd watchdog) |
| Knowledge Accumulation |
CLAUDE.md + LEARNINGS.md + FEATURES.md |
| Isolation |
Role separation (Architect manages plans, Executor writes code) |
| Deployment |
systemd user service + loginctl linger |
| Key Features |
Self-triggering agents, git discipline, cross-project coordination |
| Repository |
GitHub |
| Evolution Stage |
Stage 2 (reliable operation, progressing toward Stage 3) |
Standout innovation: The bracket-paste protocol solves a real tmux problem — multi-line text corruption via send-keys. This is a "battle scar" pattern that can only come from production experience.
agency-agents-zh
| Dimension |
Details |
| Language/Tech Stack |
Markdown + MCP Memory Server |
| Core Architecture |
Seven-Stage Pipeline (Recon → Plan → Review → Build → Test → Deploy → Monitor) |
| Communication Method |
MCP Memory (semantic search + rollback) + copy-paste handoff |
| Fault Tolerance |
4 layers (quality gates at each pipeline stage) |
| Knowledge Accumulation |
MCP Memory (remember/recall/rollback) |
| Isolation |
Minimal (prompt-based role specification only) |
| Deployment |
install.sh script deploys to 10+ AI tool formats |
| Key Features |
211 expert agents, DAG workflow, breakpoint resume, 32 handoff templates, cross-platform deployment |
| Repository |
GitHub |
| Evolution Stage |
Stage 1 (running, but lacks autonomous fault tolerance) |
Standout innovation: Cross-platform agent deployment — a single agent definition can be installed as Claude Code, GitHub Copilot, Cursor, Aider, Windsurf, and more. This "write once, deploy everywhere" approach is unique in the ecosystem.
Composio (agent-orchestrator)
| Dimension |
Details |
| Language/Tech Stack |
TypeScript + pnpm |
| Core Architecture |
Orchestrator-Worker (1:N with dashboard) |
| Communication Method |
Shared files (todo.md, scratchpad) + JSON handoff |
| Fault Tolerance |
2 layers (LifecycleWorker + dashboard monitoring) |
| Knowledge Accumulation |
None (agents are stateless per session) |
| Isolation |
git worktree (Workers in independent worktrees) |
| Deployment |
ao start <url> one-click CLI |
| Key Features |
CI/CD integration, PR-based workflow, runtime agnostic, React dashboard, preflight checks |
| Repository |
GitHub |
| Evolution Stage |
Stage 2 (reliable, but knowledge gap limits Stage 3) |
Standout innovation: Preflight mechanism — check all dependencies before starting, rather than discovering "git not installed" at runtime. This is a DevOps best practice applied to Agent orchestration.
Overstory
| Dimension |
Details |
| Language/Tech Stack |
TypeScript + Bun runtime |
| Core Architecture |
Coordinator → Lead → Worker tree (hierarchical) |
| Communication Method |
SQLite Mail (9 protocol types + group addresses) |
| Fault Tolerance |
4 layers (tiered watchdog: bash timer + AI triage) |
| Knowledge Accumulation |
Mulch Knowledge Base (conflict patterns, failure patterns, project knowledge) |
| Isolation |
git worktree (managed by WorktreeManager) + 4-level merge strategy |
| Deployment |
ov init + ov coordinator CLI |
| Key Features |
11 runtime adapters, capability-based dispatch, overlay injection, event store, checkpoint handoff |
| Repository |
GitHub |
| Evolution Stage |
Stage 3 (intelligent enhancement, most mature) |
Standout innovation: Overlay injection — a three-layer rendering system (role definition + project profile + task assignment) that ensures every agent starts with the right context. This is the "consumer side" of knowledge accumulation.
Reference Projects (Not Deeply Analyzed)
| Project |
Language |
Architecture |
Key Contribution |
| Claude Code |
TypeScript |
Single-Agent CLI |
Native CLI integration, CLAUDE.md convention |
| CrewAI |
Python |
Role Collaboration |
Human-agent collaboration, shared memory |
| LangGraph |
Python |
State Graph |
Graph-based workflows, conditional edges, checkpoints |
| AutoGen |
Python |
Multi-Agent Conversation |
Conversational orchestration, code execution |
| OpenAI Swarm |
Python |
Agent Handoff |
Minimal handoff framework, lightweight |
Cross-Project Comparison Matrix
| Dimension |
Tmux-Orch |
agency-zh |
Composio |
Overstory |
| Setup Complexity |
Medium |
Low |
Low |
Medium |
| Max Agent Count |
3-5 |
211 (catalog) |
5-10 |
5-20 |
| Autonomy Level |
High |
Low (human-driven) |
Medium |
High |
| Production Readiness |
Battle-tested |
Template-only |
Early stage |
Most complete |
| Cross-Runtime |
No |
Yes (10+ formats) |
Partial (4 runtimes) |
Yes (11 adapters) |
| Knowledge Persistence |
LEARNINGS.md |
MCP Memory |
None |
Mulch + Event Store |
| Merge Strategy |
None |
None |
Basic |
4-level AI-assisted |