agent-orchestration
Multi-agent orchestration runtime with operator-aware autonomy. Six specialized agents collaborate through a typed artifact pipeline, with autonomy levels dynamically adjusted based on operator cognitive state.
Architecture
┌──────────────────────────────────────────────────────────────┐
│ MCP Runtime (41 RPC methods) │
│ Sessions · Artifacts · Worktrees · Agent Execution · Merge │
└──────────────────────────┬───────────────────────────────────┘
│
┌──────────────────────────┴───────────────────────────────────┐
│ Orchestration Pipeline │
│ POLYMATH → RESONANT → ARCHITECT → EXECUTOR → HORIZON │
│ (optional) │
└────────┬─────────────────────────────────┬───────────────────┘
│ │
┌────────┴────────┐ ┌────────┴────────┐
│ MIND Engine │ │ BASIS Engine │
│ Operator State │ │ Context Score │
│ Machine (FSM) │ │ Calculator │
│ │ │ │
│ fresh → mid → │ │ Domains × │
│ faded ↔ high_ │ │ Weights → │
│ pressure │ │ Caps/Penalties → │
│ │ │ CSS (0-100) │
│ → Autonomy │ │ → Tier A/B/C │
│ L0-L3 │ │ │
└─────────────────┘ └──────────────────┘
How It Works
- Task enters the pipeline via the MCP runtime
- MIND engine evaluates operator state (session duration, decision count, error rate, fatigue signals) and assigns an autonomy level (L0–L3)
- BASIS engine calculates a Context Sufficiency Score across weighted domains — determines whether enough context exists to proceed
- Agents execute in sequence, each producing a typed artifact:
| Agent | Role | Artifact |
|---|---|---|
| Polymath | Divergent exploration, hypothesis generation | TaskMap |
| Resonant | Evidence validation, risk assessment | EvidencePack |
| Architect | Design specification from evidence | DesignSpec |
| Executor | Implementation in isolated worktrees | PatchSet |
| Horizon | Ship gating (5 gates), release decision | ShipDecision |
| Alchemist | Creative reframing when work is stuck | OptionsSet |
- Permission matrix enforces read/write guardrails per agent per autonomy level. Only Executor can write code, and only at L2+.
Project Structure
slate/
├── agents/ # 6 agent runners (polymath, resonant, architect, executor, horizon, alchemist)
├── engines/
│ ├── basis/ # Context Sufficiency Score calculator
│ └── mind/ # Operator state machine + autonomy resolver
├── libs/
│ ├── context-schema/ # Zod artifact schemas (TaskMap, EvidencePack, DesignSpec, etc.)
│ ├── context-loader/ # Markdown + YAML context loading
│ ├── orchestration/ # Pipeline coordination + session management
│ └── llm-provider/ # LLM router (OpenAI primary, Anthropic fallback)
├── apps/
│ └── mcp-runtime/ # JSON-RPC server (41 methods)
├── tests/ # E2E test suites
└── tools/ # Agent manifests, contracts, templates
Tech Stack
- Language: TypeScript 5.4
- Build: Nx monorepo
- Schema Validation: Zod
- Testing: Vitest
- LLM Integration: OpenAI SDK, Anthropic SDK
- Runtime: Node.js, vite-node
- Protocol: MCP (Model Context Protocol) via JSON-RPC
Run
# Install dependencies
npm install
# Build all packages
npx nx run-many --target=build
# Run tests
npx nx run-many --target=test
# Start MCP runtime
npx nx run slate-runtime:serve
Status
Working prototype, actively developed. Core pipeline, all 6 agents, both engines, and the MCP runtime are functional with passing test suites. Not production-hardened — session persistence is file-based, no monitoring/observability layer yet.