system-prompts-and-models-of-ai-tools/salesflow-saas/docs/governance/execution-fabric.md

Execution Fabric — Dealix Execution Plane Deep Dive

Parent: MASTER_OPERATING_PROMPT.md
Plane: Execution | Tracks: All
Version: 1.0 | Status: Canonical

---

Overview

The Execution Fabric defines how Dealix performs work: how tasks are classified, routed, checkpointed, retried, and completed. The backbone is the OpenClaw Framework — a durable execution engine with policy-aware gating.

---

Architecture

Inbound Request/Event
        │
        ▼
┌──────────────────┐
│  OpenClaw Gateway │  ← Single ingress for all tasks
│   (gateway.py)    │
└───────┬──────────┘
        │
        ▼
┌──────────────────┐
│   Policy Gate     │  ← Classify action (A/B/C)
│   (policy.py)     │
└───────┬──────────┘
        │
   ┌────┴────┐
   │ Class C │──→ BLOCKED (forbidden)
   └─────────┘
        │
   ┌────┴────┐
   │ Class B │──→ Check approval_token
   └─────────┘     │
        │     ┌────┴─────┐
        │     │ No token │──→ BLOCKED (requires_approval)
        │     └──────────┘
        │
        ▼
┌──────────────────┐
│  Canary Context   │  ← Tenant in canary group?
│ (canary_context)  │
└───────┬──────────┘
        │
        ▼
┌──────────────────┐
│  Observability    │  ← Start trace, record steps
│ (observability)   │
└───────┬──────────┘
        │
        ▼
┌──────────────────┐
│   Task Router     │  ← Dispatch to handler
│  (task_router)    │
└───────┬──────────┘
        │
        ▼
┌──────────────────┐
│  Durable Flow     │  ← Checkpoint state
│ (durable_flow)    │
└───────┬──────────┘
        │
        ▼
┌──────────────────┐
│  Handler / Agent  │  ← Execute business logic
│  (Celery / Sync)  │
└──────────────────┘

---

Task Classification

Class A — Safe Auto Actions

SAFE_AUTO_ACTIONS = {
    "read_status", "collect_signals", "summarize", "classify",
    "tag", "internal_status_update", "research", "generate_draft",
    "plan", "predictive_analysis"
}

These execute immediately without human approval.

Class B — Approval-Gated Actions

APPROVAL_GATED_ACTIONS = {
    "send_whatsapp", "send_email", "send_linkedin",
    "trigger_voice_call", "sync_salesforce", "create_charge",
    "publish_content", "change_billing_state", "modify_lead_routing",
    "send_contract_for_signature", "video_generate", "music_generate"
}

These require an approval_token in the payload.

Class C — Forbidden Actions

FORBIDDEN_ACTIONS = {
    "exfiltrate_secrets", "delete_data_without_audit",
    "bypass_auth", "publish_without_approval", "destructive_unchecked"
}

These are unconditionally blocked.

Default: Unknown actions → Class B (approval required).

---

Durable Flow Lifecycle

1. CREATE    → DurableTaskFlow(flow_name, tenant_id)
2. CHECKPOINT → flow.checkpoint(note, state_patch) → FlowRevision
3. RESUME    → Load from checkpoints, continue from last state
4. COMPLETE  → Final checkpoint, mark complete
5. ROLLBACK  → Compensate side effects (target state)

Each checkpoint stores:

• revision_id (UUID)
• at (ISO timestamp)
• note (human-readable)
• checkpoint (full state snapshot)

---

Plugin System

Plugins extend the Execution Plane with external integrations:

Plugin	File	Purpose
WhatsApp	plugins/whatsapp_plugin.py	WhatsApp Cloud API messaging
Salesforce	plugins/salesforce_agentforce_plugin.py	CRM sync, Account 360
Stripe	plugins/stripe_plugin.py	Payment processing
Voice	plugins/voice_plugin.py	Voice call integration
Contract Intel	plugins/contract_intelligence_plugin.py	Contract analysis

Plugin Contract

Each plugin must:

1. Register its task types with task_router.register()
2. Accept (tenant_id: str, payload: dict) as input
3. Return dict with structured output
4. Handle its own retries and error reporting
5. Log to observability bridge

---

Agent Execution Model

Event → Agent Router → Input Validation → Celery Task
  → LLM Call (model_router.py selects provider)
  → Output Parsing (Pydantic schema validation)
  → Escalation Check (rules in agent config)
  → Action Handler / Human Handoff
  → Log to ai_conversations

19 specialized agents, each with:

• System prompt (ai-agents/prompts/)
• Input/output schema
• Model + temperature config
• Escalation rules

---

Error Handling

Error Type	Behavior
LLM timeout	Retry with exponential backoff (3 attempts)
Plugin failure	Log error, mark flow as failed, alert
Policy violation	Block immediately, log to audit
Tenant mismatch	Block, log security event
Unknown task type	Raise ValueError, log

---

Current vs Target

Capability	Current	Target
Task classification (A/B/C)	Live	Live
Durable checkpointing	Live (in-memory)	Persistent storage
Plugin system	Live (5 plugins)	Expand to 10+
Agent execution	Live (19 agents)	Add governance agents
Canary enforcement	Live	Live
Compensation/rollback	Not implemented	Planned
Idempotency keys	Not implemented	Planned
Dead letter queue	Not implemented	Planned
Temporal integration	Not evaluated	Watch