duraflows-builder

name	duraflows-builder
description	Builds complete duraflows workflow implementations from natural-language requirements. Use when the user asks to create, design, or scaffold a workflow, or says 'build me a workflow for X', 'I need a workflow that does Y', 'create a state machine for Z', or wants to model a business process with duraflows.

duraflows Workflow Builder

A step-by-step reasoning process for translating natural-language requirements into complete duraflows workflow implementations.

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Reasoning Checklist

Follow these steps in order when a user asks you to build a workflow.

Step 1: Extract Domain Entities and Actions

From the user's description, identify:

• Main entity: What is being tracked? (order, ticket, document, deployment, etc.)
• Lifecycle stages: What distinct phases does it go through?
• External actions: What side effects happen? (API calls, notifications, payments)
• Failure modes: What can go wrong at each stage?
• Time-sensitive transitions: Are there deadlines or auto-escalations?
• Human decision points: Where does a person need to approve or decide?

Step 2: Map to States

Each distinct lifecycle stage becomes a state in the WorkflowDefinition:

• Active states: Have events (the workflow can progress)
• Terminal states: No events (the workflow is done). Define as empty objects {}
• Gateway states: Use onEnter to auto-execute commands and transition (no human trigger needed)
• Waiting states: Have events but no onEnter (waiting for external trigger or timeout)

Keep states minimal. Each state should represent a genuinely distinct lifecycle phase. Don't add intermediate or "final" wrapper states unless they serve a specific purpose (running commands, branching, enabling retry). If a single terminal state like cancelled or failed is sufficient, use it directly — don't split it into cancelling + cancelled_final.

For each state, determine what context values should be set on entry (status flags, timestamps).

Step 3: Map to Events

Each user action, external trigger, or automated transition becomes an event:

• Determine targetState (where does success lead?). v1.0.0: targetState is now optional — see command-only events below.
• Does this event involve commands that can fail? If yes, define errorState (or mark non-critical commands as bestEffort — see Step 4c).
• Is this event time-triggered? Define timeout with afterMinutes/afterHours/afterDays
• Is the event gated by a precondition that should run before any commands? Define a guard (v1.1.0). See Step 4d.
• Remember: at most one timeout event per state

Event shapes (v1.0.0): an event must define at least one of targetState, errorState, or commands. Three valid combinations:

Shape	Use case
targetState (+ optional errorState + commands)	Standard transition — most events
commands only (no targetState)	Command-only event — runs side effects, stays in current state. Right for operator notes, manual context corrections, side-effect kicks
errorState + commands (no targetState)	Failure-only event — trap a failure and route to recovery without forward progress

v2.0.0 — merged self-loop is allowed. When targetState and errorState point at the same state (typically the current state, e.g., poll: { targetState: "active", errorState: "active" }), WorkflowCompiler collapses the two branches into a single transition at compile time. Both outcomes resolve to that state and the result still distinguishes outcome: "success" vs "failure" for history. Use this shape for "stay here regardless of outcome, just record what happened" — typical for polling, idempotent retries, and best-effort tick events.

Step 4: Map to Commands

Each side-effecting action becomes a WorkflowCommand:

• Name with verb-noun pattern: chargePayment, sendNotification, validateInventory
• Determine what each command reads from ctx.metadata (identity) and ctx.context (working state)
• Determine what each command writes to ctx.context
• Commands execute sequentially in definition order; first failure stops the chain

Step 4b: Best-Effort Commands (v1.0.0)

For non-critical side effects — notifications, metrics, analytics, compensation/rollback steps — set bestEffort = true on the command class:

class SendNotificationCommand implements WorkflowCommand {
  readonly bestEffort = true;
  async execute(subject, ctx): Promise<CommandResult> {
    /* ... */
  }
}

A best-effort command:

• Returning { ok: false } does NOT abort the chain or taint outcome. The result is recorded; the next command runs.
• Throwing is caught and recorded as { ok: false, code: "BEST_EFFORT_THROWN", error: { name, message, stack? } }. The chain continues.

Decision matrix:

Concern	Right tool
Failure must abort the workflow	Mandatory command (no bestEffort)
Failure should route to a recovery state	Mandatory command + errorState
Failure should be recorded but not stop forward progress	bestEffort: true
Cross-cutting audit / metric of every state entry	Observer (post-commit, see Step 9b)

This replaces the v0.x pattern of "catch the error inside the command and return { ok: true } anyway". Returning ok: true lies in the history; bestEffort: true records the truth and continues.

Step 4c: Per-Command Metadata (v1.0.0)

Add metadata to a WorkflowCommandRef to drive one handler with different parameters from many call sites:

commands: [
  { name: "send-notification", metadata: { channel: "email", template: "payment-confirmed" } },
  { name: "send-notification", metadata: { channel: "sms", template: "delivered" } },
];

Inside the handler, read ctx.commandMetadata.channel etc. Each ref's metadata is deep-cloned + frozen, isolated from siblings.

Step 4d: Event Guards (v1.1.0)

For preconditions that gate an event before any commands run, use a WorkflowGuard instead of a routing errorState. A guard is a read-only predicate; if it returns false, the event short-circuits with outcome: "guard-rejected", no commands execute, no state change.

class IsVerifiedGuard implements WorkflowGuard<Customer> {
  readonly name = "isVerified";
  evaluate(subject: Customer, ctx: WorkflowExecutionContext): boolean {
    return subject.verified === true;
  }
}

// In the workflow:
events: {
  Submit: {
    guard: { name: "isVerified" },          // ref name resolved against the guard registry
    targetState: "submitted",
    commands: [{ name: "createOrder" }],
  },
}

When a guard is the right choice:

• The decision is read-only ("is this allowed right now?") — no I/O, no DB writes
• Rejection is normal business behavior (the caller can try again later or pick a different event)
• You want to short-circuit before any side effects run
• The same logic applies to multiple events (define once, reference from many)

Choose errorState instead when the failure represents a fault to capture, the workflow needs an alternate path with full command results recorded, or the decision depends on side-effecting work (an external check, a DB lookup that can't be precomputed into context).

Per-event metadata. Like commands, a guard ref can carry metadata that reaches the implementation through ctx.commandMetadata (deep-cloned + frozen). Use this so one WorkflowGuard implementation can serve many call sites:

events: {
  ApplyDiscount: { guard: { name: "minTier", metadata: { minTier: "gold" } }, /* ... */ },
  Refund:        { guard: { name: "minTier", metadata: { minTier: "silver" } }, /* ... */ },
}

Critical constraints (the runtime enforces these):

• The guard receives a deepFreezed clone of ctx.context. Any mutation throws under strict mode.
• Guards run inside the per-event transaction. Do not call external services or write to DBs from a guard — non-idempotent I/O will repeat on timeout sweeps.
• errorState does NOT catch guard rejections. They are not faults.
• The guard ref name (eventDef.guard.name) is what appears in WorkflowExecutionResult.rejectedBy and the history rejected_by column — definitions are the source of truth.

Timeout interaction. When a guard rejects a timeout-driven event, the runtime additionally clears expiresAt so the next sweep won't re-pick the instance. The rejection counts toward ProcessExpiredWorkflowsResult.rejected, not processed.

Step 4e: Conditional Branching

duraflows doesn't have a native "if/else" transition from a single command result. Use these patterns:

Pattern A: errorState as branch. A gateway state with onEnter runs a command. ok: true follows targetState, ok: false follows errorState. This is the idiomatic pattern for binary branching (e.g., "if flagged go to review, otherwise auto-approve").

scanning: {
  onEnter: {
    commands: ["aiScan"],
    targetState: "approved",     // scan clean -> auto-approve
    errorState: "pending_review", // scan flagged -> human review
  },
},

The aiScan command returns { ok: false, code: "FLAGGED" } to route to review. This is not an error — it's intentional routing using the ok: false / errorState mechanism.

Trade-off: Pattern A uses the single errorState slot for branching, so actual infrastructure failures (e.g., scan service down) can't route to a separate error state at the state machine level. Handle infrastructure errors inside the command itself: catch them, retry if appropriate, and if unrecoverable, either re-throw (which rolls back the transaction and leaves the workflow in the current state for retry) or return { ok: false } with a distinguishing code and a context flag:

// Inside the aiScan command:
try {
  const result = await this.aiService.scan(content);
  if (result.flagged) {
    ctx.context.scanOutcome = "flagged";
    return { ok: false, code: "FLAGGED" };
  }
  ctx.context.scanOutcome = "clean";
  return { ok: true, code: "CLEAN" };
} catch (err) {
  // Infrastructure failure — re-throw to roll back transaction.
  // The workflow stays in the current state; the event can be retried.
  throw err;
}

Pattern B: Two events for explicit triggers. When the branch depends on an external decision (not a command result), use separate events on a waiting state:

pending_review: {
  events: [
    { name: "approve", targetState: "approved" },
    { name: "reject", targetState: "rejected", commands: ["notifyAuthor"] },
  ],
},

Prefer Pattern A for automated decisions and Pattern B for human decisions. Don't add unnecessary routing gateway states when a single onEnter with targetState/errorState achieves the branch directly.

Step 5: Design Error Recovery

For each command that can fail:

• Define an errorState on the event
• Consider retry patterns: errorState with a Retry event that transitions back
• Track retry count in context: ctx.context.retryCount = (ctx.context.retryCount ?? 0) + 1
• Consider compensation (saga): if step N fails, do previous steps need rollback? See saga template

Step 6: Design Timeout Patterns

For waiting states that need deadlines:

• Auto-close: timeout: { afterDays: 30 } -> terminal state
• Escalation: timeout: { afterHours: 48 } -> escalated state with force-approve/reject events
• Reminder: timeout: { afterDays: 1 } -> gateway state that sends reminder then returns to waiting

Step 7: Assemble the WorkflowDefinition

Use the skeleton templates as starting points:

• Simple sequence -- linear progression with timeout
• Fan-out/fan-in -- multi-step processing via onEnter chains
• Saga with compensation -- forward chain + rollback
• Approval / human-in-the-loop -- waiting states with escalation

Step 8: Implement Commands

For each command name referenced in the definition:

NestJS pattern:

import { WorkflowCommand } from "@duraflows/nestjs";

@WorkflowCommand("chargePayment")
export class ChargePaymentCommand implements WorkflowCommandInterface {
  constructor(private readonly gateway: PaymentGateway) {}

  async execute(subject: unknown, ctx: WorkflowExecutionContext): Promise<CommandResult> {
    try {
      const result = await this.gateway.charge(/* ... */);
      ctx.context.chargeId = result.id;
      ctx.context.chargedAt = ctx.now.toISOString();
      return { ok: true, code: "CHARGED" };
    } catch (err) {
      return { ok: false, code: "CHARGE_FAILED", message: String(err) };
    }
  }
}

Standalone pattern:

const commandRegistry = new InMemoryCommandRegistry();
commandRegistry.register("chargePayment", new ChargePaymentCommand(gateway));

Step 9: Wire Up

NestJS (sync):

WorkflowModule.forRoot({
  workflows: [myWorkflow],
  persistence: pgWorkflowProviders(pool),
  observers: [auditObserver], // v1.0.0: top-level for forRoot only
  guards: [new IsVerifiedGuard()], // v1.1.0: array form composes an InMemoryGuardRegistry; OR pass guardRegistry (mutually exclusive)
});

NestJS (async, v1.0.0):

WorkflowModule.forRootAsync<[pg.Pool, AuditObserver]>({
  imports: [ObserversModule], // observer DI must be visible to the dynamic-module factory
  useFactory: (pool, audit) => ({
    workflows: [myWorkflow],
    persistence: pgWorkflowProviders(pool),
    observers: [audit], // v1.0.0: observers go INSIDE useFactory return value
    guards: [new IsVerifiedGuard()], // v1.1.0; or guardRegistry — never both
    onObserverError: (err, obs, evt) => logger.warn(`${obs.name} failed: ${err}`),
  }),
  inject: [PG_POOL, AuditObserver],
});

Standalone:

const guardRegistry = new InMemoryGuardRegistry(); // v1.1.0: only required if any event uses a guard
guardRegistry.register("isVerified", new IsVerifiedGuard());

const runtime = new WorkflowRuntime({
  definitionRegistry,
  commandRegistry,
  guardRegistry, // omit if no events declare a guard
  ...pgWorkflowProviders(pool),
  clock: { now: () => new Date() },
  observers: [auditObserver],
  onObserverError: (err, obs, evt) => logger.warn(`${obs.name} failed: ${err}`),
});

If the workflow uses timeouts, set up a poller:

// NestJS: @Cron(CronExpression.EVERY_MINUTE)
await timeoutService.processExpiredWorkflows(100);

Step 9b: Add Observers (v1.0.0)

For audit trails, metrics, projections, cache invalidation, or webhooks, register a WorkflowObserver:

const auditObserver: WorkflowObserver = {
  name: "audit",
  onEnter: async (event) => {
    await audit.record({
      workflow: event.workflowName,
      instance: event.instanceUuid,
      from: event.fromState,
      to: event.toState,
      via: event.triggerEvent,
      transitionUuid: event.transitionUuid,
      at: event.occurredAt,
    });
  },
};

Observers fire post-commit, at-most-once, sequential, error-contained. They are NOT a place for business-critical work — use a workflow command if the work must run inside the transaction or must retry on failure.

event.transitionUuid matches the transitionUuid on the WorkflowExecutionContext of commands that ran on entry to the same state, so observer logs and command logs can be correlated 1:1.

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Requirement-to-Primitive Mapping

User Says	duraflows Primitive
"when X happens"	Event on a state
"then do Y"	Command in event's commands list
"if Y fails, go to Z"	errorState on the event
"wait for X"	State with events but no onEnter
"automatically do X when entering state"	onEnter with commands
"if nothing happens in N hours/days"	Timeout event: timeout: { afterHours: N }
"retry up to N times"	errorState -> state with Retry event, retryCount in context
"poll/tick/heartbeat — stay here regardless of outcome, just record it"	Merged self-loop event: targetState and errorState both equal current state (v2.0.0)
"do X, then Y, then Z automatically"	onEnter chain: gateway1 -> gateway2 -> gateway3
"if any step fails, undo previous steps"	Saga: error states with compensation onEnter chains; mark cancel/rollback commands bestEffort: true
"needs human approval"	Waiting state with Approve/Reject events
"escalate after N hours"	Timeout event -> escalated state
"track who did it"	triggerMetadata: { actor: userId } (stored in history)
"set status to X in this state"	context: { status: "X" } on state definition
"remember the result for later"	Command writes to ctx.context
"identify by order ID"	metadata: { orderId } at creation (immutable)
"send a notification but don't fail the order if email is down"	bestEffort: true on the notification command (v1.0.0)
"let an operator add a note without changing state"	Command-only event — commands only, no targetState (v1.0.0)
"use the same handler with different parameters at different call sites"	Per-WorkflowCommandRef.metadata, read via ctx.commandMetadata (v1.0.0)
"log/audit every state transition"	Register a WorkflowObserver (v1.0.0) — post-commit, at-most-once
"only allow this event if the user is verified / cart total ≥ N / etc."	guard: { name: "..." } on the event (v1.1.0) — read-only predicate, runs before any commands
"block the timeout from auto-progressing until X is true"	Same event guard; on timeout the runtime additionally clears expiresAt to avoid sweep churn (v1.1.0)
"the same precondition with different thresholds at different call sites"	One WorkflowGuard implementation; pass guard.metadata: { ... }, read via ctx.commandMetadata (v1.1.0)
"the rejection should NOT be treated as an error"	Use a guard rather than an errorState — errorState catches command failures only (v1.1.0)

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Skeleton Templates

Start from the template closest to your use case:

Template	Pattern	When to Use
simple-sequence.ts	Linear state progression	Straightforward lifecycle with sequential stages
fan-out-fan-in.ts	Multi-step onEnter chains	Processing pipelines, multi-stage enrichment
saga-compensation.ts	Forward + rollback chains	Multi-service transactions needing rollback
approval-human-in-loop.ts	Waiting states + timeout	Approval flows, review processes, escalation