Use Workflow Orchestrator Prover with your AI.

Validate workflow orchestration

You must: (1) DEFINE TRIGGER. what initiates this workflow and what happens if the trigger fires twice (duplicate event). (2) MAP EVERY FAILURE. for each integration step: what happens when it returns 500? 429? timeout? invalid data? Define: Dead Letter Queue, circuit breaker, retry with exponential backoff, compensating transaction. (3) CALCULATE RATE LIMITS. exact request volume per API per minute/hour/day. Compare against documented rate limits. Calculate cost at scale. (4) GUARANTEE IDEMPOTENCY. every step must be safe to retry. Idempotency keys, state machines, conditional transitions, deduplication. (5) PLAN AUTH LIFECYCLE. token TTL, refresh timing, rotation schedule, expiry monitoring. The consistency engine has zero tolerance for lazy answers. If rejected, fix the flaw immediately. Structured reflection capability for automation pipeline validation. forces rigorous error handling, rate limit awareness, idempotency guarantees, and authentication lifecycle planning before writing any integration code. Based on the principle: automation amplifies both success AND failure. a manual process that fails affects one transaction; an automated pipeline that fails affects every transaction until someone notices. Catches Happy Path Bias (designing only for success, ignoring failure modes. a restaurant ordering system: online order → payment gateway → kitchen printer → confirmation email. Happy path works perfectly. Then: Payment gateway returns HTTP 500. The order is placed in the kitchen but never charged. 47 free meals before anyone notices. Kitchen printer runs out of paper. Orders are confirmed to customers but never printed. Customers arrive for pickup. nothing is ready. Email service is down. Customer pays, kitchen cooks, but no confirmation email. Customer calls: "Did my order go through?". 200 calls that afternoon. Fix: for EVERY step, define: what happens when it FAILS? Dead Letter Queue (failed orders stored for manual processing). Circuit breaker (stop accepting orders when kitchen system is down. do not accumulate debt). Retry with exponential backoff (payment gateway transient failure: retry at 1s, 2s, 4s, 8s. not immediately). Compensating transaction (if payment succeeds but kitchen fails: reverse the charge)), Rate Limit Blindness (ignoring API rate limits that will break the pipeline under load. a hotel booking aggregator: polls 15 hotel APIs every 5 minutes to update availability. Each API allows 100 requests/minute. At 15 hotels × 20 room types × 30 days = 9,000 requests per cycle. At 1 cycle every 5 minutes = 1,800 requests/minute. Budget: 100/minute per API. The system exceeds rate limits on cycle 1. Gets throttled. Returns stale data. Guests book rooms that are already occupied. Front desk: "We are overbooked." Fix: calculate exact request volume BEFORE building the pipeline. Implement: rate limit tracking per API, request batching, staggered polling, exponential backoff on 429 responses, and cost estimation. if hotel API charges $0.003/request: 9,000 × 288 cycles/day = $7,776/day. The "free API" costs $233K/month at scale), Non-Idempotent (unsafe retries that cause duplicate actions. a pharmacy prescription fulfillment pipeline: Doctor submits prescription → system processes → pharmacy dispenses → patient notified. Network timeout after "dispense" step. System does not know if it succeeded. Retries the entire workflow. Pharmacy dispenses TWICE. Patient receives double medication. For blood thinners: this is a medical emergency. Fix: every step must be idempotent. safe to retry without duplication. Idempotency key per prescription (UUID). Check "already dispensed?" before dispensing. State machine: CREATED → PROCESSING → DISPENSED → NOTIFIED. Each transition is guarded: "IF status = PROCESSING THEN dispense". never re-dispense if DISPENSED. If the system crashes between DISPENSED and NOTIFIED: retry notification only, not dispensing), and Auth Orphaned (credentials that expire mid-workflow without refresh planning. a warehouse inventory system: nightly sync at 2 AM pulls data from ERP (SAP), updates warehouse management (WMS), and generates purchase orders in procurement (Ariba). OAuth2 token obtained at 2:00 AM. Token TTL: 30 minutes. SAP sync: 25 minutes (tight but works). WMS update: 20 minutes. Total: 45 minutes. Token expires at 2:30 AM. halfway through WMS update. WMS write fails silently. Procurement gets partial data. Purchase orders generated for items the warehouse already has. $340,000 in duplicate inventory. Fix: token refresh BEFORE expiry (refresh at 80% of TTL = 24 minutes). Token refresh handler: if refresh fails → alert + abort (do not continue with expired credentials). Credential rotation plan: service account passwords, API keys, certificates. all have expiry dates. Monitor: alert when any credential is within 7 days of expiry). Call once per automation workflow, integration pipeline, or scheduled process