Event

Event -- Event-Driven Architecture

Activate When

• User invokes /godmode:event
• User says "event sourcing", "CQRS", "message broker"
• User says "Kafka", "RabbitMQ", "dead letter queue"
• When building loosely coupled async systems

Workflow

Step 1: Event Architecture Assessment

# Detect message broker infrastructure
ls kafka/ docker-compose*.yml 2>/dev/null \
  | head -5
grep -rl "kafkajs\|amqplib\|@aws-sdk/client-sqs" \
  package.json pyproject.toml 2>/dev/null

# Check for event schemas
find . -name "*.avsc" -o -name "*.proto" \
  -o -path "*/events/*" | head -10

EVENT ARCHITECTURE CONTEXT:
Current State: No events | Basic pub/sub | Full CQRS/ES
Throughput: 
Ordering: None | Per-entity | Global
Retention: 

IF throughput > 10K/s: recommend Kafka
IF ordering per-entity only: Kafka partitions by key
IF need replay: Kafka or NATS JetStream (not RabbitMQ)
IF simple fan-out: SNS/SQS or RabbitMQ

Step 2: Broker Selection

MESSAGE BROKER SELECTION:
| Feature    | Kafka  | RabbitMQ | SQS/SNS | NATS  |
|-----------|--------|----------|---------|-------|
| Throughput| V.High | High     | High    | V.High|
| Latency   | ~5ms   | ~1ms     | ~50ms   | ~0.1ms|
| Ordering  | Per-pt | Per-q    | FIFO opt| Per-sb|
| Replay    | Yes    | No       | No      | Yes*  |

THRESHOLDS:
  Kafka: use when > 10K events/sec or need replay
  RabbitMQ: use when  0: alert team within 5 minutes
  IF DLQ depth > 100: page on-call
  IF message age in DLQ > 24h: escalate to P1
  Every consumer MUST have a DLQ configured

Step 5: Idempotency Patterns

| Pattern           | How It Works         |
|-------------------|---------------------|
| Idempotency key   | Store processed IDs |
| Natural idempotent| Upserts, SET ops    |
| Optimistic locking| Version check       |
| Dedup table       | event_id in DB      |

RULE: Every consumer must be idempotent.
At-least-once delivery means duplicates WILL occur.

Step 6: Event Sourcing (if needed)

Store state as immutable event sequence. Rebuild aggregate state by replaying events. Use snapshots every 100 events for performance.

Step 7: CQRS (if needed)

Separate write model (commands → event store) from read model (projections → query-optimized DB). Projection lag target: -- event types, , "`

Key Behaviors

Never ask to continue. Loop autonomously until done.

1. Events are facts, not commands. Past tense:

"OrderPlaced", not "PlaceOrder".

1. Events are immutable. Publish corrective events.
2. Schema evolution is mandatory. Backward and

forward compatibility from day one.

1. Every consumer is idempotent.

Quality Targets

• Publish-to-consume: 99% success rate
• Max payload: <1MB per event

HARD RULES

1. Never use events as remote procedure calls.
2. Never mutate historical events.
3. Never deploy consumers without idempotency.
4. Never skip the dead letter queue.
5. Never publish without schema registry check.

Auto-Detection

1. Broker: kafka, rabbitmq, SQS/SNS, NATS configs
2. Schemas: *.avsc, *.proto, events/ directory
3. DLQ: dead-letter config, maxReceiveCount
4. Event sourcing: event_store table, Axon framework

Loop Protocol

FOR each event domain:
  1. Design schema with envelope standard
  2. Register in schema registry
  3. Implement producer + consumer
  4. Configure DLQ + retry policy
  5. Verify idempotency with duplicate test
  6. IF schema breaks compat: add field, don't modify
  7. IF DLQ growing: check handler, fix root cause

Output Format

Print: Event: {pattern}, {broker}, {N} event types, DLQ: {configured}. Verdict: {verdict}.

TSV Logging

timestamp	broker	event_types	dlq_configured	idempotency	status

Keep/Discard Discipline

KEEP if: schema registered AND DLQ configured
  AND idempotent consumer verified
DISCARD if: schema breaks compat OR no DLQ
  OR consumer not idempotent

Stop Conditions

STOP when ANY of:
  - All events have schemas with compat checks
  - DLQ on every consumer with backoff retry
  - Idempotency verified for all consumers
  - User requests stop

Error Recovery

• Schema compat fails: add fields with defaults only.
• Consumer lag growing: scale instances, add partitions.
• DLQ growing: check handler, fix deserialization.
• Ordering broken: verify partition key strategy.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: arbazkhan971
• Source: arbazkhan971/godmode
• License: MIT

Install and usage instructions live in the source repository linked above.