Event Store Design workflow skill. Use this skill when the user needs Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
Event Store Design workflow skill. Use this skill when the user needs Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
This public intake copy packages plugins/antigravity-bundle-ddd-evented-architecture/skills/event-store-design from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.
Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.
This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.
Event Store Design Comprehensive guide to designing event stores for event-sourced applications.
Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Core Concepts, Technology Comparison, Templates, Limitations.
When to Use This Skill
Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.
The task is unrelated to event store design
You need a different domain or tool outside this scope
Designing event sourcing infrastructure
Choosing between event store technologies
Implementing custom event stores
Optimizing event storage and retrieval
Operating Table
Situation
Start here
Why it matters
First-time use
metadata.json
Confirms repository, branch, commit, and imported path through the external_source block before touching the copied workflow
Provenance review
ORIGIN.md
Gives reviewers a plain-language audit trail for the imported source
Workflow execution
resources/implementation-playbook.md
Starts with the smallest copied file that materially changes execution
Supporting context
resources/implementation-playbook.md
Adds the next most relevant copied source file without loading the entire package
Handoff decision
## Related Skills
Helps the operator switch to a stronger native skill when the task drifts
Workflow
This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.
Clarify goals, constraints, and required inputs.
Apply relevant best practices and validate outcomes.
Provide actionable steps and verification.
If detailed examples are required, open resources/implementation-playbook.md.
Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
Read the overview and provenance files before loading any copied upstream support files.
Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
Imported Workflow Notes
Imported: Instructions
Clarify goals, constraints, and required inputs.
Apply relevant best practices and validate outcomes.
Provide actionable steps and verification.
If detailed examples are required, open resources/implementation-playbook.md.
Use @event-store-design-v3 to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.
Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.
Example 2: Ask for a provenance-grounded review
Review @event-store-design-v3 against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.
Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.
Example 3: Narrow the copied support files before execution
Use @event-store-design-v3 for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.
Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.
Example 4: Build a reviewer packet
Review @event-store-design-v3 using the copied upstream files plus provenance, then summarize any gaps before merge.
Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.
Best Practices
Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.
Use stream IDs that include aggregate type - Order-{uuid}
Include correlation/causation IDs - For tracing
Version events from day one - Plan for schema evolution
Implement idempotency - Use event IDs for deduplication
Index appropriately - For your query patterns
Don't update or delete events - They're immutable facts
Don't store large payloads - Keep events small
Imported Operating Notes
Imported: Best Practices
Do's
Use stream IDs that include aggregate type - Order-{uuid}
Include correlation/causation IDs - For tracing
Version events from day one - Plan for schema evolution
Implement idempotency - Use event IDs for deduplication
Index appropriately - For your query patterns
Don'ts
Don't update or delete events - They're immutable facts
Don't store large payloads - Keep events small
Don't skip optimistic concurrency - Prevents data corruption
Don't ignore backpressure - Handle slow consumers
Troubleshooting
Problem: The operator skipped the imported context and answered too generically
Symptoms: The result ignores the upstream workflow in plugins/antigravity-bundle-ddd-evented-architecture/skills/event-store-design, fails to mention provenance, or does not use any copied source files at all.
Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.
Problem: The imported workflow feels incomplete during review
Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task.
Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.
Problem: The task drifted into a different specialization
Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better.
Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.
Related Skills
@airflow-dag-patterns-v3 - Use when the work is better handled by that native specialization after this imported skill establishes context.
@aws-serverless-v3 - Use when the work is better handled by that native specialization after this imported skill establishes context.
@bash-linux-v3 - Use when the work is better handled by that native specialization after this imported skill establishes context.
@concise-planning-v3 - Use when the work is better handled by that native specialization after this imported skill establishes context.
Additional Resources
Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.
Resource family
What it gives the reviewer
Example path
references
copied reference notes, guides, or background material from upstream
references/n/a
examples
worked examples or reusable prompts copied from upstream
examples/n/a
scripts
upstream helper scripts that change execution or validation
scripts/n/a
agents
routing or delegation notes that are genuinely part of the imported package
agents/n/a
assets
supporting assets or schemas copied from the source package
-- Events tableCREATE TABLE events (
id UUID PRIMARY KEYDEFAULT gen_random_uuid(),
stream_id VARCHAR(255) NOT NULL,
stream_type VARCHAR(255) NOT NULL,
event_type VARCHAR(255) NOT NULL,
event_data JSONB NOT NULL,
metadata JSONB DEFAULT'{}',
version BIGINTNOT NULL,
global_position BIGSERIAL,
created_at TIMESTAMPTZ DEFAULT NOW(),
CONSTRAINT unique_stream_version UNIQUE (stream_id, version)
);
-- Index for stream queriesCREATE INDEX idx_events_stream_id ON events(stream_id, version);
-- Index for global subscriptionCREATE INDEX idx_events_global_position ON events(global_position);
-- Index for event type queriesCREATE INDEX idx_events_event_type ON events(event_type);
-- Index for time-based queriesCREATE INDEX idx_events_created_at ON events(created_at);
-- Snapshots tableCREATE TABLE snapshots (
stream_id VARCHAR(255) PRIMARY KEY,
stream_type VARCHAR(255) NOT NULL,
snapshot_data JSONB NOT NULL,
version BIGINTNOT NULL,
created_at TIMESTAMPTZ DEFAULT NOW()
);
-- Subscriptions checkpoint tableCREATE TABLE subscription_checkpoints (
subscription_id VARCHAR(255) PRIMARY KEY,
last_position BIGINTNOT NULLDEFAULT0,
updated_at TIMESTAMPTZ DEFAULT NOW()
);
Template 2: Python Event Store Implementation
from dataclasses import dataclass, field
from datetime import datetime
from typing importAny, Optional, Listfrom uuid import UUID, uuid4
import json
import asyncpg
@dataclassclassEvent:
stream_id: str
event_type: str
data: dict
metadata: dict = field(default_factory=dict)
event_id: UUID = field(default_factory=uuid4)
version: Optional[int] = None
global_position: Optional[int] = None
created_at: datetime = field(default_factory=datetime.utcnow)
classEventStore:
def__init__(self, pool: asyncpg.Pool):
self.pool = pool
asyncdefappend_events(
self,
stream_id: str,
stream_type: str,
events: List[Event],
expected_version: Optional[int] = None) -> List[Event]:
"""Append events to a stream with optimistic concurrency."""asyncwithself.pool.acquire() as conn:
asyncwith conn.transaction():
# Check expected versionif expected_version isnotNone:
current = await conn.fetchval(
"SELECT MAX(version) FROM events WHERE stream_id = $1",
stream_id
)
current = current or0if current != expected_version:
raise ConcurrencyError(
f"Expected version {expected_version}, got {current}"
)
# Get starting version
start_version = await conn.fetchval(
"SELECT COALESCE(MAX(version), 0) + 1 FROM events WHERE stream_id = $1",
stream_id
)
# Insert events
saved_events = []
for i, event inenumerate(events):
event.version = start_version + i
row = await conn.fetchrow(
"""
INSERT INTO events (id, stream_id, stream_type, event_type,
event_data, metadata, version, created_at)
VALUES ($1, $2, $3, $4, $5, $6, $7, $8)
RETURNING global_position
""",
event.event_id,
stream_id,
stream_type,
event.event_type,
json.dumps(event.data),
json.dumps(event.metadata),
event.version,
event.created_at
)
event.global_position = row['global_position']
saved_events.append(event)
return saved_events
asyncdefread_stream(
self,
stream_id: str,
from_version: int = 0,
limit: int = 1000) -> List[Event]:
"""Read events from a stream."""asyncwithself.pool.acquire() as conn:
rows = await conn.fetch(
"""
SELECT id, stream_id, event_type, event_data, metadata,
version, global_position, created_at
FROM events
WHERE stream_id = $1 AND version >= $2
ORDER BY version
LIMIT $3
""",
stream_id, from_version, limit
)
return [self._row_to_event(row) for row in rows]
asyncdefread_all(
self,
from_position: int = 0,
limit: int = 1000) -> List[Event]:
"""Read all events globally."""asyncwithself.pool.acquire() as conn:
rows = await conn.fetch(
"""
SELECT id, stream_id, event_type, event_data, metadata,
version, global_position, created_at
FROM events
WHERE global_position > $1
ORDER BY global_position
LIMIT $2
""",
from_position, limit
)
return [self._row_to_event(row) for row in rows]
asyncdefsubscribe(
self,
subscription_id: str,
handler,
from_position: int = 0,
batch_size: int = 100):
"""Subscribe to all events from a position."""# Get checkpointasyncwithself.pool.acquire() as conn:
checkpoint = await conn.fetchval(
"""
SELECT last_position FROM subscription_checkpoints
WHERE subscription_id = $1
""",
subscription_id
)
position = checkpoint or from_position
whileTrue:
events = awaitself.read_all(position, batch_size)
ifnot events:
await asyncio.sleep(1) # Poll intervalcontinuefor event in events:
await handler(event)
position = event.global_position
# Save checkpointasyncwithself.pool.acquire() as conn:
await conn.execute(
"""
INSERT INTO subscription_checkpoints (subscription_id, last_position)
VALUES ($1, $2)
ON CONFLICT (subscription_id)
DO UPDATE SET last_position = $2, updated_at = NOW()
""",
subscription_id, position
)
def_row_to_event(self, row) -> Event:
return Event(
event_id=row['id'],
stream_id=row['stream_id'],
event_type=row['event_type'],
data=json.loads(row['event_data']),
metadata=json.loads(row['metadata']),
version=row['version'],
global_position=row['global_position'],
created_at=row['created_at']
)
classConcurrencyError(Exception):
"""Raised when optimistic concurrency check fails."""pass
Template 3: EventStoreDB Usage
from esdbclient import EventStoreDBClient, NewEvent, StreamState
import json
# Connect
client = EventStoreDBClient(uri="esdb://localhost:2113?tls=false")
# Append eventsdefappend_events(stream_name: str, events: list, expected_revision=None):
new_events = [
NewEvent(
type=event['type'],
data=json.dumps(event['data']).encode(),
metadata=json.dumps(event.get('metadata', {})).encode()
)
for event in events
]
if expected_revision isNone:
state = StreamState.ANY
elif expected_revision == -1:
state = StreamState.NO_STREAM
else:
state = expected_revision
return client.append_to_stream(
stream_name=stream_name,
events=new_events,
current_version=state
)
# Read streamdefread_stream(stream_name: str, from_revision: int = 0):
events = client.get_stream(
stream_name=stream_name,
stream_position=from_revision
)
return [
{
'type': event.type,
'data': json.loads(event.data),
'metadata': json.loads(event.metadata) if event.metadata else {},
'stream_position': event.stream_position,
'commit_position': event.commit_position
}
for event in events
]
# Subscribe to allasyncdefsubscribe_to_all(handler, from_position: int = 0):
subscription = client.subscribe_to_all(commit_position=from_position)
asyncfor event in subscription:
await handler({
'type': event.type,
'data': json.loads(event.data),
'stream_id': event.stream_name,
'position': event.commit_position
})
# Category projection ($ce-Category)defread_category(category: str):
"""Read all events for a category using system projection."""return read_stream(f"$ce-{category}")
Template 4: DynamoDB Event Store
import boto3
from boto3.dynamodb.conditions import Key
from datetime import datetime
import json
import uuid
classDynamoEventStore:
def__init__(self, table_name: str):
self.dynamodb = boto3.resource('dynamodb')
self.table = self.dynamodb.Table(table_name)
defappend_events(self, stream_id: str, events: list, expected_version: int = None):
"""Append events with conditional write for concurrency."""withself.table.batch_writer() as batch:
for i, event inenumerate(events):
version = (expected_version or0) + i + 1
item = {
'PK': f"STREAM#{stream_id}",
'SK': f"VERSION#{version:020d}",
'GSI1PK': 'EVENTS',
'GSI1SK': datetime.utcnow().isoformat(),
'event_id': str(uuid.uuid4()),
'stream_id': stream_id,
'event_type': event['type'],
'event_data': json.dumps(event['data']),
'version': version,
'created_at': datetime.utcnow().isoformat()
}
batch.put_item(Item=item)
return events
defread_stream(self, stream_id: str, from_version: int = 0):
"""Read events from a stream."""
response = self.table.query(
KeyConditionExpression=Key('PK').eq(f"STREAM#{stream_id}") &
Key('SK').gte(f"VERSION#{from_version:020d}")
)
return [
{
'event_type': item['event_type'],
'data': json.loads(item['event_data']),
'version': item['version']
}
for item in response['Items']
]
# Table definition (CloudFormation/Terraform)"""
DynamoDB Table:
- PK (Partition Key): String
- SK (Sort Key): String
- GSI1PK, GSI1SK for global ordering
Capacity: On-demand or provisioned based on throughput needs
"""
Imported: Limitations
Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
