/dataasset
SkillDev toolsCreate a DataAsset note documenting a data entity - database table, API endpoint, data product, Kafka topic, or file. Captures location, ownership, consumers, and planned changes.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the /dataasset skill
About this capability
A comprehensive knowledge management system for Solutions Architects using AI
What this skill tells your AI
The instructions your AI receives, as published by davidroliverba/architectkb in .claude/skills/dataasset/SKILL.md and read by ahel’s review.
Create a DataAsset note documenting a data entity - database table, API endpoint, data product, Kafka topic, or file. Captures location, ownership, consumers, and planned changes.
Usage
/dataasset <name>
/dataasset "Revenue Fact Table"
/dataasset "Customer Orders"
/dataasset "Maintenance Events"
Instructions
Phase 1: Parse Input & Identify System
- Extract data asset name from input
- Ask which system produces this data:
Which system produces this data? Search: [user searches for System] Or create new System? (Y/n) - Confirm link: "Link to [[System - {{system}}]]? (Y/n)"
Phase 2: Essential Information
Creating DataAsset: {{name}} (produced by {{system}})
1️⃣ Asset ID (unique identifier):
Suggestion: {{SYSTEM}}-{{NAME}}-001
User input: [accept or modify]
2️⃣ Data Type:
- database-table (relational table)
- database-view (virtual table)
- api-endpoint (REST/GraphQL data)
- kafka-topic (event stream)
- data-product (curated dataset)
- data-lake (file-based storage)
- file (CSV, Excel, etc.)
- report (BI report/dashboard)
- cache (Redis/Memcached)
Default: database-table
User input: [selection]
3️⃣ Domain:
- engineering
- data
- operations
- finance
- hr
- supply-chain
- maintenance
Default: [infer from system]
User input: [selection]
4️⃣ Classification:
- public
- internal
- confidential
- secret
Default: internal
User input: [selection]
5️⃣ Storage Location:
Examples: "mydb.fact_revenue", "s3://bucket/path", "/api/v1/orders"
User input: [path/table/endpoint]
6️⃣ Format:
- sql
- json
- parquet
- avro
- csv
- xml
- binary
Default: [infer from data type]
User input: [selection]
Phase 3: Ownership
7️⃣ Data Owner (accountable person):
Search: [[Person - ...]]
User input: [search or skip]
8️⃣ Data Steward (governance contact, optional):
Search: [[Person - ...]]
User input: [search or skip]
Phase 4: Consumer Relationships (Key Differentiator)
Which systems currently consume this data?
Current Consumers (search for Systems):
> [[System - Data Warehouse]]
> [[System - Analytics Platform]]
[Enter blank to finish]
Planned Consumers (systems that WILL consume):
> [[System - New BI Tool]]
[Enter blank to finish]
Deprecating Consumers (systems moving AWAY from this data):
> [[System - Legacy Reporting]]
[Enter blank to finish]
Phase 5: Data Lineage (Optional)
Ask: "Track data lineage? (Y/n)"
If YES:
Derived From (upstream data sources):
> [[DataAsset - Source Invoices]]
[Enter blank to finish]
Feeds Into (downstream data assets):
> [[DataAsset - Revenue Dashboard]]
[Enter blank to finish]
Phase 6: Operational Details (Quick or Full)
Ask: "Quick capture or full detail? (Q/f)"
If Quick - skip to Phase 7 with defaults
If Full:
Refresh Frequency:
- real-time | hourly | daily | weekly | monthly | ad-hoc
Default: daily
Record Count (approximate): [number]
Volume per Day: [e.g., "2.5GB", "500K records"]
Retention Period: [e.g., "7 years", "90 days"]
Data Quality Metrics:
- Completeness (%): [e.g., 98.5]
- Uniqueness (%): [e.g., 99.9]
- Accuracy: high | medium | low
- Timeliness: [e.g., "< 5 minutes"]
SLAs:
- Availability: [e.g., "99.9%"]
- Latency: [e.g., "< 500ms"]
Governance:
- GDPR Applicable: Y/n
- PII Fields: [comma-separated list]
Phase 7: Generate Frontmatter
type: DataAsset
title: "{{name}}"
assetId: "{{assetId}}"
# Classification
domain: {{domain}}
dataType: {{dataType}}
classification: {{classification}}
# Location & Format
sourceSystem: "[[System - {{system}}]]"
storageLocation: "{{location}}"
format: {{format}}
# Ownership
owner: "[[{{owner}}]]"
steward: {{steward}}
# Relationships - Current State
producedBy: ["[[System - {{system}}]]"]
consumedBy: [{{consumers}}]
exposedVia: [{{exposedVia}}]
# Relationships - Future State
plannedConsumers: [{{plannedConsumers}}]
deprecatingConsumers: [{{deprecatingConsumers}}]
# Lineage
derivedFrom: [{{derivedFrom}}]
feedsInto: [{{feedsInto}}]
# Operational Metrics
refreshFrequency: {{frequency}}
recordCount: {{recordCount}}
volumePerDay: "{{volume}}"
retentionPeriod: "{{retention}}"
# Data Quality
completeness: {{completeness}}
uniqueness: {{uniqueness}}
accuracy: {{accuracy}}
timeliness: "{{timeliness}}"
# SLAs
slaAvailability: "{{slaAvailability}}"
slaLatency: "{{slaLatency}}"
# Governance
gdprApplicable: {{gdpr}}
piiFields: [{{piiFields}}]
# Quality Indicators
confidence: medium
freshness: current
verified: false
reviewed: null
created: {{today}}
modified: {{today}}
tags: [type/data-asset, domain/{{domain}}]
Phase 8: Generate Body Content
Create structured body with:
- Overview - What data this contains, business purpose
- Source Details - Table with system, location, format
- Data Relationships - Mermaid diagram showing producers/consumers
- Consumer Systems - Table of current, planned, and deprecating consumers
- Data Lineage - Upstream/downstream flow (if captured)
- Operational Metrics - Volume, refresh, quality (if full detail)
- Security & Governance - Classification, PII, GDPR status
- Related Notes - Links to ADRs, integrations, system notes
Phase 9: Create File
Filename: DataAsset - {{name}}.md
Location: Vault root
Output:
✅ Created: DataAsset - {{name}}.md
Linked to:
- [[System - {{producing system}}]] (producer)
- [[System - {{consumer1}}]] (consumer)
- [[System - {{consumer2}}]] (consumer)
Relationship summary:
- 1 producer
- {{n}} current consumers
- {{n}} planned consumers
- {{n}} deprecating consumers
Next steps:
1. Add to [[MOC - Data Assets]]
2. Create integration notes: /integration {{source}} {{target}}
3. Document data contract if critical
Example Interaction
User: /dataasset "Work Orders"
System: Which system produces this data?
> ERP System
Asset ID suggestion: ERP-WORK-ORDERS-001
> [accept]
Data Type:
> database-table
Domain:
> engineering
Classification:
> internal
Storage Location:
> erp.dbo.work_orders
Format:
> sql
Data Owner:
> [[Data Owner Name]]
Data Steward:
> [skip]
Current Consumers:
> [[System - Data Warehouse]]
> [[System - Analytics Platform]]
> [done]
Planned Consumers:
> [[System - New BI Tool]]
> [done]
Deprecating Consumers:
> [[System - Legacy Reporting]]
> [done]
Track lineage? (Y/n)
> n
Quick or Full detail? (Q/f)
> q
✅ Created: DataAsset - Work Orders.md
Linked to:
- [[System - ERP System]] (producer)
- [[System - Data Warehouse]] (consumer)
- [[System - Analytics Platform]] (consumer)
Relationship summary:
- 1 producer
- 2 current consumers
- 1 planned consumer
- 1 deprecating consumer
Key Differentiators from /datasource
| Aspect | /datasource | /dataasset |
|---|---|---|
| Future state | Not tracked | plannedConsumers, deprecatingConsumers |
| Lineage | Schema-level only | System-level derivedFrom/feedsInto |
| Detail level | Always full | Quick vs Full capture modes |
| Ownership | Single owner | owner + steward |
| SLAs | Not tracked | slaAvailability, slaLatency |
Signals
- GitHub stars
- 52
- Forks
- 12
- Last commit
- Mar 2026
Advanced
- Catalog kind
- skill
- Gateway key
dataasset- Source
- github.com/davidroliverba/architectkb