Agent skill
datasource
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/datasource
SKILL.md
/datasource
Create a DataSource note documenting a specific database, table, API endpoint, dataset, or data entity with schema, quality metrics, and access information.
Usage
/datasource <name>
/datasource "SAP Invoices"
/datasource "DataPlatform Revenue Fact Table"
/datasource "Snowflake Customers"
Instructions
Phase 1: Parse Input & Link to System
- Extract data source name
- Ask which system owns this data:
Which system owns this data source? Search: [user searches for System] Or create new System? (Y/n) - Confirm link: "Link to [[System - {{system}}]]? (Y/n)"
Phase 2: Essential Information
Creating DataSource: {{name}} (owned by {{system}})
1️⃣ Data Type:
- database-table (relational table)
- database-view (virtual table)
- api-endpoint (REST/GraphQL data)
- kafka-topic (event stream)
- data-warehouse-table (Snowflake/BigQuery)
- data-lake (file-based storage)
- cache (Redis/Memcached)
Default: database-table
User input: [selection]
2️⃣ Record Count (approximate):
Default: null
User input: [number, e.g., 5000000]
3️⃣ Data Volume per Day:
Default: null
User input: [e.g., "2.5GB", "500K records"]
4️⃣ Refresh Frequency:
- real-time
- hourly
- daily
- weekly
- on-demand
Default: daily
User input: [selection]
5️⃣ Classification:
- public
- internal
- confidential
- secret
Default: internal
User input: [selection]
Phase 3: Data Quality (Optional)
Ask: "Add data quality metrics? (Y/n)"
If YES:
- Completeness (%): 98.5
- Uniqueness (%): 99.9
- Accuracy: high | medium | low
- Timeliness: how fresh (< 5 minutes, < 1 hour, etc.)
Phase 4: Schema & Key Fields
Key Fields (comma-separated):
invoice_id, vendor_id, amount
Then ask:
Schema details needed? (Y/n)
- Parent entities (sources of this data)
- Child entities (what feeds from this)
- Related tables
Phase 5: Access & Consumers
How is this data accessed?
- REST API
- GraphQL
- Direct database query
- Kafka topic
- Batch export / S3
- Other
Default: [based on data type]
Which systems consume this data?
Search: [[System - DataPlatform]]
Add: [[System - Analytics]]
Phase 6: Generate Frontmatter
type: DataSource
title: "{{name}}"
sourceId: "{{sourceId}}"
sourceSystem: "[[System - {{system}}]]"
owner: "[[{{person}}]]"
dataType: {{type}}
recordCount: {{count}}
volumePerDay: "{{volume}}"
refreshFrequency: {{frequency}}
classification: {{classification}}
gdprApplicable: {{gdpr}}
piiFields: [{{pii}}]
completeness: {{completeness}}
uniqueness: {{uniqueness}}
accuracy: {{accuracy}}
timeliness: {{timeliness}}
exposedVia: [rest-api, kafka-topic]
consumerCount: {{consumer_count}}
criticalConsumers: [{{critical_systems}}]
confidence: medium
freshness: current
verified: false
created: 2026-01-14
tags: [type/data-source, {{sourceSystem|lower}}]
Phase 7: Generate Body Content
- Overview: What data this contains
- Data Volume & Performance: Size, growth, refresh
- Data Schema: Sample table structure
- Field Mapping: Key fields explained
- Data Quality: Completeness, accuracy metrics
- Access & Integration: How systems access it
- Security & Governance: Classification, PII, GDPR
- Related Integration Notes: What uses this data
Phase 8: Create File
Filename: DataSource - {{name}}.md
Location: Vault root
Output:
✅ Created: DataSource - {{name}}.md
Linked to:
- [[System - {{owning system}}]]
Next steps:
1. Create integration: /integration {{source}} {{target}}
2. Document consumer systems
3. Add to architecture diagram
Example Interaction
User: /datasource "SAP Invoices"
System: Which system owns this data?
> SAP S/4HANA
Data Type:
> database-table
Record Count:
> 200000000
Volume per Day:
> 5GB
Refresh Frequency:
> hourly
Classification:
> confidential
Data Quality:
Completeness: 98.5
Uniqueness: 99.9
Accuracy: high
Timeliness: < 5 minutes
Key Fields:
> invoice_id, vendor_id, company_code, amount, invoice_date
Consumers (search for Systems):
> DataPlatform
> Snowflake
> Analytics
✅ Created: DataSource - SAP Invoices.md
Updated:
- [[System - SAP S/4HANA]] added to owns/exposes
- [[System - DataPlatform]] added to consumers
- [[System - Snowflake]] added to consumers
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