Agent skill
integration
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/integration
SKILL.md
/integration
Create an Integration note documenting how two systems exchange data, including pattern, protocol, frequency, SLA, and error handling.
Usage
/integration <source-system> <target-system>
/integration SAP DataPlatform
/integration DataPlatform Snowflake --pattern batch
/integration "System - SAP S/4HANA" "System - DataPlatform" --frequency hourly
Instructions
Creates comprehensive Integration notes linking System notes and documenting connection characteristics.
Phase 1: Parse Input & Validate Systems
- Extract source and target system names
- Search vault for both systems:
node scripts/graph-query.js --type System --search "<source>" node scripts/graph-query.js --type System --search "<target>" - If systems not found:
- "[[System - {{name}}]] not found. Create it first? (Y/n)"
- Offer to create System notes before Integration
- If system already integrates, show existing:
- "Found: [[Integration - SAP to DataPlatform]]. Edit instead? (Y/n)"
Phase 2: Essential Information
Gather required fields:
Creating Integration: {{source}} → {{target}}
1️⃣ Integration Pattern:
- api-sync (REST/GraphQL synchronous)
- event-streaming (Kafka/Pub-Sub asynchronous)
- batch-etl (scheduled bulk data transfer)
- message-queue (queued messages with processing)
- file-transfer (SFTP/S3 file exchange)
- database-replication (direct DB sync)
Default: api-sync
User input: [selection]
2️⃣ Protocol:
(Based on pattern selection, suggest defaults)
- For api-sync: rest, graphql, soap, odata
- For event-streaming: kafka, rabbitmq, pubsub
- For batch-etl: s3, sftp, sql
Default: [depends on pattern]
User input: [selection]
3️⃣ Frequency:
- real-time (< 1 second latency)
- near-real-time (< 5 minutes)
- hourly
- daily
- weekly
- on-demand
Default: daily
User input: [selection]
4️⃣ Direction:
- one-way (source → target only)
- bidirectional (source ↔ target)
Default: one-way
User input: [selection]
5️⃣ Criticality:
- critical (business stops if fails)
- high (significant impact)
- medium (moderate impact)
- low (minimal impact)
Default: medium
User input: [selection]
Phase 3: SLA & Performance (Brief)
6️⃣ Availability SLA (%):
Default: 99.5
User input: [number 90-99.99]
7️⃣ Maximum acceptable latency:
For real-time: < 100ms
For batch: < 5 minutes
For daily: no constraint
Default: [based on frequency]
User input: [optional override]
8️⃣ Data volume (records/second or volume/day):
Default: null
User input: [e.g., "500 rec/sec" or "2.5GB/day"]
Phase 4: Middleware & Infrastructure
9️⃣ Does this use middleware?
(Search for integration platforms)
- [[System - Kong]] (API Gateway)
- [[System - Cloud Platform Integration Suite]]
- [[System - Apache Kafka]]
- None (direct connection)
Default: None
User input: [selection]
Phase 5: Error Handling (Optional)
Ask: "Add error handling details? (Y/n)"
If YES:
- Retry strategy: exponential-backoff | linear-backoff | none
- Max retries: 3
- Dead letter queue: enabled | disabled
- Idempotent: yes | no
Phase 6: Generate Frontmatter
type: Integration
title: "{{source}} → {{target}}"
integrationId: "INT-{{source|upper}}-{{target|upper}}-001"
status: active
version: "1.0.0"
sourceSystem: "[[System - {{source}}]]"
targetSystem: "[[System - {{target}}]]"
pattern: {{pattern}}
protocol: [{{protocol}}]
direction: {{direction}}
criticality: {{criticality}}
frequency: {{frequency}}
latency-sla: "{{latency}}"
middleware: {{middleware|null}}
retryPolicy: exponential-backoff
maxRetries: 3
deadLetterQueue: {{dlq|true}}
idempotency: {{idempotency|true}}
slo: "{{sla}}%"
confidence: medium
freshness: current
verified: false
created: 2026-01-14
modified: 2026-01-14
tags: [type/integration, pattern/{{pattern}}, {{source|lower}}-{{target|lower}}]
Phase 7: Generate Body Content
- Overview: What data flows and why
- Data Flow Sequence Diagram: Mermaid sequence showing flow
- Integration Properties Table: Quick reference
- Middleware Details: If applicable
- Protocol & Connection Details: Endpoints, auth, encryption
- Error Handling: Retry logic, DLQ, monitoring
- Monitoring & SLA: Health checks, alerts, dashboards
- Related Architecture: Link to ADRs and Architectures
Phase 8: Update Related Systems
Automatically update both System notes:
- Add this Integration to source System's
connectsTo - Add this Integration to target System's
connectedFrom - Suggest: "Update {{source}} and {{target}} System notes? (Y/n)"
Phase 9: Create File
Filename: Integration - {{source}} to {{target}}.md
Location: Vault root
Output:
✅ Created: Integration - {{source}} to {{target}}.md
Links updated:
- [[System - {{source}}]] → connectsTo added
- [[System - {{target}}]] → connectedFrom added
Next steps:
1. Add data sources: /datasource <name>
2. Generate diagram: /dataflow-diagram [[Project - <name>]]
3. Add to architecture: /architecture --relate-integration <name>
Example Interaction
User: /integration SAP DataPlatform
Skill: Searching for systems...
Found: [[System - SAP S/4HANA]] and [[System - DataPlatform]]
Integration Pattern (default: api-sync):
1. api-sync (REST/GraphQL synchronous)
2. event-streaming (Kafka publish/subscribe)
3. batch-etl (scheduled bulk transfer)
4. message-queue (queued messages)
> 2
Protocol (default: kafka):
> kafka
Frequency (default: daily):
> real-time
Direction (default: one-way):
> one-way
Criticality (default: medium):
> high
Availability SLA (default: 99.5):
> 99.95
Latency (default: < 1 second for real-time):
> < 100ms
Data volume:
> 500 records/second
Middleware:
> None
✅ Created: Integration - SAP to DataPlatform.md
Updated:
- [[System - SAP S/4HANA]] added to connectsTo
- [[System - DataPlatform]] added to connectedFrom
Next: /datasource SAP Invoices
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