Marketplace

data-architecture

Design data architectures with modeling, pipelines, and governance

$ 安裝

git clone https://github.com/pluginagentmarketplace/custom-plugin-software-architect /tmp/custom-plugin-software-architect && cp -r /tmp/custom-plugin-software-architect/skills/data-architecture ~/.claude/skills/custom-plugin-software-architect

// tip: Run this command in your terminal to install the skill


name: data-architecture description: Design data architectures with modeling, pipelines, and governance version: "2.0.0" sasmp_version: "1.3.0" bonded_agent: 06-data-architecture bond_type: PRIMARY_BOND last_updated: "2025-01"

Data Architecture Skill

Purpose

Design data architectures including data models, pipeline designs, governance frameworks, and quality management for operational and analytical systems.


Parameters

ParameterTypeRequiredValidationDefault
data_domainstringmin: 20 chars-
design_typeenummodel|pipeline|governance|qualitymodel
data_typeenumoperational|analytical|streamingoperational
volume_tierenumsmall|medium|large|massivemedium
output_formatenumerd|yaml|jsonerd

Execution Flow

┌──────────────────────────────────────────────────────────┐
│ 1. VALIDATE: Check data domain and requirements          │
│ 2. DISCOVER: Identify data sources and entities          │
│ 3. MODEL: Create conceptual/logical/physical model       │
│ 4. DESIGN: Pipeline or governance framework              │
│ 5. QUALITY: Define data quality rules                    │
│ 6. VALIDATE: Check model consistency                     │
│ 7. DOCUMENT: Return data architecture                    │
└──────────────────────────────────────────────────────────┘

Retry Logic

ErrorRetryBackoffMax Attempts
VALIDATION_ERRORNo-1
MODEL_GENERATION_ERRORYes1s2
FORMAT_ERRORYes500ms3

Logging & Observability

log_points:
  - event: design_started
    level: info
    data: [design_type, data_type]
  - event: entities_identified
    level: info
    data: [entity_count, relationship_count]
  - event: quality_rules_defined
    level: info
    data: [rule_count, dimensions_covered]

metrics:
  - name: models_created
    type: counter
    labels: [design_type]
  - name: design_time_ms
    type: histogram
  - name: entity_count
    type: gauge

Error Handling

Error CodeDescriptionRecovery
E401Missing data domainRequest domain description
E402Invalid relationshipsHighlight circular/missing refs
E403Schema validation failedShow validation errors
E404Unsupported volume tierSuggest architectural changes

Unit Test Template

test_cases:
  - name: "E-commerce data model"
    input:
      data_domain: "E-commerce order management"
      design_type: "model"
      output_format: "erd"
    expected:
      has_entities: true
      entities_include: ["Customer", "Order", "Product"]
      has_relationships: true
      valid_erd: true

  - name: "Analytics pipeline"
    input:
      data_domain: "Customer analytics"
      design_type: "pipeline"
      data_type: "analytical"
    expected:
      has_ingestion: true
      has_transformation: true
      has_serving: true

  - name: "Data quality rules"
    input:
      data_domain: "User profiles"
      design_type: "quality"
    expected:
      has_dimensions: true
      dimensions_include: ["completeness", "accuracy"]
      has_rules: true

Troubleshooting

Common Issues

SymptomRoot CauseResolution
Missing relationshipsIncomplete domainAdd missing entities
Invalid ERD syntaxFormat errorValidate Mermaid ERD
Missing quality rulesDimensions not specifiedAdd quality dimensions

Debug Checklist

□ Is data domain clearly defined?
□ Are all entities identified?
□ Are relationships correctly typed?
□ Is output format valid?
□ Are quality dimensions covered?

Data Quality Dimensions

DimensionExample Rule
CompletenessNOT NULL checks
AccuracyRegex validation
ConsistencyReferential integrity
TimelinessSLA monitoring
UniquenessPrimary key constraints

Integration

ComponentTriggerData Flow
Agent 06Design requestReceives domain, returns model
Agent 04Cloud data servicesCloud data platform

Quality Standards

  • Normalized: 3NF for operational, denormalized for analytical
  • Documented: All entities and relationships described
  • Quality-first: DQ rules for all critical fields

Version History

VersionDateChanges
2.0.02025-01Production-grade: ERD, pipelines, DQ framework
1.0.02024-12Initial release